State reference design and saturated control of doubly-fed induction generators under voltage dips

NASA Astrophysics Data System (ADS)

Tilli, Andrea; Conficoni, Christian; Hashemi, Ahmad

2017-04-01

In this paper, the stator/rotor currents control problem of doubly-fed induction generator under faulty line voltage is carried out. Common grid faults cause a steep decline in the line voltage profile, commonly denoted as voltage dip. This point is critical for such kind of machines, having their stator windings directly connected to the grid. In this respect, solid methodological nonlinear control theory arguments are exploited and applied to design a novel controller, whose main goal is to improve the system behaviour during voltage dips, endowing it with low voltage ride through capability, a fundamental feature required by modern Grid Codes. The proposed solution exploits both feedforward and feedback actions. The feedforward part relies on suitable reference trajectories for the system internal dynamics, which are designed to prevent large oscillations in the rotor currents and command voltages, excited by line perturbations. The feedback part uses state measurements and is designed according to Linear Matrix Inequalities (LMI) based saturated control techniques to further reduce oscillations, while explicitly accounting for the system constraints. Numerical simulations verify the benefits of the internal dynamics trajectory planning, and the saturated state feedback action, in crucially improving the Doubly-Fed Induction Machine response under severe grid faults.

Equivalence Between Squirrel Cage and Sheet Rotor Induction Motor

NASA Astrophysics Data System (ADS)

Dwivedi, Ankita; Singh, S. K.; Srivastava, R. K.

2016-06-01

Due to topological changes in dual stator induction motor and high cost of its fabrication, it is convenient to replace the squirrel cage rotor with a composite sheet rotor. For an experimental machine, the inner and outer stator stampings are normally available whereas the procurement of rotor stampings is quite cumbersome and is not always cost effective. In this paper, the equivalence between sheet/solid rotor induction motor and squirrel cage induction motor has been investigated using layer theory of electrical machines, so as to enable one to utilize sheet/solid rotor in dual port experimental machines.

Induced electric fields in workers near low-frequency induction heating machines.

PubMed

Kos, Bor; Valič, Blaž; Kotnik, Tadej; Gajšek, Peter

2014-04-01

Published data on occupational exposure to induction heating equipment are scarce, particularly in terms of induced quantities in the human body. This article provides some additional information by investigating exposure to two such machines-an induction furnace and an induction hardening machine. Additionally, a spatial averaging algorithm for measured fields we developed in a previous publication is tested on new data. The human model was positioned at distances where measured values of magnetic flux density were above the reference levels. All human exposure was below the basic restriction-the lower bound of the 0.1 top percentile induced electric field in the body of a worker was 0.193 V/m at 30 cm from the induction furnace. © 2013 Wiley Periodicals, Inc.

Hybrid-secondary uncluttered induction machine

DOEpatents

Hsu, John S.

2001-01-01

An uncluttered secondary induction machine (100) includes an uncluttered rotating transformer (66) which is mounted on the same shaft as the rotor (73) of the induction machine. Current in the rotor (73) is electrically connected to current in the rotor winding (67) of the transformer, which is not electrically connected to, but is magnetically coupled to, a stator secondary winding (40). The stator secondary winding (40) is alternately connected to an effective resistance (41), an AC source inverter (42) or a magnetic switch (43) to provide a cost effective slip-energy-controlled, adjustable speed, induction motor that operates over a wide speed range from below synchronous speed to above synchronous speed based on the AC line frequency fed to the stator.

Numerical investigation and electro-acoustic modeling of measurement methods for the in-duct acoustical source parameters.

PubMed

Jang, Seung-Ho; Ih, Jeong-Guon

2003-02-01

It is known that the direct method yields different results from the indirect (or load) method in measuring the in-duct acoustic source parameters of fluid machines. The load method usually comes up with a negative source resistance, although a fairly accurate prediction of radiated noise can be obtained from any method. This study is focused on the effect of the time-varying nature of fluid machines on the output results of two typical measurement methods. For this purpose, a simplified fluid machine consisting of a reservoir, a valve, and an exhaust pipe is considered as representing a typical periodic, time-varying system and the measurement situations are simulated by using the method of characteristics. The equivalent circuits for such simulations are also analyzed by considering the system as having a linear time-varying source. It is found that the results from the load method are quite sensitive to the change of cylinder pressure or valve profile, in contrast to those from the direct method. In the load method, the source admittance turns out to be predominantly dependent on the valve admittance at the calculation frequency as well as the valve and load admittances at other frequencies. In the direct method, however, the source resistance is always positive and the source admittance depends mainly upon the zeroth order of valve admittance.

Effect of Dimension and Shape of Magnet on the Performance AC Generator with Translation Motion

NASA Astrophysics Data System (ADS)

Indriani, A.; Dimas, S.; Hendra

2018-02-01

The development of power plants using the renewable energy sources is very rapid. Renewable energy sources used solar energy, wind energy, ocean wave energy and other energy. All of these renewable energy sources require a processing device or a change of motion system to become electrical energy. One processing device is a generator which have work principle of converting motion (mechanical) energy into electrical energy with rotary shaft, blade and other motion components. Generator consists of several types of rotation motion and linear motion (translational). The generator have components such as rotor, stator and anchor. In the rotor and stator having magnet and winding coil as an electric generating part of the electric motion force. Working principle of AC generator with linear motion (translation) also apply the principle of Faraday that is using magnetic induction which change iron magnet to produce magnetic flux. Magnetic flux is captured by the stator to be converted into electrical energy. Linear motion generators consist of linear induction machine, wound synchronous machine field, and permanent magnet synchronous [1]. Performance of synchronous generator of translation motion is influenced by magnet type, magnetic shape, coil winding, magnetic and coil spacing and others. In this paper focus on the neodymium magnet with varying shapes, number of coil windings and gap of magnetic distances. This generator work by using pneumatic mechanism (PLTGL) for power plants system. Result testing of performance AC generator translation motion obtained that maximum voltage, current and power are 63 Volt for diameter winding coil 0.15 mm, number of winding coil 13000 and distance of magnet 20 mm. For effect shape of magnet, maximum voltage happen on rectangle magnet 30x20x5 mm with 4.64 Volt. Voltage and power on effect of diameter winding coil is 14.63 V and 17.82 W at the diameter winding coil 0.7 and number of winding coil is 1260 with the distance of magnet 25 mm.

Nonlinear Control of the Doubly Fed Induction Motor with Copper Losses Minimization for Electrical Vehicle

NASA Astrophysics Data System (ADS)

Drid, S.; Nait-Said, M.-S.; Tadjine, M.; Makouf, A.

2008-06-01

There is an increasing interest in electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved propulsion system for electric vehicles applications with minimal power losses. This paper deals with the high efficient vector control for the reduction of copper losses of the doubly fed motor. Firstly, the feedback linearization control based on Lyapunov approach is employed to design the underlying controller achieving the double fluxes orientation. The fluxes controllers are designed independently of the speed. The speed controller is designed using the Lyapunov method especially employed to the unknown load torques. The global asymptotic stability of the overall system is theoretically proven. Secondly, a new Torque Copper Losses Factor is proposed to deal with the problem of the machine copper losses. Its main function is to optimize the torque in keeping the machine saturation at an acceptable level. This leads to a reduction in machine currents and therefore their accompanied copper losses guaranteeing improved machine efficiency. The simulation results in comparative presentation confirm largely the effectiveness of the proposed DFIM control with a very interesting energy saving contribution.

A new self-regulated self-excited single-phase induction generator using a squirrel cage three-phase induction machine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fukami, Tadashi; Imamura, Michinori; Kaburaki, Yuichi

1995-12-31

A new single-phase capacitor self-excited induction generator with self-regulating feature is presented. The new generator consists of a squirrel cage three-phase induction machine and three capacitors connected in series and parallel with a single phase load. The voltage regulation of this generator is very small due to the effect of the three capacitors. Moreover, since a Y-connected stator winding is employed, the waveform of the output voltage becomes sinusoidal. In this paper the system configuration and the operating principle of the new generator are explained, and the basic characteristics are also investigated by means of a simple analysis and experimentsmore » with a laboratory machine.« less

Method and device for determining bond separation strength using induction heating

NASA Technical Reports Server (NTRS)

Coultrip, Robert H. (Inventor); Johnson, Samuel D. (Inventor); Copeland, Carl E. (Inventor); Phillips, W. Morris (Inventor); Fox, Robert L. (Inventor)

1994-01-01

An induction heating device includes an induction heating gun which includes a housing, a U-shaped pole piece having two spaced apart opposite ends defining a gap there between, the U-shaped pole piece being mounted in one end of the housing, and a tank circuit including an induction coil wrapped around the pole piece and a capacitor connected to the induction coil. A power source is connected to the tank circuit. A pull test machine is provided having a stationary chuck and a movable chuck, the two chucks holding two test pieces bonded together at a bond region. The heating gun is mounted on the pull test machine in close proximity to the bond region of the two test pieces, whereby when the tank circuit is energized, the two test pieces are heated by induction heating while a tension load is applied to the two test pieces by the pull test machine to determine separation strength of the bond region.

Induction generators for Wind Energy Conversion Systems. Part I: review of induction generator with squirrel cage rotor. Part II: the Double Output Induction Generator (DOIG). Progress report, July-December 1975

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jayadev, T.S.

1976-02-01

The application of induction generators in Wind Energy Conversion Systems (WECS) is described. The conventional induction generator, which is an induction machine with a squirrel cage rotor, had been used in large wind power plants in Europe, but has not caught much attention until now by designers of large systems in this country. The induction generator with a squirrel cage rotor is described and useful design techniques to build induction generators for wind energy application are outlined. The Double Output Induction Generator (DOIG) - so called because power is fed into the grid from the stator, as well as themore » rotor is described. It is a wound rotor induction machine with power electronics to convert rotor slip frequency power to that of line frequency.« less

Analysis and design of asymmetrical reluctance machine

NASA Astrophysics Data System (ADS)

Harianto, Cahya A.

Over the past few decades the induction machine has been chosen for many applications due to its structural simplicity and low manufacturing cost. However, modest torque density and control challenges have motivated researchers to find alternative machines. The permanent magnet synchronous machine has been viewed as one of the alternatives because it features higher torque density for a given loss than the induction machine. However, the assembly and permanent magnet material cost, along with safety under fault conditions, have been concerns for this class of machine. An alternative machine type, namely the asymmetrical reluctance machine, is proposed in this work. Since the proposed machine is of the reluctance machine type, it possesses desirable feature, such as near absence of rotor losses, low assembly cost, low no-load rotational losses, modest torque ripple, and rather benign fault conditions. Through theoretical analysis performed herein, it is shown that this machine has a higher torque density for a given loss than typical reluctance machines, although not as high as the permanent magnet machines. Thus, the asymmetrical reluctance machine is a viable and advantageous machine alternative where the use of permanent magnet machines are undesirable.

Inductive displacement sensors with a notch filter for an active magnetic bearing system.

PubMed

Chen, Seng-Chi; Le, Dinh-Kha; Nguyen, Van-Sum

2014-07-15

Active magnetic bearing (AMB) systems support rotating shafts without any physical contact, using electromagnetic forces. Each radial AMB uses two pairs of electromagnets at opposite sides of the rotor. This allows the rotor to float in the air gap, and the machine to operate without frictional losses. In active magnetic suspension, displacement sensors are necessary to detect the radial and axial movement of the suspended object. In a high-speed rotating machine equipped with an AMB, the rotor bending modes may be limited to the operating range. The natural frequencies of the rotor can cause instability. Thus, notch filters are a useful circuit for stabilizing the system. In addition, commercial displacement sensors are sometimes not suitable for AMB design, and cannot filter the noise caused by the natural frequencies of rotor. Hence, implementing displacement sensors based on the AMB structure is necessary to eliminate noises caused by natural frequency disturbances. The displacement sensor must be highly sensitive in the desired working range, and also exhibit a low interference noise, high stability, and low cost. In this study, we used the differential inductive sensor head and lock-in amplifier for synchronous demodulation. In addition, an active low-pass filter and a notch filter were used to eliminate disturbances, which caused by natural frequencies. As a consequence, the inductive displacement sensor achieved satisfactory linearity, high sensitivity, and disturbance elimination. This sensor can be easily produced for AMB applications. A prototype of these displacement sensors was built and tested.

Sensorless speed detection of squirrel-cage induction machines using stator neutral point voltage harmonics

NASA Astrophysics Data System (ADS)

Petrovic, Goran; Kilic, Tomislav; Terzic, Bozo

2009-04-01

In this paper a sensorless speed detection method of induction squirrel-cage machines is presented. This method is based on frequency determination of the stator neutral point voltage primary slot harmonic, which is dependent on rotor speed. In order to prove method in steady state and dynamic conditions the simulation and experimental study was carried out. For theoretical investigation the mathematical model of squirrel cage induction machines, which takes into consideration actual geometry and windings layout, is used. Speed-related harmonics that arise from rotor slotting are analyzed using digital signal processing and DFT algorithm with Hanning window. The performance of the method is demonstrated over a wide range of load conditions.

Method for reducing peak phase current and decreasing staring time for an internal combustion engine having an induction machine

DOEpatents

Amey, David L.; Degner, Michael W.

2002-01-01

A method for reducing the starting time and reducing the peak phase currents for an internal combustion engine that is started using an induction machine starter/alternator. The starting time is reduced by pre-fluxing the induction machine and the peak phase currents are reduced by reducing the flux current command after a predetermined period of time has elapsed and concurrent to the application of the torque current command. The method of the present invention also provides a strategy for anticipating the start command for an internal combustion engine and determines a start strategy based on the start command and the operating state of the internal combustion engine.

Electro-mechanical energy conversion system having a permanent magnet machine with stator, resonant transfer link and energy converter controls

DOEpatents

Skeist, S. Merrill; Baker, Richard H.

2006-01-10

An electro-mechanical energy conversion system coupled between an energy source and an energy load comprising an energy converter device including a permanent magnet induction machine coupled between the energy source and the energy load to convert the energy from the energy source and to transfer the converted energy to the energy load and an energy transfer multiplexer to control the flow of power or energy through the permanent magnetic induction machine.

Design of motor induction 3-Phase from waste industry to generator for microhydro at isolated village

NASA Astrophysics Data System (ADS)

Rimbawati; Azis Hutasuhut, Abdul; Irsan Pasaribu, Faisal; Cholish; Muharnif

2017-09-01

There is an electric machine that can operate as a generator either single-phase or three-phase in almost every household and industry today. This electric engine cannot be labeled as a generator but can be functioned as a generator. The machine that is mentioned is “squirrel cage motors” or it is well-known as induction motor that can be found in water pumps, washing machines, fans, blowers and other industrial machines. The induction motor can be functioned as a generator when the rotational speed of the rotor is made larger than the speed of the rotary field. In this regard, this study aims to modify the remains of 3-phase induction motor to be a permanent generator. Data of research based conducted on the river flow of Rumah Sumbul Village, STM Hulu district of Deli Serdang. The method of this research is by changing rotor and stator winding on a 3 phase induction motor, so it can produce a generator with rotation speed of 500 rpm. Based on the research, it can be concluded that the output voltage generator has occurred a voltage drop 10% between before and after loading for Star circuit and 2% for Delta circuit.

Impact of equalizing currents on losses and torque ripples in electrical machines with fractional slot concentrated windings

NASA Astrophysics Data System (ADS)

Toporkov, D. M.; Vialcev, G. B.

2017-10-01

The implementation of parallel branches is a commonly used manufacturing method of the realizing of fractional slot concentrated windings in electrical machines. If the rotor eccentricity is enabled in a machine with parallel branches, the equalizing currents can arise. The simulation approach of the equalizing currents in parallel branches of an electrical machine winding based on magnetic field calculation by using Finite Elements Method is discussed in the paper. The high accuracy of the model is provided by the dynamic improvement of the inductances in the differential equation system describing a machine. The pre-computed table flux linkage functions are used for that. The functions are the dependences of the flux linkage of parallel branches on the branches currents and rotor position angle. The functions permit to calculate self-inductances and mutual inductances by partial derivative. The calculated results obtained for the electric machine specimen are presented. The results received show that the adverse combination of design solutions and the rotor eccentricity leads to a high value of the equalizing currents and windings heating. Additional torque ripples also arise. The additional ripples harmonic content is not similar to the cogging torque or ripples caused by the rotor eccentricity.

Optimal Control of Induction Machines to Minimize Transient Energy Losses

NASA Astrophysics Data System (ADS)

Plathottam, Siby Jose

Induction machines are electromechanical energy conversion devices comprised of a stator and a rotor. Torque is generated due to the interaction between the rotating magnetic field from the stator, and the current induced in the rotor conductors. Their speed and torque output can be precisely controlled by manipulating the magnitude, frequency, and phase of the three input sinusoidal voltage waveforms. Their ruggedness, low cost, and high efficiency have made them ubiquitous component of nearly every industrial application. Thus, even a small improvement in their energy efficient tend to give a large amount of electrical energy savings over the lifetime of the machine. Hence, increasing energy efficiency (reducing energy losses) in induction machines is a constrained optimization problem that has attracted attention from researchers. The energy conversion efficiency of induction machines depends on both the speed-torque operating point, as well as the input voltage waveform. It also depends on whether the machine is in the transient or steady state. Maximizing energy efficiency during steady state is a Static Optimization problem, that has been extensively studied, with commercial solutions available. On the other hand, improving energy efficiency during transients is a Dynamic Optimization problem that is sparsely studied. This dissertation exclusively focuses on improving energy efficiency during transients. This dissertation treats the transient energy loss minimization problem as an optimal control problem which consists of a dynamic model of the machine, and a cost functional. The rotor field oriented current fed model of the induction machine is selected as the dynamic model. The rotor speed and rotor d-axis flux are the state variables in the dynamic model. The stator currents referred to as d-and q-axis currents are the control inputs. A cost functional is proposed that assigns a cost to both the energy losses in the induction machine, as well as the deviations from desired speed-torque-magnetic flux setpoints. Using Pontryagin's minimum principle, a set of necessary conditions that must be satisfied by the optimal control trajectories are derived. The conditions are in the form a two-point boundary value problem, that can be solved numerically. The conjugate gradient method that was modified using the Hestenes-Stiefel formula was used to obtain the numerical solution of both the control and state trajectories. Using the distinctive shape of the numerical trajectories as inspiration, analytical expressions were derived for the state, and control trajectories. It was shown that the trajectory could be fully described by finding the solution of a one-dimensional optimization problem. The sensitivity of both the optimal trajectory and the optimal energy efficiency to different induction machine parameters were analyzed. A non-iterative solution that can use feedback for generating optimal control trajectories in real time was explored. It was found that an artificial neural network could be trained using the numerical solutions and made to emulate the optimal control trajectories with a high degree of accuracy. Hence a neural network along with a supervisory logic was implemented and used in a real-time simulation to control the Finite Element Method model of the induction machine. The results were compared with three other control regimes and the optimal control system was found to have the highest energy efficiency for the same drive cycle.

Mask induction despite circuit obstruction: an unrecognized hazard of relying on automated machine check technology.

PubMed

Yang, Kamie K; Lewis, Ian H

2014-06-15

Various equipment malfunctions of anesthesia gas delivery systems have been previously reported. Our profession increasingly uses technology as a means to prevent these errors. We report a case of a near-total anesthesia circuit obstruction that went undetected before the induction of anesthesia despite the use of automated machine check technology. This case highlights that automated machine check modules can fail to detect severe equipment failure and demonstrates how, even in this era of expanding technology, manual checks still remain essential components of safe care.

The reflection of evolving bearing faults in the stator current's extended park vector approach for induction machines

NASA Astrophysics Data System (ADS)

Corne, Bram; Vervisch, Bram; Derammelaere, Stijn; Knockaert, Jos; Desmet, Jan

2018-07-01

Stator current analysis has the potential of becoming the most cost-effective condition monitoring technology regarding electric rotating machinery. Since both electrical and mechanical faults are detected by inexpensive and robust current-sensors, measuring current is advantageous on other techniques such as vibration, acoustic or temperature analysis. However, this technology is struggling to breach into the market of condition monitoring as the electrical interpretation of mechanical machine-problems is highly complicated. Recently, the authors built a test-rig which facilitates the emulation of several representative mechanical faults on an 11 kW induction machine with high accuracy and reproducibility. Operating this test-rig, the stator current of the induction machine under test can be analyzed while mechanical faults are emulated. Furthermore, while emulating, the fault-severity can be manipulated adaptively under controllable environmental conditions. This creates the opportunity of examining the relation between the magnitude of the well-known current fault components and the corresponding fault-severity. This paper presents the emulation of evolving bearing faults and their reflection in the Extended Park Vector Approach for the 11 kW induction machine under test. The results confirm the strong relation between the bearing faults and the stator current fault components in both identification and fault-severity. Conclusively, stator current analysis increases reliability in the application as a complete, robust, on-line condition monitoring technology.

Harmonic reduction of Direct Torque Control of six-phase induction motor.

PubMed

Taheri, A

2016-07-01

In this paper, a new switching method in Direct Torque Control (DTC) of a six-phase induction machine for reduction of current harmonics is introduced. Selecting a suitable vector in each sampling period is an ordinal method in the ST-DTC drive of a six-phase induction machine. The six-phase induction machine has 64 voltage vectors and divided further into four groups. In the proposed DTC method, the suitable voltage vectors are selected from two vector groups. By a suitable selection of two vectors in each sampling period, the harmonic amplitude is decreased more, in and various comparison to that of the ST-DTC drive. The harmonics loss is greater reduced, while the electromechanical energy is decreased with switching loss showing a little increase. Spectrum analysis of the phase current in the standard and new switching table DTC of the six-phase induction machine and determination for the amplitude of each harmonics is proposed in this paper. The proposed method has a less sampling time in comparison to the ordinary method. The Harmonic analyses of the current in the low and high speed shows the performance of the presented method. The simplicity of the proposed method and its implementation without any extra hardware is other advantages of the proposed method. The simulation and experimental results show the preference of the proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Linear motor drive system for continuous-path closed-loop position control of an object

DOEpatents

Barkman, William E.

1980-01-01

A precision numerical controlled servo-positioning system is provided for continuous closed-loop position control of a machine slide or platform driven by a linear-induction motor. The system utilizes filtered velocity feedback to provide system stability required to operate with a system gain of 100 inches/minute/0.001 inch of following error. The filtered velocity feedback signal is derived from the position output signals of a laser interferometer utilized to monitor the movement of the slide. Air-bearing slides mounted to a stable support are utilized to minimize friction and small irregularities in the slideway which would tend to introduce positioning errors. A microprocessor is programmed to read command and feedback information and converts this information into the system following error signal. This error signal is summed with the negative filtered velocity feedback signal at the input of a servo amplifier whose output serves as the drive power signal to the linear motor position control coil.

Energy saving concepts relating to induction generators

NASA Technical Reports Server (NTRS)

Nola, F. J.

1980-01-01

Energy saving concepts relating to induction generators are presented. The first describes a regenerative scheme using an induction generator as a variable load for prime movers under test is described. A method for reducing losses in induction machines used specifically as wind driven generators is also described.

Contributions a l'etude et a l'application industrielle de la machine asynchrone

NASA Astrophysics Data System (ADS)

Ouhrouche, Mohand-Ameziane

The work presented in this thesis, done in the Electrical Drives Laboratory of Electrical and Computer Engineering Department, deals with the industrial applications of a three-phase induction machine (electrical drives and electricity generation). This thesis, characterized by its multidisciplinary content, has two major parts. The first one deals with the on-line and off-line parametric identification of the induction machine model necessary to achieve accurate vector control strategy. The second part, which is a resume of a research work sponsored by Hydro-Quebec, deals with the application of an induction machine in Asynchronous Non Utility Generators units (ANUG). As it is shown in the following, major scientific contributions are made in both two parts. In the first part of our research work, we propose a new speed sensorless vector control strategy for an induction machine, which is adaptive to the rotor resistance variations. The proposed control strategy is based on the Extended Kalman Filter approach and a decoupling controller which takes into account the rotor resistance variations. The consideration of coupled electrical and mechanical modes leads to a fifth order nonlinear model of the induction machine. The load torque is taken as a function of the rotor angular speed. The Extended Kalman Filter, based on the process's nonlinear (bilinear) model, estimate simultaneously the rotor resistance, angular speed and the flux vector from the startup to the steady state equilibrium point. The machine-converter-control system is implemented in MATLAB/SIMULINK environment and the obtained results confirm the robustness of the proposed scheme. As in the electrical drives erea, the induction machine is now widely used by small to medium power Non Utility Generator units (NUG) to produce electricity. In Quebec, these NUGs units are integrated into the Hydro-Quebec 25 kV distribution system via transformer which exhibit nonlinear characteristics. We have shown by using the ElectroMagnetic Program (EMTP) that, in some islanding scenarios, i.e. that the NUG unit is disconnected from the power grid, in addition to frequency variations, appearence of high an abnormal overvoltages, ferroresonance should occur. As a consequence, normal protective devices could fail to securely operate, which could cause serious damages to the equipment and the maintenance staff. This result, established for the first time , can be useful to improve the reliability of the NUGs units and is considered important by the power engineering community. This has led to a publication in the John Wiley & Sons Encyclopedia of Electrical and Electronics Engineering which will be available in February 1999 ( http://www.engr.wisc.edu/ ece/ece).

Investigation of a tubular dual-stator flux-switching permanent-magnet linear generator for free-piston energy converter

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Tong, Chengde; Yu, Bin; Zhu, Shaohong; Zhu, Jianguo

2015-05-01

This paper describes a tubular dual-stator flux-switching permanent-magnet (PM) linear generator for free-piston energy converter. The operating principle, topology, and design considerations of the machine are investigated. Combining the motion characteristic of free-piston Stirling engine, a tubular dual-stator PM linear generator is designed by finite element method. Some major structural parameters, such as the outer and inner radii of the mover, PM thickness, mover tooth width, tooth width of the outer and inner stators, etc., are optimized to improve the machine performances like thrust capability and power density. In comparison with conventional single-stator PM machines like moving-magnet linear machine and flux-switching linear machine, the proposed dual-stator flux-switching PM machine shows advantages in higher mass power density, higher volume power density, and lighter mover.

Detection of inter-turn short-circuit at start-up of induction machine based on torque analysis

NASA Astrophysics Data System (ADS)

Pietrowski, Wojciech; Górny, Konrad

2017-12-01

Recently, interest in new diagnostics methods in a field of induction machines was observed. Research presented in the paper shows the diagnostics of induction machine based on torque pulsation, under inter-turn short-circuit, during start-up of a machine. In the paper three numerical techniques were used: finite element analysis, signal analysis and artificial neural networks (ANN). The elaborated numerical model of faulty machine consists of field, circuit and motion equations. Voltage excited supply allowed to determine the torque waveform during start-up. The inter-turn short-circuit was treated as a galvanic connection between two points of the stator winding. The waveforms were calculated for different amounts of shorted-turns from 0 to 55. Due to the non-stationary waveforms a wavelet packet decomposition was used to perform an analysis of the torque. The obtained results of analysis were used as input vector for ANN. The response of the neural network was the number of shorted-turns in the stator winding. Special attention was paid to compare response of general regression neural network (GRNN) and multi-layer perceptron neural network (MLP). Based on the results of the research, the efficiency of the developed algorithm can be inferred.

Impact of wind generator infed on dynamic performance of a power system

NASA Astrophysics Data System (ADS)

Alam, Md. Ahsanul

Wind energy is one of the most prominent sources of electrical energy in the years to come. A tendency to increase the amount of electricity generation from wind turbine can be observed in many countries. One of the major concerns related to the high penetration level of the wind energy into the existing power grid is its influence on power system dynamic performance. In this thesis, the impact of wind generation system on power system dynamic performance is investigated through detailed dynamic modeling of the entire wind generator system considering all the relevant components. Nonlinear and linear models of a single machine as well as multimachine wind-AC system have been derived. For the dynamic model of integrated wind-AC system, a general transformation matrix is determined for the transformation of machine and network quantities to a common reference frame. Both time-domain and frequency domain analyses on single machine and multimachine systems have been carried out. The considered multimachine systems are---A 4 machine 12 bus system, and 10 machine 39 bus New England system. Through eigenvalue analysis, impact of asynchronous wind system on overall network damping has been quantified and modes responsible for the instability have been identified. Over with a number of simulation studies it is observed that for a induction generator based wind generation system, the fixed capacitor located at the generator terminal cannot normally cater for the reactive power demand during the transient disturbances like wind gust and fault on the system. For weak network connection, system instability may be initiated because of induction generator terminal voltage collapse under certain disturbance conditions. Incorporation of dynamic reactive power compensation scheme through either variable susceptance control or static compensator (STATCOM) is found to improve the dynamic performance significantly. Further improvement in transient profile has been brought in by supporting STATCOM with bulk energy storage devices. Two types of energy storage system (ESS) have been considered---battery energy storage system, and supercapacitor based energy storage system. A decoupled P -- Q control strategy has been implemented on STATCOM/ESS. It is observed that wind generators when supported by STATCOM/ESS can achieve significant withstand capability in the presence of grid fault of reasonable duration. It experiences almost negligible rotor speed variation, maintains constant terminal voltage, and resumes delivery of smoothed (almost transient free) power to the grid immediately after the fault is cleared. Keywords: Wind energy, induction generator, dynamic performance of wind generators, energy storage system, decoupled P -- Q control, multimachine system.

Induction machine

DOEpatents

Owen, Whitney H.

1980-01-01

A polyphase rotary induction machine for use as a motor or generator utilizing a single rotor assembly having two series connected sets of rotor windings, a first stator winding disposed around the first rotor winding and means for controlling the current induced in one set of the rotor windings compared to the current induced in the other set of the rotor windings. The rotor windings may be wound rotor windings or squirrel cage windings.

Direct Torque Control of a Three-Phase Voltage Source Inverter-Fed Induction Machine

DTIC Science & Technology

2013-12-01

factors, FOC acquires all advantages of DC machine control and frees itself from the mechanical commutation drawbacks. Furthermore, FOC leads to high...of three-phase induction motor using microcontroller,” S.R.M Engineering College, Tamil Nadu, India , June/July 2006. [5] Texas Instruments Europe...loop. Direct flux control is possible through the constant magnetic field orientation achieved through commutator action. These two primary factors

Comparison of Linear Induction Motor Theories for the LIMRV and TLRV Motors

DOT National Transportation Integrated Search

1978-01-01

The Oberretl, Yamamura, and Mosebach theories of the linear induction motor are described and also applied to predict performance characteristics of the TLRV & LIMRV linear induction motors. The effect of finite motor width and length on performance ...

Performance testing of a high frequency link converter for Space Station power distribution system

NASA Technical Reports Server (NTRS)

Sul, S. K.; Alan, I.; Lipo, T. A.

1989-01-01

The testing of a brassboard version of a 20-kHz high-frequency ac voltage link prototype converter dynamics for Space Station application is presented. The converter is based on a three-phase six-pulse bridge concept. The testing includes details of the operation of the converter when it is driving an induction machine source/load. By adapting a field orientation controller (FOC) to the converter, four-quadrant operation of the induction machine from the converter has been achieved. Circuit modifications carried out to improve the performance of the converter are described. The performance of two 400-Hz induction machines powered by the converter with simple V/f regulation mode is reported. The testing and performance results for the converter utilizing the FOC, which provides the capability for rapid torque changes, speed reversal, and four-quadrant operation, are reported.

Magnetic properties of Fe-Si steel depending on compressive and tensile stresses under sinusoidal and distorted excitations

NASA Astrophysics Data System (ADS)

Permiakov, V.; Pulnikov, A.; Dupré, L.; De Wulf, M.; Melkebeek, J.

2003-05-01

In this article, the magnetic properties of nonoriented electrical steel under sinusoidal and distorted excitations are investigated for the whole range of unidirectional mechanical stresses. The distorted flux obtained from the tooth tip of 3 kW induction machine at no-load test was put into the measurement system. The total losses increase for compressive stress both under sinusoidal and distorted excitations. For tensile elastic stresses, the total losses first decrease and then increase in a very similar way for both excitations. In contrast, the difference between total losses under sinusoidal and distorted magnetic fluxes becomes smaller with increase of the plastic strain. This work is a serious step toward complete characterization of the magnetic properties of electrical steel in the teeth area of induction machines. A deeper insight of that problem can improve the design of induction machines and other electromagnetic devices.

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window

PubMed Central

Burriel-Valencia, Jordi; Martinez-Roman, Javier; Sapena-Bano, Angel

2018-01-01

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current’s spectrogram with a significant reduction of the required computational resources. PMID:29316650

Fault Diagnosis of Induction Machines in a Transient Regime Using Current Sensors with an Optimized Slepian Window.

PubMed

Burriel-Valencia, Jordi; Puche-Panadero, Ruben; Martinez-Roman, Javier; Sapena-Bano, Angel; Pineda-Sanchez, Manuel

2018-01-06

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that for a given sequence length of finite duration, the Slepian window has the maximum concentration of energy, greater than can be reached with a gated Gaussian window, which is usually used as the analysis window. In this paper, the use and optimization of the Slepian window for fault diagnosis of induction machines is theoretically introduced and experimentally validated through the test of a 3.15-MW induction motor with broken bars during the start-up transient. The theoretical analysis and the experimental results show that the use of the Slepian window can highlight the fault components in the current's spectrogram with a significant reduction of the required computational resources.

Geophysical investigation of the June 6, 1944 D-Day invasion site at Pointe du Hoc, Normandy, France

NASA Astrophysics Data System (ADS)

Everett, M. E.; Pierce, C. J.; Warden, R. R.; Burt, R. A.

2005-05-01

A near-surface geophysical survey at the D-Day invasion site atop the cliffs at Pointe du Hoc, Normandy, France was carried out using ground-penetrating radar, electromagnetic induction, and magnetic gradiometry equipment. The subsurface targets of investigation are predominantly buried concrete and steel structures and earthworks associated with the German coastal fortifications at this stronpoint of Hitler's Atlantic Wall. The targets are readily detectable embedded within the vadose zone of a weakly magnetic, electrically resistive loess soil cover. The radar and electromagnetic induction responses lend themselves to plan-view imaging of the subsurface, while the magnetics data reveal the presence of buried magnetic bodies in a more subtle fashion. Several intriguing geophysical signatures were discovered, including what may be the buried remains of a railway turntable, ordnance fragments in the bomb craters, a buried steel-reinforced concrete trench, and a linear chain of machine gun firing positins. Geophysical prospecting is shown to be a very powerful tool for historical battlefield characterization.

A new capacitive long-range displacement nanometer sensor with differential sensing structure based on time-grating

NASA Astrophysics Data System (ADS)

Yu, Zhicheng; Peng, Kai; Liu, Xiaokang; Pu, Hongji; Chen, Ziran

2018-05-01

High-precision displacement sensors, which can measure large displacements with nanometer resolution, are key components in many ultra-precision fabrication machines. In this paper, a new capacitive nanometer displacement sensor with differential sensing structure is proposed for long-range linear displacement measurements based on an approach denoted time grating. Analytical models established using electric field coupling theory and an area integral method indicate that common-mode interference will result in a first-harmonic error in the measurement results. To reduce the common-mode interference, the proposed sensor design employs a differential sensing structure, which adopts a second group of induction electrodes spatially separated from the first group of induction electrodes by a half-pitch length. Experimental results based on a prototype sensor demonstrate that the measurement accuracy and the stability of the sensor are substantially improved after adopting the differential sensing structure. Finally, a prototype sensor achieves a measurement accuracy of  ±200 nm over the full 200 mm measurement range of the sensor.

Large-Scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation

DTIC Science & Technology

2016-08-10

AFRL-AFOSR-JP-TR-2016-0073 Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation ...2016 4.  TITLE AND SUBTITLE Large-scale Linear Optimization through Machine Learning: From Theory to Practical System Design and Implementation 5a...performances on various machine learning tasks and it naturally lends itself to fast parallel implementations . Despite this, very little work has been

Acoustic sensor for real-time control for the inductive heating process

DOEpatents

Kelley, John Bruce; Lu, Wei-Yang; Zutavern, Fred J.

2003-09-30

Disclosed is a system and method for providing closed-loop control of the heating of a workpiece by an induction heating machine, including generating an acoustic wave in the workpiece with a pulsed laser; optically measuring displacements of the surface of the workpiece in response to the acoustic wave; calculating a sub-surface material property by analyzing the measured surface displacements; creating an error signal by comparing an attribute of the calculated sub-surface material properties with a desired attribute; and reducing the error signal below an acceptable limit by adjusting, in real-time, as often as necessary, the operation of the inductive heating machine.

Modeling of Geometric Error in Linear Guide Way to Improved the vertical three-axis CNC Milling machine’s accuracy

NASA Astrophysics Data System (ADS)

Kwintarini, Widiyanti; Wibowo, Agung; Arthaya, Bagus M.; Yuwana Martawirya, Yatna

2018-03-01

The purpose of this study was to improve the accuracy of three-axis CNC Milling Vertical engines with a general approach by using mathematical modeling methods of machine tool geometric errors. The inaccuracy of CNC machines can be caused by geometric errors that are an important factor during the manufacturing process and during the assembly phase, and are factors for being able to build machines with high-accuracy. To improve the accuracy of the three-axis vertical milling machine, by knowing geometric errors and identifying the error position parameters in the machine tool by arranging the mathematical modeling. The geometric error in the machine tool consists of twenty-one error parameters consisting of nine linear error parameters, nine angle error parameters and three perpendicular error parameters. The mathematical modeling approach of geometric error with the calculated alignment error and angle error in the supporting components of the machine motion is linear guide way and linear motion. The purpose of using this mathematical modeling approach is the identification of geometric errors that can be helpful as reference during the design, assembly and maintenance stages to improve the accuracy of CNC machines. Mathematically modeling geometric errors in CNC machine tools can illustrate the relationship between alignment error, position and angle on a linear guide way of three-axis vertical milling machines.

Linear positioning laser calibration setup of CNC machine tools

NASA Astrophysics Data System (ADS)

Sui, Xiulin; Yang, Congjing

2002-10-01

The linear positioning laser calibration setup of CNC machine tools is capable of executing machine tool laser calibraiotn and backlash compensation. Using this setup, hole locations on CNC machien tools will be correct and machien tool geometry will be evaluated and adjusted. Machien tool laser calibration and backlash compensation is a simple and straightforward process. First the setup is to 'find' the stroke limits of the axis. Then the laser head is then brought into correct alignment. Second is to move the machine axis to the other extreme, the laser head is now aligned, using rotation and elevation adjustments. Finally the machine is moved to the start position and final alignment is verified. The stroke of the machine, and the machine compensation interval dictate the amount of data required for each axis. These factors determine the amount of time required for a through compensation of the linear positioning accuracy. The Laser Calibrator System monitors the material temperature and the air density; this takes into consideration machine thermal growth and laser beam frequency. This linear positioning laser calibration setup can be used on CNC machine tools, CNC lathes, horizontal centers and vertical machining centers.

Magnetic Launch Assist Experimental Track

NASA Technical Reports Server (NTRS)

1999-01-01

In this photograph, a futuristic spacecraft model sits atop a carrier on the Magnetic Launch Assist System, formerly known as the Magnetic Levitation (MagLev) System, experimental track at the Marshall Space Flight Center (MSFC). Engineers at MSFC have developed and tested Magnetic Launch Assist technologies that would use magnetic fields to levitate and accelerate a vehicle along a track at very high speeds. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, a Magnetic Launch Assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide, and about 1.5-feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Research Technology

NASA Image and Video Library

2001-03-01

Engineers at the Marshall Space Flight Center (MSFC) have been testing Magnetic Launch Assist Systems, formerly known as Magnetic Levitation (MagLev) technologies. To launch spacecraft into orbit, a Magnetic Launch Assist system would use magnetic fields to levitate and accelerate a vehicle along a track at a very high speed. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, the launch-assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This photograph shows a subscale model of an airplane running on the experimental track at MSFC during the demonstration test. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide, and about 1.5- feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Research Technology

NASA Image and Video Library

1999-10-01

In this photograph, a futuristic spacecraft model sits atop a carrier on the Magnetic Launch Assist System, formerly known as the Magnetic Levitation (MagLev) System, experimental track at the Marshall Space Flight Center (MSFC). Engineers at MSFC have developed and tested Magnetic Launch Assist technologies that would use magnetic fields to levitate and accelerate a vehicle along a track at very high speeds. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, a Magnetic Launch Assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide, and about 1.5-feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Induction machine bearing faults detection based on a multi-dimensional MUSIC algorithm and maximum likelihood estimation.

PubMed

Elbouchikhi, Elhoussin; Choqueuse, Vincent; Benbouzid, Mohamed

2016-07-01

Condition monitoring of electric drives is of paramount importance since it contributes to enhance the system reliability and availability. Moreover, the knowledge about the fault mode behavior is extremely important in order to improve system protection and fault-tolerant control. Fault detection and diagnosis in squirrel cage induction machines based on motor current signature analysis (MCSA) has been widely investigated. Several high resolution spectral estimation techniques have been developed and used to detect induction machine abnormal operating conditions. This paper focuses on the application of MCSA for the detection of abnormal mechanical conditions that may lead to induction machines failure. In fact, this paper is devoted to the detection of single-point defects in bearings based on parametric spectral estimation. A multi-dimensional MUSIC (MD MUSIC) algorithm has been developed for bearing faults detection based on bearing faults characteristic frequencies. This method has been used to estimate the fundamental frequency and the fault related frequency. Then, an amplitude estimator of the fault characteristic frequencies has been proposed and fault indicator has been derived for fault severity measurement. The proposed bearing faults detection approach is assessed using simulated stator currents data, issued from a coupled electromagnetic circuits approach for air-gap eccentricity emulating bearing faults. Then, experimental data are used for validation purposes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Measurement of LHCD antenna position in Aditya tokamak

NASA Astrophysics Data System (ADS)

Ambulkar, K. K.; Sharma, P. K.; Virani, C. G.; Parmar, P. R.; Thakur, A. L.; Kulkarni, S. V.

2010-02-01

To drive plasma current non-inductively in ADITYA tokamak, 120 kW pulsed Lower Hybrid Current Drive (LHCD) system at 3.7 GHz has been designed, fabricated and installed on ADITYA tokamak. In this system, the antenna consists of a grill structure, having two rows, each row comprising of four sub-waveguides. The coupling of LHCD power to the plasma strongly depends on the plasma density near the mouth of grill antenna. Thus the grill antenna has to be precisely positioned for efficient coupling. The movement of mechanical bellow, which contracts or expands up to 50mm, governs the movement of antenna. In order to monitor the position of the antenna precisely, the reference position of the antenna with respect to the machine/plasma position has to be accurately determined. Further a mechanical system or an electronic system to measure the relative movement of the antenna with respect to the reference position is also desired. Also due to poor accessibility inside the ADITYA machine, it is impossible to measure physically the reference position of the grill antenna with respect to machine wall, taken as reference position and hence an alternative method has to be adopted to establish these measurements reliably. In this paper we report the design and development of a mechanism, using which the antenna position measurements are made. It also describes a unique method employing which the measurements of the reference position of the antenna with respect to the inner edge of the tokamak wall is carried out, which otherwise was impossible due to poor accessibility and physical constraints. The position of the antenna is monitored using an electronic scale, which is developed and installed on the bellow. Once the reference position is derived, the linear potentiometer, attached to the bellow, measures the linear distance using position transmitter. The accuracy of measurement obtained in our setup is within +/- 0.5 % and the linearity, along with repeatability is excellent.

Advanced Propulsion Power Distribution System for Next Generation Electric/Hybrid Vehicle. Phase 1; Preliminary System Studies

NASA Technical Reports Server (NTRS)

Bose, Bimal K.; Kim, Min-Huei

1995-01-01

The report essentially summarizes the work performed in order to satisfy the above project objective. In the beginning, different energy storage devices, such as battery, flywheel and ultra capacitor are reviewed and compared, establishing the superiority of the battery. Then, the possible power sources, such as IC engine, diesel engine, gas turbine and fuel cell are reviewed and compared, and the superiority of IC engine has been established. Different types of machines for drive motor/engine generator, such as induction machine, PM synchronous machine and switched reluctance machine are compared, and the induction machine is established as the superior candidate. Similar discussion was made for power converters and devices. The Insulated Gate Bipolar Transistor (IGBT) appears to be the most superior device although Mercury Cadmium Telluride (MCT) shows future promise. Different types of candidate distribution systems with the possible combinations of power and energy sources have been discussed and the most viable system consisting of battery, IC engine and induction machine has been identified. Then, HFAC system has been compared with the DC system establishing the superiority of the former. The detailed component sizing calculations of HFAC and DC systems reinforce the superiority of the former. A preliminary control strategy has been developed for the candidate HFAC system. Finally, modeling and simulation study have been made to validate the system performance. The study in the report demonstrates the superiority of HFAC distribution system for next generation electric/hybrid vehicle.

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes.

PubMed

Vogl, Gregory W; Weiss, Brian A; Donmez, M Alkan

2015-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a 'sensor box' to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality.

A Sensor-Based Method for Diagnostics of Machine Tool Linear Axes

PubMed Central

Vogl, Gregory W.; Weiss, Brian A.; Donmez, M. Alkan

2017-01-01

A linear axis is a vital subsystem of machine tools, which are vital systems within many manufacturing operations. When installed and operating within a manufacturing facility, a machine tool needs to stay in good condition for parts production. All machine tools degrade during operations, yet knowledge of that degradation is illusive; specifically, accurately detecting degradation of linear axes is a manual and time-consuming process. Thus, manufacturers need automated and efficient methods to diagnose the condition of their machine tool linear axes without disruptions to production. The Prognostics and Health Management for Smart Manufacturing Systems (PHM4SMS) project at the National Institute of Standards and Technology (NIST) developed a sensor-based method to quickly estimate the performance degradation of linear axes. The multi-sensor-based method uses data collected from a ‘sensor box’ to identify changes in linear and angular errors due to axis degradation; the sensor box contains inclinometers, accelerometers, and rate gyroscopes to capture this data. The sensors are expected to be cost effective with respect to savings in production losses and scrapped parts for a machine tool. Numerical simulations, based on sensor bandwidth and noise specifications, show that changes in straightness and angular errors could be known with acceptable test uncertainty ratios. If a sensor box resides on a machine tool and data is collected periodically, then the degradation of the linear axes can be determined and used for diagnostics and prognostics to help optimize maintenance, production schedules, and ultimately part quality. PMID:28691039

Torque shudder protection device and method

DOEpatents

King, Robert D.; De Doncker, Rik W. A. A.; Szczesny, Paul M.

1997-01-01

A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency.

Torque shudder protection device and method

DOEpatents

King, R.D.; Doncker, R.W.A.A. De.; Szczesny, P.M.

1997-03-11

A torque shudder protection device for an induction machine includes a flux command generator for supplying a steady state flux command and a torque shudder detector for supplying a status including a negative status to indicate a lack of torque shudder and a positive status to indicate a presence of torque shudder. A flux adapter uses the steady state flux command and the status to supply a present flux command identical to the steady state flux command for a negative status and different from the steady state flux command for a positive status. A limiter can receive the present flux command, prevent the present flux command from exceeding a predetermined maximum flux command magnitude, and supply the present flux command to a field oriented controller. After determining a critical electrical excitation frequency at which a torque shudder occurs for the induction machine, a flux adjuster can monitor the electrical excitation frequency of the induction machine and adjust a flux command to prevent the monitored electrical excitation frequency from reaching the critical electrical excitation frequency. 5 figs.

A solid-state controller for a wind-driven slip-ring induction generator

NASA Astrophysics Data System (ADS)

Velayudhan, C.; Bundell, J. H.; Leary, B. G.

1984-08-01

The three-phase induction generator appears to become the preferred choice for wind-powered systems operated in parallel with existing power systems. A problem arises in connection with the useful operating speed range of the squirrel-cage machine, which is relatively narrow, as, for instance, in the range from 1 to 1.15. Efficient extraction of energy from a wind turbine, on the other hand, requires a speed range, perhaps as large as 1 to 3. One approach for 'matching' the generator to the turbine for the extraction of maximum power at any usable wind speed involves the use of a slip-ring induction machine. The power demand of the slip-ring machine can be matched to the available output from the wind turbine by modifying the speed-torque characteristics of the generator. A description is presented of a simple electronic rotor resistance controller which can optimize the power taken from a wind turbine over the full speed range.

Proceedings of the Workshop on Change of Representation and Problem Reformulation

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

The proceedings of the third Workshop on Change of representation and Problem Reformulation is presented. In contrast to the first two workshops, this workshop was focused on analytic or knowledge-based approaches, as opposed to statistical or empirical approaches called 'constructive induction'. The organizing committee believes that there is a potential for combining analytic and inductive approaches at a future date. However, it became apparent at the previous two workshops that the communities pursuing these different approaches are currently interested in largely non-overlapping issues. The constructive induction community has been holding its own workshops, principally in conjunction with the machine learning conference. While this workshop is more focused on analytic approaches, the organizing committee has made an effort to include more application domains. We have greatly expanded from the origins in the machine learning community. Participants in this workshop come from the full spectrum of AI application domains including planning, qualitative physics, software engineering, knowledge representation, and machine learning.

Pole-phase modulated toroidal winding for an induction machine

DOEpatents

Miller, John Michael; Ostovic, Vlado

1999-11-02

A stator (10) for an induction machine for a vehicle has a cylindrical core (12) with inner and outer slots (26, 28) extending longitudinally along the inner and outer peripheries between the end faces (22, 24). Each outer slot is associated with several adjacent inner slots. A plurality of toroidal coils (14) are wound about the core and laid in the inner and outer slots. Each coil occupies a single inner slot and is laid in the associated outer slot thereby minimizing the distance the coil extends from the end faces and minimizing the length of the induction machine. The toroidal coils are configured for an arbitrary pole phase modulation wherein the coils are configured with variable numbers of phases and poles for providing maximum torque for cranking and switchable to a another phase and pole configuration for alternator operation. An adaptor ring (36) circumferentially positioned about the stator improves mechanical strength, and provides a coolant channel manifold (34) for removing heat produced in stator windings during operation.

Tuning the Magnetic Transport of an Induction LINAC using Emittance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Houck, T L; Brown, C G; Ong, M M

2006-08-11

The Lawrence Livermore National Laboratory Flash X-Ray (FXR) machine is a linear induction accelerator used to produce a nominal 18 MeV, 3 kA, 65 ns pulse width electron beam for hydrodynamic radiographs. A common figure of merit for this type of radiographic machine is the x-ray dose divided by the spot area on the bremsstrahlung converter where a higher FOM is desired. Several characteristics of the beam affect the minimum attainable x-ray spot size. The most significant are emittance (chaotic transverse energy), chromatic aberration (energy variation), and beam motion (transverse instabilities and corkscrew motion). FXR is in the midst ofmore » a multi-year optimization project to reduce the spot size. This paper describes the effort to reduce beam emittance by adjusting the fields of the transport solenoids and position of the cathode. If the magnetic transport is not correct, the beam will be mismatched and undergo envelope oscillations increasing the emittance. We measure the divergence and radius of the beam in a drift section after the accelerator by imaging the optical transition radiation (OTR) and beam envelope on a foil. These measurements are used to determine an emittance. Relative changes in the emittance can be quickly estimated from the foil measurements allowing for an efficient, real-time study. Once an optimized transport field is determined, the final focus can be adjusted and the new x-ray spot measured. A description of the diagnostics and analysis is presented.« less

A single-phase axially-magnetized permanent-magnet oscillating machine for miniature aerospace power sources

NASA Astrophysics Data System (ADS)

Sui, Yi; Zheng, Ping; Cheng, Luming; Wang, Weinan; Liu, Jiaqi

2017-05-01

A single-phase axially-magnetized permanent-magnet (PM) oscillating machine which can be integrated with a free-piston Stirling engine to generate electric power, is investigated for miniature aerospace power sources. Machine structure, operating principle and detent force characteristic are elaborately studied. With the sinusoidal speed characteristic of the mover considered, the proposed machine is designed by 2D finite-element analysis (FEA), and some main structural parameters such as air gap diameter, dimensions of PMs, pole pitches of both stator and mover, and the pole-pitch combinations, etc., are optimized to improve both the power density and force capability. Compared with the three-phase PM linear machines, the proposed single-phase machine features less PM use, simple control and low controller cost. The power density of the proposed machine is higher than that of the three-phase radially-magnetized PM linear machine, but lower than the three-phase axially-magnetized PM linear machine.

Free electron lasers driven by linear induction accelerators: High power radiation sources

NASA Technical Reports Server (NTRS)

Orzechowski, T. J.

1989-01-01

The technology of Free Electron Lasers (FELs) and linear induction accelerators (LIAs) is addressed by outlining the following topics: fundamentals of FELs; basic concepts of linear induction accelerators; the Electron Laser Facility (a microwave FEL); PALADIN (an infrared FEL); magnetic switching; IMP; and future directions (relativistic klystrons). This presentation is represented by viewgraphs only.

Specification for Teaching Machines and Programmes (Interchangeability of Programmes). Part 1, Linear Machines and Programmes.

ERIC Educational Resources Information Center

British Standards Institution, London (England).

To promote interchangeability of teaching machines and programs, so that the user is not so limited in his choice of programs, the British Standards Institute has offered a standard. Part I of the standard deals with linear teaching machines and programs that make use of the roll or sheet methods of presentation. Requirements cover: spools,…

Inductional Effects in a Halbach Magnet Motion Above Distributed Inductance

NASA Astrophysics Data System (ADS)

Tchatchoua, Yves; Conrow, Ary; Kim, Dong; Morgan, Daniel; Majewski, Walerian; Zafar, Zaeema

2013-03-01

We experimented with attempts to levitate a linear (bar) Halbach array of five 1'' Nd magnets above a linear inductive track. Next, in order to achieve a control over the relative velocity, we designed a different experiment. In it a large wheel with circumferentially positioned along its rim inducting coils rotates, while the magnet is suspended directly above the rim of the wheel on a force sensor. Faraday's Law with the Lenz's Rule is responsible for the lifting and drag forces on the magnet; the horizontal drag force is measured by another force sensor. Approximating the magnet's linear relative motion over inductors with a motion along a large circle, we may use formulas derived earlier in the literature for linear inductive levitation. We measured lift and drag forces as functions of relative velocity of the Halbach magnet and the inductive ``track,'' in an approximate agreement with the existing theory. We then vary the inductance and shape of the inductive elements to find the most beneficial choice for the lift/drag ratio at the lowest relative speed.

Intrusion Detection Systems with Live Knowledge System

DTIC Science & Technology

2016-05-31

Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR, which is a machine-learning based RDR...propose novel approach that uses Ripple -down Rule (RDR) to maintain the knowledge from human experts with knowledge base generated by the Induct RDR...detection model by applying Induct RDR approach. The proposed induct RDR ( Ripple Down Rules) approach allows to acquire the phishing detection

Study of Environmental Data Complexity using Extreme Learning Machine

NASA Astrophysics Data System (ADS)

Leuenberger, Michael; Kanevski, Mikhail

2017-04-01

The main goals of environmental data science using machine learning algorithm deal, in a broad sense, around the calibration, the prediction and the visualization of hidden relationship between input and output variables. In order to optimize the models and to understand the phenomenon under study, the characterization of the complexity (at different levels) should be taken into account. Therefore, the identification of the linear or non-linear behavior between input and output variables adds valuable information for the knowledge of the phenomenon complexity. The present research highlights and investigates the different issues that can occur when identifying the complexity (linear/non-linear) of environmental data using machine learning algorithm. In particular, the main attention is paid to the description of a self-consistent methodology for the use of Extreme Learning Machines (ELM, Huang et al., 2006), which recently gained a great popularity. By applying two ELM models (with linear and non-linear activation functions) and by comparing their efficiency, quantification of the linearity can be evaluated. The considered approach is accompanied by simulated and real high dimensional and multivariate data case studies. In conclusion, the current challenges and future development in complexity quantification using environmental data mining are discussed. References - Huang, G.-B., Zhu, Q.-Y., Siew, C.-K., 2006. Extreme learning machine: theory and applications. Neurocomputing 70 (1-3), 489-501. - Kanevski, M., Pozdnoukhov, A., Timonin, V., 2009. Machine Learning for Spatial Environmental Data. EPFL Press; Lausanne, Switzerland, p.392. - Leuenberger, M., Kanevski, M., 2015. Extreme Learning Machines for spatial environmental data. Computers and Geosciences 85, 64-73.

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Magnetic Launch Assist System Demonstration Test

NASA Technical Reports Server (NTRS)

2001-01-01

Engineers at the Marshall Space Flight Center (MSFC) have been testing Magnetic Launch Assist Systems, formerly known as Magnetic Levitation (MagLev) technologies. To launch spacecraft into orbit, a Magnetic Launch Assist system would use magnetic fields to levitate and accelerate a vehicle along a track at a very high speed. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, the launch-assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This photograph shows a subscale model of an airplane running on the experimental track at MSFC during the demonstration test. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide, and about 1.5- feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Magnetic Launch Assist Demonstration Test

NASA Technical Reports Server (NTRS)

2001-01-01

This image shows a 1/9 subscale model vehicle clearing the Magnetic Launch Assist System, formerly referred to as the Magnetic Levitation (MagLev), test track during a demonstration test conducted at the Marshall Space Flight Center (MSFC). Engineers at MSFC have developed and tested Magnetic Launch Assist technologies. To launch spacecraft into orbit, a Magnetic Launch Assist System would use magnetic fields to levitate and accelerate a vehicle along a track at very high speeds. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, a launch-assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide and about 1.5-feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Research Technology

NASA Image and Video Library

2001-03-01

This image shows a 1/9 subscale model vehicle clearing the Magnetic Launch Assist System, formerly referred to as the Magnetic Levitation (MagLev), test track during a demonstration test conducted at the Marshall Space Flight Center (MSFC). Engineers at MSFC have developed and tested Magnetic Launch Assist technologies. To launch spacecraft into orbit, a Magnetic Launch Assist System would use magnetic fields to levitate and accelerate a vehicle along a track at very high speeds. Similar to high-speed trains and roller coasters that use high-strength magnets to lift and propel a vehicle a couple of inches above a guideway, a launch-assist system would electromagnetically drive a space vehicle along the track. A full-scale, operational track would be about 1.5-miles long and capable of accelerating a vehicle to 600 mph in 9.5 seconds. This track is an advanced linear induction motor. Induction motors are common in fans, power drills, and sewing machines. Instead of spinning in a circular motion to turn a shaft or gears, a linear induction motor produces thrust in a straight line. Mounted on concrete pedestals, the track is 100-feet long, about 2-feet wide and about 1.5-feet high. The major advantages of launch assist for NASA launch vehicles is that it reduces the weight of the take-off, the landing gear, the wing size, and less propellant resulting in significant cost savings. The US Navy and the British MOD (Ministry of Defense) are planning to use magnetic launch assist for their next generation aircraft carriers as the aircraft launch system. The US Army is considering using this technology for launching target drones for anti-aircraft training.

Assessment of Advanced Logistics Delivery System (ALDS) Launch Systems Concepts

DTIC Science & Technology

2004-10-01

highest force vs. rotor weight required, allows much higher magnetic field generation than the linear induction or linear permanent magnet motors , and...provides the highest force vs. rotor weight required, allows much higher magnetic generation than the linear induction or linear permanent magnet motors , and

Comparison of effects of overload on parameters and performance of samarium-cobalt and strontium-ferrite radially oriented permanent magnet brushless DC motors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Demerdash, N.A.; Nehl, T.W.; Nyamusa, T.A.

1985-08-01

Effects of high momentary overloads on the samarium-cobalt and strontium-ferrite permanent magnets and the magnetic field in electronically commutated brushless dc machines, as well as their impact on the associated machine parameters were studied. The effect of overload on the machine parameters, and subsequently on the machine system performance was also investigated. This was accomplished through the combined use of finite element analysis of the magnetic field in such machines, perturbation of the magnetic energies to determine machine inductances, and dynamic simulation of the performance of brushless dc machines, when energized from voltage source inverters. These effects were investigated throughmore » application of the above methods to two equivalent 15 hp brushless dc motors, one of which was built with samarium-cobalt magnets, while the other was built with strontium- ferrite magnets. For momentary overloads as high as 4.5 p.u. magnet flux reductions of 29% and 42% of the no load flux were obtained in the samarium-cobalt and strontiumferrite machines, respectively. Corresponding reductions in the line to line armature inductances of 52% and 46% of the no load values were reported for the samarium-cobalt and strontium-ferrite cases, respectively. The overload affected the profiles and magnitudes of armature induced back emfs. Subsequently, the effects of overload on machine parameters were found to have significant impact on the performance of the machine systems, where findings indicate that the samarium-cobalt unit is more suited for higher overload duties than the strontium-ferrite machine.« less

Study on magnetic force of electromagnetic levitation circular knitting machine

NASA Astrophysics Data System (ADS)

Wu, X. G.; Zhang, C.; Xu, X. S.; Zhang, J. G.; Yan, N.; Zhang, G. Z.

2018-06-01

The structure of the driving coil and the electromagnetic force of the test prototype of electromagnetic-levitation (EL) circular knitting machine are studied. In this paper, the driving coil’s structure and working principle of the EL circular knitting machine are firstly introduced, then the mathematical modelling analysis of the driving electromagnetic force is carried out, and through the Ansoft Maxwell finite element simulation software the coil’s magnetic induction intensity and the needle’s electromagnetic force is simulated, finally an experimental platform is built to measure the coil’s magnetic induction intensity and the needle’s electromagnetic force. The results show that the theoretical analysis, the simulation analysis and the results of the test are very close, which proves the correctness of the proposed model.

A novel single-phase flux-switching permanent magnet linear generator used for free-piston Stirling engine

NASA Astrophysics Data System (ADS)

Zheng, Ping; Sui, Yi; Tong, Chengde; Bai, Jingang; Yu, Bin; Lin, Fei

2014-05-01

This paper investigates a novel single-phase flux-switching permanent-magnet (PM) linear machine used for free-piston Stirling engines. The machine topology and operating principle are studied. A flux-switching PM linear machine is designed based on the quasi-sinusoidal speed characteristic of the resonant piston. Considering the performance of back electromotive force and thrust capability, some leading structural parameters, including the air gap length, the PM thickness, the ratio of the outer radius of mover to that of stator, the mover tooth width, the stator tooth width, etc., are optimized by finite element analysis. Compared with conventional three-phase moving-magnet linear machine, the proposed single-phase flux-switching topology shows advantages in less PM use, lighter mover, and higher volume power density.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly utilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilizes induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Induction motor control

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1990-01-01

Electromechanical actuators developed to date have commonly ultilized permanent magnet (PM) synchronous motors. More recently switched reluctance (SR) motors have been advocated due to their robust characteristics. Implications of work which utilized induction motors and advanced control techniques are discussed. When induction motors are operated from an energy source capable of controlling voltages and frequencies independently, drive characteristics are obtained which are superior to either PM or SR motors. By synthesizing the machine frequency from a high-frequency carrier (nominally 20 kHz), high efficiencies, low distortion, and rapid torque response are available. At this time multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of aerospace actuators. This effort is based upon high-frequency power distribution and management techniques developed by NASA for Space Station Freedom.

Four quadrant control of induction motors

NASA Technical Reports Server (NTRS)

Hansen, Irving G.

1991-01-01

Induction motors are the nation's workhorse, being the motor of choice in most applications due to their simple rugged construction. It has been estimated that 14 to 27 percent of the country's total electricity use could be saved with adjustable speed drives. Until now, induction motors have not been suited well for variable speed or servo-drives, due to the inherent complexity, size, and inefficiency of their variable speed controls. Work at NASA Lewis Research Center on field oriented control of induction motors using pulse population modulation method holds the promise for the desired drive electronics. The system allows for a variable voltage to frequency ratio which enables the user to operate the motor at maximum efficiency, while having independent control of both the speed and torque of an induction motor in all four quadrants of the speed torque map. Multiple horsepower machine drives were demonstrated, and work is on-going to develop a 20 hp average, 40 hp peak class of machine. The pulse population technique, results to date, and projections for implementation of this existing new motor control technology are discussed.

DIRECT SIMULATION OF A-C MACHINERY.

DTIC Science & Technology

show the application of the simulation to both induction and synchronous machines. The fundamental space harmonic only, the fundamental and third ... space harmonic only, or all the space harmonics are considered. The report concludes that: (1) Successful direct simulation of the 2-phase induction

On the Stability of Jump-Linear Systems Driven by Finite-State Machines with Markovian Inputs

NASA Technical Reports Server (NTRS)

Patilkulkarni, Sudarshan; Herencia-Zapana, Heber; Gray, W. Steven; Gonzalez, Oscar R.

2004-01-01

This paper presents two mean-square stability tests for a jump-linear system driven by a finite-state machine with a first-order Markovian input process. The first test is based on conventional Markov jump-linear theory and avoids the use of any higher-order statistics. The second test is developed directly using the higher-order statistics of the machine s output process. The two approaches are illustrated with a simple model for a recoverable computer control system.

Etude analytique du fonctionnement des moteurs à réluctance alimentés à fréquence variable

NASA Astrophysics Data System (ADS)

Sargos, F. M.; Gudefin, E. J.; Zaskalicky, P.

1995-03-01

In switched reluctance motors fed by a constant voltage source (like a battery) at high frequencies, the current becomes unpredictable and often cannot reach a given reference value, because of the variation of the inductances with the rotor position ; the “motional” m.m.f. generates commutation troubles which increase with the frequency. An optimal control as well as an approximate design of the motor require a quick and simple calculation of currents, powers and losses ; now, in principle, the non-linear electrical equation needs a numerical resolution, whose results cannot be extrapolated. By linearizing this equation by intervals, the method proposed here allows to express analytically, in any case, the phase currents, the torque and the copper losses, when the feeding voltage itself is constant by intervals. The model neglects saturation, but a simple adjustment of the inductance (chosen ad libitum) allows to deal with it. The calculation is immediate and perfectly accurate as long as the machine parameters themselves are well defined. Some results are given as examples for two usual feeding modes. Dans les machines à réluctance alimentées à haute fréquence par une source à tension constante, comme une batterie, le courant varie de manière difficilement prévisible, à cause de la variation des inductances avec la position du rotor, et souvent ne parvient pas à s'établir à une valeur de consigne imposée ; la f.é.m. “motionnelle” engendre des difficultés de communication qui s'aggravent avec l'augmentation de fréquence jusqu'à empêcher le fonctionnement. Tant pour optimiser la commande que pour dimensionner approximativement un moteur ; on doit pouvoir calculer simplement et rapidement le courant et la puissance ; or l'équation électrique, non linéaire, doit en principe être résolue numériquement et les résultats ne sont pratiquement pas extrapolables. En linéarisant par intervalles cette équation, la méthode proposée ici permer d'exprimer analytiquement et dans tous les cas les courants de phase, la puissance fournie et les pertes Joule, lorsque la tension aux bornes de l'enroulement est constante par morceaux. Le modèle utilisé néglige la saturation ; mais il est possible de tenir compte de celle-ci par des ajustements, facilement calculables, de la courbe d'inductance, quelle que soit son allure. Les calculs sont immédiats et parfaitement précis pour autant que les paramètres soient bien définis. Quelques résultats sont donnés à titre d'exemple, pour deux modes d'alimentation usuels.

High efficiency machining technology and equipment for edge chamfer of KDP crystals

NASA Astrophysics Data System (ADS)

Chen, Dongsheng; Wang, Baorui; Chen, Jihong

2016-10-01

Potassium dihydrogen phosphate (KDP) is a type of nonlinear optical crystal material. To Inhibit the transverse stimulated Raman scattering of laser beam and then enhance the optical performance of the optics, the edges of the large-sized KDP crystal needs to be removed to form chamfered faces with high surface quality (RMS<5 nm). However, as the depth of cut (DOC) of fly cutting is usually several, its machining efficiency is too low to be accepted for chamfering of the KDP crystal as the amount of materials to be removed is in the order of millimeter. This paper proposes a novel hybrid machining method, which combines precision grinding with fly cutting, for crackless and high efficiency chamfer of KDP crystal. A specialized machine tool, which adopts aerostatic bearing linear slide and aerostatic bearing spindle, was developed for chamfer of the KDP crystal. The aerostatic bearing linear slide consists of an aerostatic bearing guide with linearity of 0.1 μm/100mm and a linear motor to achieve linear feeding with high precision and high dynamic performance. The vertical spindle consists of an aerostatic bearing spindle with the rotation accuracy (axial) of 0.05 microns and Fork type flexible connection precision driving mechanism. The machining experiment on flying and grinding was carried out, the optimize machining parameters was gained by a series of experiment. Surface roughness of 2.4 nm has been obtained. The machining efficiency can be improved by six times using the combined method to produce the same machined surface quality.

Determination of efficiencies, loss mechanisms, and performance degradation factors in chopper controlled dc vehical motors. Section 2: The time dependent finite element modeling of the electromagnetic field in electrical machines: Methods and applications. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hamilton, H. B.; Strangas, E.

1980-01-01

The time dependent solution of the magnetic field is introduced as a method for accounting for the variation, in time, of the machine parameters in predicting and analyzing the performance of the electrical machines. The method of time dependent finite element was used in combination with an also time dependent construction of a grid for the air gap region. The Maxwell stress tensor was used to calculate the airgap torque from the magnetic vector potential distribution. Incremental inductances were defined and calculated as functions of time, depending on eddy currents and saturation. The currents in all the machine circuits were calculated in the time domain based on these inductances, which were continuously updated. The method was applied to a chopper controlled DC series motor used for electric vehicle drive, and to a salient pole sychronous motor with damper bars. Simulation results were compared to experimentally obtained ones.

Pinch current limitation effect in plasma focus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, S.; Saw, S. H.; INTI International University College, 71800 Nilai

The Lee model couples the electrical circuit with plasma focus dynamics, thermodynamics, and radiation. It is used to design and simulate experiments. A beam-target mechanism is incorporated, resulting in realistic neutron yield scaling with pinch current and increasing its versatility for investigating all Mather-type machines. Recent runs indicate a previously unsuspected 'pinch current limitation' effect. The pinch current does not increase beyond a certain value however low the static inductance is reduced to. The results indicate that decreasing the present static inductance of the PF1000 machine will neither increase the pinch current nor the neutron yield, contrary to expectations.

Volumetric Verification of Multiaxis Machine Tool Using Laser Tracker

PubMed Central

Aguilar, Juan José

2014-01-01

This paper aims to present a method of volumetric verification in machine tools with linear and rotary axes using a laser tracker. Beyond a method for a particular machine, it presents a methodology that can be used in any machine type. Along this paper, the schema and kinematic model of a machine with three axes of movement, two linear and one rotational axes, including the measurement system and the nominal rotation matrix of the rotational axis are presented. Using this, the machine tool volumetric error is obtained and nonlinear optimization techniques are employed to improve the accuracy of the machine tool. The verification provides a mathematical, not physical, compensation, in less time than other methods of verification by means of the indirect measurement of geometric errors of the machine from the linear and rotary axes. This paper presents an extensive study about the appropriateness and drawbacks of the regression function employed depending on the types of movement of the axes of any machine. In the same way, strengths and weaknesses of measurement methods and optimization techniques depending on the space available to place the measurement system are presented. These studies provide the most appropriate strategies to verify each machine tool taking into consideration its configuration and its available work space. PMID:25202744

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

Asynchronous machine rotor speed estimation using a tabulated numerical approach

NASA Astrophysics Data System (ADS)

Nguyen, Huu Phuc; De Miras, Jérôme; Charara, Ali; Eltabach, Mario; Bonnet, Stéphane

2017-12-01

This paper proposes a new method to estimate the rotor speed of the asynchronous machine by looking at the estimation problem as a nonlinear optimal control problem. The behavior of the nonlinear plant model is approximated off-line as a prediction map using a numerical one-step time discretization obtained from simulations. At each time-step, the speed of the induction machine is selected satisfying the dynamic fitting problem between the plant output and the predicted output, leading the system to adopt its dynamical behavior. Thanks to the limitation of the prediction horizon to a single time-step, the execution time of the algorithm can be completely bounded. It can thus easily be implemented and embedded into a real-time system to observe the speed of the real induction motor. Simulation results show the performance and robustness of the proposed estimator.

Cage-rotor induction motor inter-turn short circuit fault detection with and without saturation effect by MEC model.

PubMed

Naderi, Peyman

2016-09-01

The inter-turn short fault for the Cage-Rotor-Induction-Machine (CRIM) is studied in this paper and its local saturation is taken into account. However, in order to observe the exact behavior of machine, the Magnetic-Equivalent-Circuit (MEC) and nonlinear B-H curve are proposed to provide an insight into the machine model and saturation effect respectively. The electrical machines are generally operated near to their saturation zone due to some design necessities. Hence, when the machine is exposed to a fault such as short circuit or eccentricities, it is operated within its saturation zone and thus, time and space harmonics are integrated and as a result, current and torque harmonics are generated which the phenomenon cannot be explored when saturation is dismissed. Nonetheless, inter-turn short circuit may lead to local saturation and this occurrence is studied in this paper using MEC model. In order to achieve the mentioned objectives, two and also four-pole machines are modeled as two samples and the machines performances are analyzed in healthy and faulty cases with and without saturation effect. A novel strategy is proposed to precisely detect inter-turn short circuit fault according to the stator׳s lines current signatures and the accuracy of the proposed method is verified by experimental results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Induction motor speed drive improvement using fuzzy IP-self-tuning controller. A real time implementation.

PubMed

Lokriti, Abdesslam; Salhi, Issam; Doubabi, Said; Zidani, Youssef

2013-05-01

An IP-self-tuning controller tuned by a fuzzy adjustor, is proposed to improve induction machine speed control. The interest of such controller is the possibility to adjust only one gain, instead of two gains for the case of the PI-self-tuning controllers commonly used in the literature. This paper presents simulation and experimental results. These latter were obtained by practical implementation on a DSPace 1104 board of three different speed controllers (the classical IP, the fuzzy-like-PI and the IP-self-tuning), for a 1.5KW induction machine. The paper presents different tests used to compare the performances of the proposed controller to the two others in terms of computation time, tracking performances and disturbances rejection. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Numerical calculation of primary slot leakage inductance of a Single-sided HTS linear induction motor used for linear metro

NASA Astrophysics Data System (ADS)

Li, Dong; Wen, Yinghong; Li, Weili; Fang, Jin; Cao, Junci; Zhang, Xiaochen; Lv, Gang

2017-03-01

In the paper, the numerical method calculating asymmetric primary slot leakage inductances of Single-sided High-Temperature Superconducting (HTS) Linear Induction Motor (HTS LIM) is presented. The mathematical and geometric models of three-dimensional nonlinear transient electromagnetic field are established and the boundary conditions are also given. The established model is solved by time-stepping Finite Element Method (FEM). Then, the three-phase asymmetric primary slot leakage inductances under different operation conditions are calculated by using the obtained electromagnetic field distribution. The influences of the special effects such as longitudinal end effects, transversal edge effects, etc. on the primary slot leakage inductance are investigated. The presented numerical method is validated by experiments carried out on a 3.5 kW prototype with copper wires which has the same structures with the HTS LIM.

Miniature Gas-Circulating Machine

NASA Technical Reports Server (NTRS)

Swift, Walter L.; Valenzuela, Javier A.; Sixsmith, Herbert; Nutt, William E.

1993-01-01

Proposed gas-circulating machine consists essentially of centrifugal pump driven by induction motor. Noncontact bearings suppress wear and contamination. Used to circulate helium (or possibly hydrogen or another gas) in regeneration sorption-compressor refrigeration system aboard spacecraft. Also proves useful in terrestrial applications in which long life, reliability, and low contamination essential.

Performance Analysis of Saturated Induction Motors by Virtual Tests

ERIC Educational Resources Information Center

Ojaghi, M.; Faiz, J.; Kazemi, M.; Rezaei, M.

2012-01-01

Many undergraduate-level electrical machines textbooks give detailed treatments of the performance of induction motors. Students can deepen this understanding of motor performance by performing the appropriate practical work in laboratories or in simulation using proper software packages. This paper considers various common and less-common tests…

Machine learning-based methods for prediction of linear B-cell epitopes.

PubMed

Wang, Hsin-Wei; Pai, Tun-Wen

2014-01-01

B-cell epitope prediction facilitates immunologists in designing peptide-based vaccine, diagnostic test, disease prevention, treatment, and antibody production. In comparison with T-cell epitope prediction, the performance of variable length B-cell epitope prediction is still yet to be satisfied. Fortunately, due to increasingly available verified epitope databases, bioinformaticians could adopt machine learning-based algorithms on all curated data to design an improved prediction tool for biomedical researchers. Here, we have reviewed related epitope prediction papers, especially those for linear B-cell epitope prediction. It should be noticed that a combination of selected propensity scales and statistics of epitope residues with machine learning-based tools formulated a general way for constructing linear B-cell epitope prediction systems. It is also observed from most of the comparison results that the kernel method of support vector machine (SVM) classifier outperformed other machine learning-based approaches. Hence, in this chapter, except reviewing recently published papers, we have introduced the fundamentals of B-cell epitope and SVM techniques. In addition, an example of linear B-cell prediction system based on physicochemical features and amino acid combinations is illustrated in details.

Predicting the dissolution kinetics of silicate glasses using machine learning

NASA Astrophysics Data System (ADS)

Anoop Krishnan, N. M.; Mangalathu, Sujith; Smedskjaer, Morten M.; Tandia, Adama; Burton, Henry; Bauchy, Mathieu

2018-05-01

Predicting the dissolution rates of silicate glasses in aqueous conditions is a complex task as the underlying mechanism(s) remain poorly understood and the dissolution kinetics can depend on a large number of intrinsic and extrinsic factors. Here, we assess the potential of data-driven models based on machine learning to predict the dissolution rates of various aluminosilicate glasses exposed to a wide range of solution pH values, from acidic to caustic conditions. Four classes of machine learning methods are investigated, namely, linear regression, support vector machine regression, random forest, and artificial neural network. We observe that, although linear methods all fail to describe the dissolution kinetics, the artificial neural network approach offers excellent predictions, thanks to its inherent ability to handle non-linear data. Overall, we suggest that a more extensive use of machine learning approaches could significantly accelerate the design of novel glasses with tailored properties.

Steels with controlled hardenability for induction hardening

NASA Astrophysics Data System (ADS)

Shepelyakovskii, K. Z.

1980-07-01

Steels of the CH and LH type developed in the Soviet Union permit the use of a new method of induction hardening — bulk-surface hardening — and efficient utilization of the high-strength conditions (σb = 230-250 kgf/mm2). These steels make it possible to improve the structural strength, operating characteristics, service life, and reliability of critical heavily loaded machine parts. At the same time, CH steels make it possible to reduce by a factor of 2-3 the quantity of alloying elements, reduce the electrical energy for heat treatment, and completely exclude the cost of quenching oil for heat treatment in automatic equipment with high labor productivity, while retaining good working conditions. All this leads to substantial savings in production and operation. For example, when transmission gears (cylindrical and conical) are manufactured from LH steels the annual savings amount to more than 700,000 rubles at two automobile plants. Machine parts of CH steels — half axles and bearings in railway cars —have saved respectively six and four million rubles annually. The introduction of controlled-hardenability steels for induction hardening is a necessary condition for technological progress in machine construction and metallurgy.

Improving Machining Accuracy of CNC Machines with Innovative Design Methods

NASA Astrophysics Data System (ADS)

Yemelyanov, N. V.; Yemelyanova, I. V.; Zubenko, V. L.

2018-03-01

The article considers achieving the machining accuracy of CNC machines by applying innovative methods in modelling and design of machining systems, drives and machine processes. The topological method of analysis involves visualizing the system as matrices of block graphs with a varying degree of detail between the upper and lower hierarchy levels. This approach combines the advantages of graph theory and the efficiency of decomposition methods, it also has visual clarity, which is inherent in both topological models and structural matrices, as well as the resiliency of linear algebra as part of the matrix-based research. The focus of the study is on the design of automated machine workstations, systems, machines and units, which can be broken into interrelated parts and presented as algebraic, topological and set-theoretical models. Every model can be transformed into a model of another type, and, as a result, can be interpreted as a system of linear and non-linear equations which solutions determine the system parameters. This paper analyses the dynamic parameters of the 1716PF4 machine at the stages of design and exploitation. Having researched the impact of the system dynamics on the component quality, the authors have developed a range of practical recommendations which have enabled one to reduce considerably the amplitude of relative motion, exclude some resonance zones within the spindle speed range of 0...6000 min-1 and improve machining accuracy.

Voltage regulation in linear induction accelerators

DOEpatents

Parsons, William M.

1992-01-01

Improvement in voltage regulation in a Linear Induction Accelerator wherein a varistor, such as a metal oxide varistor, is placed in parallel with the beam accelerating cavity and the magnetic core. The non-linear properties of the varistor result in a more stable voltage across the beam accelerating cavity than with a conventional compensating resistance.

Structural Design Optimization of Doubly-Fed Induction Generators Using GeneratorSE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sethuraman, Latha; Fingersh, Lee J; Dykes, Katherine L

2017-11-13

A wind turbine with a larger rotor swept area can generate more electricity, however, this increases costs disproportionately for manufacturing, transportation, and installation. This poster presents analytical models for optimizing doubly-fed induction generators (DFIGs), with the objective of reducing the costs and mass of wind turbine drivetrains. The structural design for the induction machine includes models for the casing, stator, rotor, and high-speed shaft developed within the DFIG module in the National Renewable Energy Laboratory's wind turbine sizing tool, GeneratorSE. The mechanical integrity of the machine is verified by examining stresses, structural deflections, and modal properties. The optimization results aremore » then validated using finite element analysis (FEA). The results suggest that our analytical model correlates with the FEA in some areas, such as radial deflection, differing by less than 20 percent. But the analytical model requires further development for axial deflections, torsional deflections, and stress calculations.« less

Design and Analysis of Linear Fault-Tolerant Permanent-Magnet Vernier Machines

PubMed Central

Xu, Liang; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis. PMID:24982959

Design and analysis of linear fault-tolerant permanent-magnet vernier machines.

PubMed

Xu, Liang; Ji, Jinghua; Liu, Guohai; Du, Yi; Liu, Hu

2014-01-01

This paper proposes a new linear fault-tolerant permanent-magnet (PM) vernier (LFTPMV) machine, which can offer high thrust by using the magnetic gear effect. Both PMs and windings of the proposed machine are on short mover, while the long stator is only manufactured from iron. Hence, the proposed machine is very suitable for long stroke system applications. The key of this machine is that the magnetizer splits the two movers with modular and complementary structures. Hence, the proposed machine offers improved symmetrical and sinusoidal back electromotive force waveform and reduced detent force. Furthermore, owing to the complementary structure, the proposed machine possesses favorable fault-tolerant capability, namely, independent phases. In particular, differing from the existing fault-tolerant machines, the proposed machine offers fault tolerance without sacrificing thrust density. This is because neither fault-tolerant teeth nor the flux-barriers are adopted. The electromagnetic characteristics of the proposed machine are analyzed using the time-stepping finite-element method, which verifies the effectiveness of the theoretical analysis.

Investigation of Combined Motor/Magnetic Bearings for Flywheel Energy Storage Systems

NASA Technical Reports Server (NTRS)

Hofmann, Heath

2003-01-01

Dr. Hofmann's work in the summer of 2003 consisted of two separate projects. In the first part of the summer, Dr. Hofmann prepared and collected information regarding rotor losses in synchronous machines; in particular, machines with low rotor losses operating in vacuum and supported by magnetic bearings, such as the motor/generator for flywheel energy storage systems. This work culminated in a presentation at NASA Glenn Research Center on this topic. In the second part, Dr. Hofmann investigated an approach to flywheel energy storage where the phases of the flywheel motor/generator are connected in parallel with the phases of an induction machine driving a mechanical actuator. With this approach, additional power electronics for driving the flywheel unit are not required. Simulations of the connection of a flywheel energy storage system to a model of an electromechanical actuator testbed at NASA Glenn were performed that validated the proposed approach. A proof-of-concept experiment using the D1 flywheel unit at NASA Glenn and a Sundstrand induction machine connected to a dynamometer was successfully conducted.

Introduction

NASA Astrophysics Data System (ADS)

Takayama, Ken; Briggs*, Richard J.

The motivation for the initial development of linear induction accelerators starting in the early 1960s came mainly from applications requiring intense electron pulses with beam currents and a charge per pulse above the range accessible to RF accelerators, and with particle energies beyond the capabilities of single stage pulsed-power diodes. The linear induction accelerators developed to meet these needs utilize a series of induction cells containing magnetic cores (torroidal geometry) driven directly by pulse modulators (pulsed power sources). This multistage "one-to-one transformer" configuration with non-resonant, low impedance induction cells accelerates kilo-Ampere-scale electron beam current pulses in induction linacs.

Construction and Initial Tests of MAIZE: 1 MA LTD-Driven Z-Pinch *

NASA Astrophysics Data System (ADS)

Gilgenbach, R. M.; Gomez, M. R.; Zier, J. C.; Tang, W.; French, D. M.; Lau, Y. Y.; Mazarakis, M. G.; Cuneo, M. E.; Johnston, M. D.; Oliver, B. V.; Mehlhorn, T. A.; Kim, A. A.; Sinebryukhov, V. A.

2008-11-01

We report construction and initial testing of a 1-MA Linear Transformer Driver (LTD), The Michigan Accelerator for Inductive Z-pinch Experiments, (MAIZE). This machine, the first of its type to reach the USA, is based on the joint HCEI, Sandia Laboratories, and UM development effort. The compact LTD uses 80 capacitors and 40 spark gap switches, in 40 ``bricks'', to deliver 1 MA, 100 kV pulses with 70 ns risetime into a matched resistive load. Test results will be presented for a single brick and the full LTD. Design and construction will be presented of a low-inductance MITL. Experimental research programs under design and construction at UM include: a) Studies of Magneto-Raleigh-Taylor Instability of planar foils, and b) Vacuum convolute studies including cathode and anode plasma. Theory and simulation results will be presented for these planned experiments. Initial experimental designs and moderate-current feasibility experiments will be discussed. *Research supported by U. S. DoE through Sandia National Laboratories award document numbers 240985, 768225, 790791 and 805234 to the UM. MRG supported by NNSA Fellowship and JCZ supported by NPSC Fellowship / Sandia National Labs.

Public Data Set: Non-inductively Driven Tokamak Plasmas at Near-Unity βt in the Pegasus Toroidal Experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reusch, Joshua A.; Bodner, Grant M.; Bongard, Michael W.

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in J.A. Reusch et al., 'Non-inductively Driven Tokamak Plasmas at Near-Unity βt in the Pegasus Toroidal Experiment,' Phys. Plasmas 25, 056101 (2018).

Critical system issues and modeling requirements: The problem of beam energy sweep in an electron linear induction accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, W.C.; Barrett, D.M.; Sampayan, S.E.

1990-08-06

In this paper we discuss system issues and modeling requirements within the context of energy sweep in an electron linear induction accelerator. When needed, particular parameter values are taken from the ETA-II linear induction accelerator at Lawrence Livermore National Laboratory. For this paper, the most important parameter is energy sweep during a pulse. It is important to have low energy sweep to satisfy the FEL resonance condition and to limit the beam corkscrew motion. It is desired to achieve {Delta}E/E = {plus minus}1% for a 50-ns flattop whereas the present level of performance is {Delta}E/E = {plus minus}1% in 10more » ns. To improve this situation we will identify a number of areas in which modeling could help increase understanding and improve our ability to design linear induction accelerators.« less

Voltage regulation in linear induction accelerators

DOEpatents

Parsons, W.M.

1992-12-29

Improvement in voltage regulation in a linear induction accelerator wherein a varistor, such as a metal oxide varistor, is placed in parallel with the beam accelerating cavity and the magnetic core is disclosed. The non-linear properties of the varistor result in a more stable voltage across the beam accelerating cavity than with a conventional compensating resistance. 4 figs.

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

Integrated Inverter For Driving Multiple Electric Machines

DOEpatents

Su, Gui-Jia [Knoxville, TN; Hsu, John S [Oak Ridge, TN

2006-04-04

An electric machine drive (50) has a plurality of inverters (50a, 50b) for controlling respective electric machines (57, 62), which may include a three-phase main traction machine (57) and two-phase accessory machines (62) in a hybrid or electric vehicle. The drive (50) has a common control section (53, 54) for controlling the plurality of inverters (50a, 50b) with only one microelectronic processor (54) for controlling the plurality of inverters (50a, 50b), only one gate driver circuit (53) for controlling conduction of semiconductor switches (S1-S10) in the plurality of inverters (50a, 50b), and also includes a common dc bus (70), a common dc bus filtering capacitor (C1) and a common dc bus voltage sensor (67). The electric machines (57, 62) may be synchronous machines, induction machines, or PM machines and may be operated in a motoring mode or a generating mode.

Power-Factor and Torque Calculation under Consideration of Cross Saturation of the Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Seong T; Burress, Timothy A; Tolbert, Leon M

2009-01-01

This paper introduces a new method for calculating the power factor and output torque by considering the cross saturation between direct-axis (d-axis) and quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux atmore » high speed, which was developed for the traction motor of a hybrid electric vehicle. The conventional two-axis IPMSM model was modified to include the cross-saturation effect by adding the cross-coupled inductance terms Ldq and Lqd. By the advantage of the excited structure of the experimental IPMSM, the analyzing works were performed under two conditions, the highest and lowest excited conditions. Therefore, it is possible to investigate the cross-saturation effect when a machine has higher magnetic flux from its rotor. The following is a summary of conclusions that may be drawn from this work: (1) Considering cross saturation of an IPMSM offers more accurate expected values of motor parameters in output torque calculation, especially when negative d-axis current is high; (2) A less saturated synchronous machine could be more affected by the cross-coupled saturation effect; (3) Both cross-coupled inductances, L{sub qd} and L{sub dq}, are mainly governed by d-axis current rather than q-axis current; (4) The modified torque equation, can be used for the dynamic model of an IPMSM for developing a better control model or control strategy; and (5) It is possible that the brushless field excitation structure has a common magnetic flux path on both d- and q-axis, and as a result, the reluctance torque of the machine could be reduced.« less

Study of linear induction motor characteristics : the Mosebach model

DOT National Transportation Integrated Search

1976-05-31

This report covers the Mosebach theory of the double-sided linear induction motor, starting with the ideallized model and accompanying assumptions, and ending with relations for thrust, airgap power, and motor efficiency. Solutions of the magnetic in...

Study of linear induction motor characteristics : the Oberretl model

DOT National Transportation Integrated Search

1975-05-30

The Oberretl theory of the double-sided linear induction motor (LIM) is examined, starting with the idealized model and accompanying assumptions, and ending with relations for predicted thrust, airgap power, and motor efficiency. The effect of varyin...

Block-Module Electric Machines of Alternating Current

NASA Astrophysics Data System (ADS)

Zabora, I.

2018-03-01

The paper deals with electric machines having active zone based on uniform elements. It presents data on disk-type asynchronous electric motors with short-circuited rotors, where active elements are made by integrated technique that forms modular elements. Photolithography, spraying, stamping of windings, pressing of core and combined methods are utilized as the basic technological approaches of production. The constructions and features of operation for new electric machine - compatible electric machines-transformers are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees).

Efficiency of autonomous soft nanomachines at maximum power.

PubMed

Seifert, Udo

2011-01-14

We consider nanosized artificial or biological machines working in steady state enforced by imposing nonequilibrium concentrations of solutes or by applying external forces, torques, or electric fields. For unicyclic and strongly coupled multicyclic machines, efficiency at maximum power is not bounded by the linear response value 1/2. For strong driving, it can even approach the thermodynamic limit 1. Quite generally, such machines fall into three different classes characterized, respectively, as "strong and efficient," "strong and inefficient," and "balanced." For weakly coupled multicyclic machines, efficiency at maximum power has lost any universality even in the linear response regime.

Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD

PubMed Central

Galatzer-Levy, I R; Ma, S; Statnikov, A; Yehuda, R; Shalev, A Y

2017-01-01

To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate. To examine the potential yield of novel analytic tools, we reanalyzed data from a large longitudinal study of individuals identified following trauma in the general emergency room (ER) that failed to find a linear association between cortisol response to traumatic events and subsequent PTSD. First, latent growth mixture modeling empirically identified trajectories of post-traumatic symptoms, which then were used as the study outcome. Next, support vector machines with feature selection identified sets of features with stable predictive accuracy and built robust classifiers of trajectory membership (area under the receiver operator characteristic curve (AUC)=0.82 (95% confidence interval (CI)=0.80–0.85)) that combined clinical, neuroendocrine, psychophysiological and demographic information. Finally, graph induction algorithms revealed a unique path from childhood trauma via lower cortisol during ER admission, to non-remitting PTSD. Traditional general linear modeling methods then confirmed the newly revealed association, thereby delineating a specific target population for early endocrine interventions. Advanced computational approaches offer innovative ways for uncovering clinically significant, non-shared biological signals in heterogeneous samples. PMID:28323285

Utilization of machine learning for prediction of post-traumatic stress: a re-examination of cortisol in the prediction and pathways to non-remitting PTSD.

PubMed

Galatzer-Levy, I R; Ma, S; Statnikov, A; Yehuda, R; Shalev, A Y

2017-03-21

To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate. To examine the potential yield of novel analytic tools, we reanalyzed data from a large longitudinal study of individuals identified following trauma in the general emergency room (ER) that failed to find a linear association between cortisol response to traumatic events and subsequent PTSD. First, latent growth mixture modeling empirically identified trajectories of post-traumatic symptoms, which then were used as the study outcome. Next, support vector machines with feature selection identified sets of features with stable predictive accuracy and built robust classifiers of trajectory membership (area under the receiver operator characteristic curve (AUC)=0.82 (95% confidence interval (CI)=0.80-0.85)) that combined clinical, neuroendocrine, psychophysiological and demographic information. Finally, graph induction algorithms revealed a unique path from childhood trauma via lower cortisol during ER admission, to non-remitting PTSD. Traditional general linear modeling methods then confirmed the newly revealed association, thereby delineating a specific target population for early endocrine interventions. Advanced computational approaches offer innovative ways for uncovering clinically significant, non-shared biological signals in heterogeneous samples.

Method for measuring the contour of a machined part

DOEpatents

Bieg, L.F.

1995-05-30

A method is disclosed for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining. 5 figs.

Method for measuring the contour of a machined part

DOEpatents

Bieg, Lothar F.

1995-05-30

A method for measuring the contour of a machined part with a contour gage apparatus, having a probe assembly including a probe tip for providing a measure of linear displacement of the tip on the surface of the part. The contour gage apparatus may be moved into and out of position for measuring the part while the part is still carried on the machining apparatus. Relative positions between the part and the probe tip may be changed, and a scanning operation is performed on the machined part by sweeping the part with the probe tip, whereby data points representing linear positions of the probe tip at prescribed rotation intervals in the position changes between the part and the probe tip are recorded. The method further allows real-time adjustment of the apparatus machining the part, including real-time adjustment of the machining apparatus in response to wear of the tool that occurs during machining.

A Deep Learning Approach for Fault Diagnosis of Induction Motors in Manufacturing

NASA Astrophysics Data System (ADS)

Shao, Si-Yu; Sun, Wen-Jun; Yan, Ru-Qiang; Wang, Peng; Gao, Robert X.

2017-11-01

Extracting features from original signals is a key procedure for traditional fault diagnosis of induction motors, as it directly influences the performance of fault recognition. However, high quality features need expert knowledge and human intervention. In this paper, a deep learning approach based on deep belief networks (DBN) is developed to learn features from frequency distribution of vibration signals with the purpose of characterizing working status of induction motors. It combines feature extraction procedure with classification task together to achieve automated and intelligent fault diagnosis. The DBN model is built by stacking multiple-units of restricted Boltzmann machine (RBM), and is trained using layer-by-layer pre-training algorithm. Compared with traditional diagnostic approaches where feature extraction is needed, the presented approach has the ability of learning hierarchical representations, which are suitable for fault classification, directly from frequency distribution of the measurement data. The structure of the DBN model is investigated as the scale and depth of the DBN architecture directly affect its classification performance. Experimental study conducted on a machine fault simulator verifies the effectiveness of the deep learning approach for fault diagnosis of induction motors. This research proposes an intelligent diagnosis method for induction motor which utilizes deep learning model to automatically learn features from sensor data and realize working status recognition.

Using a PC and External Media to Quantitatively Investigate Electromagnetic Induction

ERIC Educational Resources Information Center

Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.

2011-01-01

In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to…

Applications of Electron Linear Induction Accelerators

NASA Astrophysics Data System (ADS)

Westenskow*, Glen; Chen, Yu-Jiuan

Linear Induction Accelerators (LIAs) can readily produce intense electron beams. For example, the ATA accelerator produced a 500 GW beam and the LIU-30 a 4 TW beam (see Chap. 2). Since the induction accelerator concept was proposed in the late 1950s [1, 2], there have been many proposed schemes to convert the beam power to other forms. Categories of applications that have been demonstrated for electron LIAs include:

Linear induction accelerator

DOEpatents

Buttram, M.T.; Ginn, J.W.

1988-06-21

A linear induction accelerator includes a plurality of adder cavities arranged in a series and provided in a structure which is evacuated so that a vacuum inductance is provided between each adder cavity and the structure. An energy storage system for the adder cavities includes a pulsed current source and a respective plurality of bipolar converting networks connected thereto. The bipolar high-voltage, high-repetition-rate square pulse train sets and resets the cavities. 4 figs.

Offline detection of broken rotor bars in AC induction motors

NASA Astrophysics Data System (ADS)

Powers, Craig Stephen

ABSTRACT. OFFLINE DETECTION OF BROKEN ROTOR BARS IN AC INDUCTION MOTORS. The detection of the broken rotor bar defect in medium- and large-sized AC induction machines is currently one of the most difficult tasks for the motor condition and monitoring industry. If a broken rotor bar defect goes undetected, it can cause a catastrophic failure of an expensive machine. If a broken rotor bar defect is falsely determined, it wastes time and money to physically tear down and inspect the machine only to find an incorrect diagnosis. Previous work in 2009 at Baker/SKF-USA in collaboration with the Korea University has developed a prototype instrument that has been highly successful in correctly detecting the broken rotor bar defect in ACIMs where other methods have failed. Dr. Sang Bin and his students at the Korea University have been using this prototype instrument to help the industry save money in the successful detection of the BRB defect. A review of the current state of motor conditioning and monitoring technology for detecting the broken rotor bar defect in ACIMs shows improved detection of this fault is still relevant. An analysis of previous work in the creation of this prototype instrument leads into the refactoring of the software and hardware into something more deployable, cost effective and commercially viable.

Linear phase compressive filter

DOEpatents

McEwan, Thomas E.

1995-01-01

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line.

Evaluation of linear induction motor characteristics : the Yamamura model

DOT National Transportation Integrated Search

1975-04-30

The Yamamura theory of the double-sided linear induction motor (LIM) excited by a constant current source is discussed in some detail. The report begins with a derivation of thrust and airgap power using the method of vector potentials and theorem of...

Effect of Frequency and Spatial-Harmonics on Rotary and Linear Induction Motor Characteristics

DOT National Transportation Integrated Search

1972-03-01

A computer analysis is made of the effect of current and MMF airgap harmonics on the output characteristics of rotary and linear induction motors. The current harmonics accompanying thyristor-control operation are evaluated by Fourier analyzing the p...

A tubular hybrid Halbach/axially-magnetized permanent-magnet linear machine

NASA Astrophysics Data System (ADS)

Sui, Yi; Liu, Yong; Cheng, Luming; Liu, Jiaqi; Zheng, Ping

2017-05-01

A single-phase tubular permanent-magnet linear machine (PMLM) with hybrid Halbach/axially-magnetized PM arrays is proposed for free-piston Stirling power generation system. Machine topology and operating principle are elaborately illustrated. With the sinusoidal speed characteristic of the free-piston Stirling engine considered, the proposed machine is designed and calculated by finite-element analysis (FEA). The main structural parameters, such as outer radius of the mover, radial length of both the axially-magnetized PMs and ferromagnetic poles, axial length of both the middle and end radially-magnetized PMs, etc., are optimized to improve both the force capability and power density. Compared with the conventional PMLMs, the proposed machine features high mass and volume power density, and has the advantages of simple control and low converter cost. The proposed machine topology is applicable to tubular PMLMs with any phases.

Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

PubMed

Oh, Jooyoung; Cho, Dongrae; Park, Jaesub; Na, Se Hee; Kim, Jongin; Heo, Jaeseok; Shin, Cheung Soo; Kim, Jae-Jin; Park, Jin Young; Lee, Boreom

2018-03-27

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning. Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients. HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information. Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.

Kinetics of the melting front movement in process of centrifugal induction surfacing of powder material with nanoscale modificaters

NASA Astrophysics Data System (ADS)

Sasnouski, I.; Kurylionak, A.

2018-03-01

For solving the problem of improving the powder coatings modified by nanostructure components obtained by induction surfacing method tribological characteristics it is necessary to study the kinetics of the powdered layer melting and define the minimum time of melting. For powdered layer predetermined temperature maintenance at sintering mode stage it is required to determine the temperature difference through blank thickness of the for one hundred-day of the define the warm-up swing on of the stocking up by solving the thermal conductivity stationary problem for quill (hollow) cylinder with internal heat source. Herewith, since in practice thickness of the cylinder wall is much less then its diameter and the temperature difference is comparatively small, the thermal conductivity dependence upon the temperature can be treated as negligible. As it was shown by our previous studies, in the induction heating process under powdered material centrifugal surfacing (i.e. before achieving the melting temperature) the temperature distribution in powdered layer thickness may be considered even. Hereinafter, considering the blank part induction heating process quasi-stationarity under Fo big values, it is possible to consider its internal surface heating as developing with constant velocity. As a result of development the melting front movement mathematical model in a powdered material with nanostructure modifiers the minimum surfacing time is defined. It allows to minimize negative impact of thermal influence on formation of applied coating structure, to raise productivity of the process, to lower power inputs and to ensure saving of nonferrous and high alloys by reducing the allowance for machining. The difference of developed mathematical model of melting front movement from previously known is that the surface temperature from which the heat transfer occures is a variable and varies with a time after the linear law.

A Flash X-Ray Facility for the Naval Postgraduate School

DTIC Science & Technology

1985-06-01

ionizing radiation, *• NPS has had active programs with a Van de Graaff generator, a reactor, radioactive sources, X-ray machines and a linear electron ...interaction of radiation with matter and with coherent radiation. Currently the most active program is at the linear electron accelerator which over...twenty years has produced some 75 theses. The flash X-ray machine was obtained to expan-i and complement the capabilities of the linear electron

Linear induction accelerator and pulse forming networks therefor

DOEpatents

Buttram, Malcolm T.; Ginn, Jerry W.

1989-01-01

A linear induction accelerator includes a plurality of adder cavities arranged in a series and provided in a structure which is evacuated so that a vacuum inductance is provided between each adder cavity and the structure. An energy storage system for the adder cavities includes a pulsed current source and a respective plurality of bipolar converting networks connected thereto. The bipolar high-voltage, high-repetition-rate square pulse train sets and resets the cavities.

Molten metal feed system controlled with a traveling magnetic field

DOEpatents

Praeg, Walter F.

1991-01-01

A continuous metal casting system in which the feed of molten metal is controlled by means of a linear induction motor capable of producing a magnetic traveling wave in a duct that connects a reservoir of molten metal to a caster. The linear induction motor produces a traveling magnetic wave in the duct in opposition to the pressure exerted by the head of molten metal in the reservoir so that p.sub.c =p.sub.g -p.sub.m where p.sub.c is the desired pressure in the caster, p.sub.g is the gravitational pressure in the duct exerted by the force of the head of molten metal in the reservoir, and p.sub.m is the electromagnetic pressure exerted by the force of the magnetic field traveling wave produced by the linear induction motor. The invention also includes feedback loops to the linear induction motor to control the casting pressure in response to measured characteristics of the metal being cast.

Control Demonstration of Multiple Doubly-Fed Induction Motors for Hybrid Electric Propulsion

NASA Technical Reports Server (NTRS)

Sadey, David J.; Bodson, Marc; Csank, Jeffrey T.; Hunker, Keith R.; Theman, Casey J.; Taylor, Linda M.

2017-01-01

The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application.The Convergent Aeronautics Solutions (CAS) High Voltage-Hybrid Electric Propulsion (HVHEP) task was formulated to support the move into future hybrid-electric aircraft. The goal of this project is to develop a new AC power architecture to support the needs of higher efficiency and lower emissions. This proposed architecture will adopt the use of the doubly-fed induction machine (DFIM) for propulsor drive motor application. DFIMs are attractive for several reasons, including but not limited to the ability to self-start, ability to operate sub- and super-synchronously, and requiring only fractionally rated power converters on a per-unit basis depending on the required range of operation. The focus of this paper is based specifically on the presentation and analysis of a novel strategy which allows for independent operation of each of the aforementioned doubly-fed induction motors. This strategy includes synchronization, soft-start, and closed loop speed control of each motor as a means of controlling output thrust; be it concurrently or differentially. The demonstration of this strategy has recently been proven out on a low power test bed using fractional horsepower machines. Simulation and hardware test results are presented in the paper.

A machine learning approach to computer-aided molecular design

NASA Astrophysics Data System (ADS)

Bolis, Giorgio; Di Pace, Luigi; Fabrocini, Filippo

1991-12-01

Preliminary results of a machine learning application concerning computer-aided molecular design applied to drug discovery are presented. The artificial intelligence techniques of machine learning use a sample of active and inactive compounds, which is viewed as a set of positive and negative examples, to allow the induction of a molecular model characterizing the interaction between the compounds and a target molecule. The algorithm is based on a twofold phase. In the first one — the specialization step — the program identifies a number of active/inactive pairs of compounds which appear to be the most useful in order to make the learning process as effective as possible and generates a dictionary of molecular fragments, deemed to be responsible for the activity of the compounds. In the second phase — the generalization step — the fragments thus generated are combined and generalized in order to select the most plausible hypothesis with respect to the sample of compounds. A knowledge base concerning physical and chemical properties is utilized during the inductive process.

Induced sadness increases persistence in a simulated slot machine task among recreational gamblers.

PubMed

Devos, Gaëtan; Clark, Luke; Maurage, Pierre; Billieux, Joël

2018-05-01

Gambling may constitute a strategy for coping with depressive mood, but a direct influence of depressive mood on gambling behaviors has never been tested via realistic experimental designs in gamblers. The current study tested whether experimentally induced sadness increases persistence on a simulated slot machine task using real monetary reinforcement in recreational gamblers. Sixty participants were randomly assigned to an experimental (sadness induction) or control (no emotional induction) condition, and then performed a slot machine task consisting of a mandatory phase followed by a persistence phase. Potential confounding variables (problem gambling symptoms, impulsivity traits, gambling cognitions) were measured to ensure that the experimental and control groups were comparable. The study showed that participants in the sadness condition displayed greater gambling persistence than control participants (p = .011). These data support the causal role of negative affect in decisions to gamble and persistence, which bears important theoretical and clinical implications. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Investigation of self-excited induction generators for wind turbine applications

DOE Office of Scientific and Technical Information (OSTI.GOV)

Muljadi, E.; Butterfield, C.P.; Sallan, J.

2000-02-28

The use of squirrel-cage induction machines in wind generation is widely accepted as a generator of choice. The squirrel-cage induction machine is simple, reliable, cheap, lightweight, and requires very little maintenance. Generally, the induction generator is connected to the utility at constant frequency. With a constant frequency operation, the induction generator operates at practically constant speed (small range of slip). The wind turbine operates in optimum efficiency only within a small range of wind speed variation. The variable-speed operation allows an increase in energy captured and reduces both the torque peaks in the drive train and the power fluctuations sentmore » to the utility. In variable-speed operation, an induction generator needs an interface to convert the variable frequency output of the generator to the fixed frequency at the utility. This interface can be simplified by using a self-excited generator because a simple diode bridge is required to perform the ac/dc conversion. The subsequent dc/ac conversion can be performed using different techniques. The use of a thyristor bridge is readily available for large power conversion and has a lower cost and higher reliability. The firing angle of the inverter bridge can be controlled to track the optimum power curve of the wind turbine. With only diodes and thyristors used in power conversion, the system can be scaled up to a very high voltage and high power applications. This paper analyzes the operation of such a system applied to a 1/3-hp self-excited induction generator. It includes the simulations and tests performed for the different excitation configurations.« less

A Novelty Design Of Minimization Of Electrical Losses In A Vector Controlled Induction Machine Drive

NASA Astrophysics Data System (ADS)

Aryza, Solly; Irwanto, M.; Lubis, Zulkarnain; Putera Utama Siahaan, Andysah; Rahim, Robbi; Furqan, Mhd.

2018-01-01

The induction motor has in the industry . More attention has been a focus to develop and design of induction motor drive. With the method of vector control novelty prove the efficiency of induction motor over their entire speed range. In this paper desirable to design a loss minimization controller which can improve the efficiency. Also, this research described Modeling of an induction motor with core loss included. Realization of methods vector control for an induction motor drive with loss element included. The case of the loss minimization condition. The procedure was successful to calculate the gains of a PI controller. Though the problem of obtaining a robust and sensorless induction motor drive is by no means completely solved, the results obtained as part of this work point in a promising direction.

Classification of sodium MRI data of cartilage using machine learning.

PubMed

Madelin, Guillaume; Poidevin, Frederick; Makrymallis, Antonios; Regatte, Ravinder R

2015-11-01

To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: Support vector machine, k-nearest neighbors, naïve Bayes, discriminant analysis, linear regression, logistic regression, neural networks, decision tree, and tree bagging were tested. Sodium magnetic resonance imaging with and without fluid suppression by inversion recovery was acquired on the knee cartilage of 19 controls and 28 osteoarthritis patients. Sodium concentrations were measured in regions of interests in the knee for both acquisitions. Mean (MEAN) and standard deviation (STD) of these concentrations were measured in each regions of interest, and the minimum, maximum, and mean of these two measurements were calculated over all regions of interests for each subject. The resulting 12 variables per subject were used as predictors for classification. Either Min [STD] alone, or in combination with Mean [MEAN] or Min [MEAN], all from fluid suppressed data, were the best predictors with an accuracy >74%, mainly with linear logistic regression and linear support vector machine. Other good classifiers include discriminant analysis, linear regression, and naïve Bayes. Machine learning is a promising technique for classifying osteoarthritis patients and controls from sodium magnetic resonance imaging data. © 2014 Wiley Periodicals, Inc.

Direct reading inductance meter

NASA Technical Reports Server (NTRS)

Kolby, R. B. (Inventor)

1977-01-01

A direct reading inductance meter comprised of a crystal oscillator and an LC tuned oscillator is presented. The oscillators function respectively to generate a reference frequency, f(r), and to generate an initial frequency, f(0), which when mixed produce a difference equal to zero. Upon connecting an inductor of small unknown value in the LC circuit to change its resonant frequency to f(x), a difference frequency (f(r)-f(x)) is produced that is very nearly a linear function of the inductance of the inductor. The difference frequency is measured and displayed on a linear scale in units of inductance.

Real time automatic detection of bearing fault in induction machine using kurtogram analysis.

PubMed

Tafinine, Farid; Mokrani, Karim

2012-11-01

A proposed signal processing technique for incipient real time bearing fault detection based on kurtogram analysis is presented in this paper. The kurtogram is a fourth-order spectral analysis tool introduced for detecting and characterizing non-stationarities in a signal. This technique starts from investigating the resonance signatures over selected frequency bands to extract the representative features. The traditional spectral analysis is not appropriate for non-stationary vibration signal and for real time diagnosis. The performance of the proposed technique is examined by a series of experimental tests corresponding to different bearing conditions. Test results show that this signal processing technique is an effective bearing fault automatic detection method and gives a good basis for an integrated induction machine condition monitor.

Free-piston engine linear generator for hybrid vehicles modeling study

NASA Astrophysics Data System (ADS)

Callahan, T. J.; Ingram, S. K.

1995-05-01

Development of a free piston engine linear generator was investigated for use as an auxiliary power unit for a hybrid electric vehicle. The main focus of the program was to develop an efficient linear generator concept to convert the piston motion directly into electrical power. Computer modeling techniques were used to evaluate five different designs for linear generators. These designs included permanent magnet generators, reluctance generators, linear DC generators, and two and three-coil induction generators. The efficiency of the linear generator was highly dependent on the design concept. The two-coil induction generator was determined to be the best design, with an efficiency of approximately 90 percent.

Optimal model of PDIG based microgrid and design of complementary stabilizer using ICA.

PubMed

Amini, R Mohammad; Safari, A; Ravadanegh, S Najafi

2016-09-01

The generalized Heffron-Phillips model (GHPM) for a microgrid containing a photovoltaic (PV)-diesel machine (DM)-induction motor (IM)-governor (GV) (PDIG) has been developed at the low voltage level. A GHPM is calculated by linearization method about a loading condition. An effective Maximum Power Point Tracking (MPPT) approach for PV network has been done using sliding mode control (SMC) to maximize output power. Additionally, to improve stability of microgrid for more penetration of renewable energy resources with nonlinear load, a complementary stabilizer has been presented. Imperialist competitive algorithm (ICA) is utilized to design of gains for the complementary stabilizer with the multiobjective function. The stability analysis of the PDIG system has been completed with eigenvalues analysis and nonlinear simulations. Robustness and validity of the proposed controllers on damping of electromechanical modes examine through time domain simulation under input mechanical torque disturbances. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Overview of the Helicity Injected Torus (HIT) Program

NASA Astrophysics Data System (ADS)

Redd, A. J.; Jarboe, T. R.; Hamp, W. T.; Nelson, B. A.; O'Neill, R. G.; Sieck, P. E.; Smith, R. J.; Sutphin, G. L.; Wrobel, J. S.

2007-06-01

The Helicity Injected Torus with Steady Inductive Helicity Injection (HIT-SI) consists of a "bowtie"-shaped axisymmetric confinement region, with two half-torus helicity injectors mounted on each side of the axisymmetric flux conserver [Sieck et al, IEEE Trans. Plasma Sci., v.33, p.723 (2005); Jarboe, Fusion Technology, v.36, p.85 (1999)]. Current and flux are driven sinusoidally with time in each injector, with the goal of generating and sustaining an axisymmetric spheromak in the main confinement region. Improvements in machine conditioning have enabled systematic study of HIT-SI discharges with significant toroidal current ITOR, including cases in which this current ITOR switches sign one or more times during the discharge. Statistical studies of all HIT-SI discharges to date demonstrate a minimum injected power to form significant ITOR, and that the maximum ITOR scales approximately linearly with the total injected power.

Nanoscale swimmers: hydrodynamic interactions and propulsion of molecular machines

NASA Astrophysics Data System (ADS)

Sakaue, T.; Kapral, R.; Mikhailov, A. S.

2010-06-01

Molecular machines execute nearly regular cyclic conformational changes as a result of ligand binding and product release. This cyclic conformational dynamics is generally non-reciprocal so that under time reversal a different sequence of machine conformations is visited. Since such changes occur in a solvent, coupling to solvent hydrodynamic modes will generally result in self-propulsion of the molecular machine. These effects are investigated for a class of coarse grained models of protein machines consisting of a set of beads interacting through pair-wise additive potentials. Hydrodynamic effects are incorporated through a configuration-dependent mobility tensor, and expressions for the propulsion linear and angular velocities, as well as the stall force, are obtained. In the limit where conformational changes are small so that linear response theory is applicable, it is shown that propulsion is exponentially small; thus, propulsion is nonlinear phenomenon. The results are illustrated by computations on a simple model molecular machine.

Linear phase compressive filter

DOEpatents

McEwan, T.E.

1995-06-06

A phase linear filter for soliton suppression is in the form of a laddered series of stages of non-commensurate low pass filters with each low pass filter having a series coupled inductance (L) and a reverse biased, voltage dependent varactor diode, to ground which acts as a variable capacitance (C). L and C values are set to levels which correspond to a linear or conventional phase linear filter. Inductance is mapped directly from that of an equivalent nonlinear transmission line and capacitance is mapped from the linear case using a large signal equivalent of a nonlinear transmission line. 2 figs.

Start-up and control method and apparatus for resonant free piston Stirling engine

DOEpatents

Walsh, Michael M.

1984-01-01

A resonant free-piston Stirling engine having a new and improved start-up and control method and system. A displacer linear electrodynamic machine is provided having an armature secured to and movable with the displacer and having a stator supported by the Stirling engine housing in juxtaposition to the armature. A control excitation circuit is provided for electrically exciting the displacer linear electrodynamic machine with electrical excitation signals having substantially the same frequency as the desired frequency of operation of the Stirling engine. The excitation control circuit is designed so that it selectively and controllably causes the displacer electrodynamic machine to function either as a generator load to extract power from the displacer or the control circuit selectively can be operated to cause the displacer electrodynamic machine to operate as an electric drive motor to apply additional input power to the displacer in addition to the thermodynamic power feedback to the displacer whereby the displacer linear electrodynamic machine also is used in the electric drive motor mode as a means for initially starting the resonant free-piston Stirling engine.

Machine learning of fault characteristics from rocket engine simulation data

NASA Technical Reports Server (NTRS)

Ke, Min; Ali, Moonis

1990-01-01

Transformation of data into knowledge through conceptual induction has been the focus of our research described in this paper. We have developed a Machine Learning System (MLS) to analyze the rocket engine simulation data. MLS can provide to its users fault analysis, characteristics, and conceptual descriptions of faults, and the relationships of attributes and sensors. All the results are critically important in identifying faults.

Fuzzy logic controller optimization

DOEpatents

Sepe, Jr., Raymond B; Miller, John Michael

2004-03-23

A method is provided for optimizing a rotating induction machine system fuzzy logic controller. The fuzzy logic controller has at least one input and at least one output. Each input accepts a machine system operating parameter. Each output produces at least one machine system control parameter. The fuzzy logic controller generates each output based on at least one input and on fuzzy logic decision parameters. Optimization begins by obtaining a set of data relating each control parameter to at least one operating parameter for each machine operating region. A model is constructed for each machine operating region based on the machine operating region data obtained. The fuzzy logic controller is simulated with at least one created model in a feedback loop from a fuzzy logic output to a fuzzy logic input. Fuzzy logic decision parameters are optimized based on the simulation.

New Technique of High-Performance Torque Control Developed for Induction Machines

NASA Technical Reports Server (NTRS)

Kenny, Barbara H.

2003-01-01

Two forms of high-performance torque control for motor drives have been described in the literature: field orientation control and direct torque control. Field orientation control has been the method of choice for previous NASA electromechanical actuator research efforts with induction motors. Direct torque control has the potential to offer some advantages over field orientation, including ease of implementation and faster response. However, the most common form of direct torque control is not suitable for the highspeed, low-stator-flux linkage induction machines designed for electromechanical actuators with the presently available sample rates of digital control systems (higher sample rates are required). In addition, this form of direct torque control is not suitable for the addition of a high-frequency carrier signal necessary for the "self-sensing" (sensorless) position estimation technique. This technique enables low- and zero-speed position sensorless operation of the machine. Sensorless operation is desirable to reduce the number of necessary feedback signals and transducers, thus improving the reliability and reducing the mass and volume of the system. This research was directed at developing an alternative form of direct torque control known as a "deadbeat," or inverse model, solution. This form uses pulse-width modulation of the voltage applied to the machine, thus reducing the necessary sample and switching frequency for the high-speed NASA motor. In addition, the structure of the deadbeat form allows the addition of the high-frequency carrier signal so that low- and zero-speed sensorless operation is possible. The new deadbeat solution is based on using the stator and rotor flux as state variables. This choice of state variables leads to a simple graphical representation of the solution as the intersection of a constant torque line with a constant stator flux circle. Previous solutions have been expressed only in complex mathematical terms without a method to clearly visualize the solution. The graphical technique allows a more insightful understanding of the operation of the machine under various conditions.

Electric converters of electromagnetic strike machine with battery power

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Kargin, V. A.; Moiseev, A. P.; Chetverikov, E. A.

2018-03-01

At present, the application of pulse linear electromagnetic engines to drive strike machines for immersion of rod elements into the soil, strike drilling of shallow wells, dynamic probing of soils is recognized as quite effective. The pulse linear electromagnetic engine performs discrete consumption and conversion of electrical energy into mechanical work. Pulse dosing of a stream transmitted by the battery source to the pulse linear electromagnetic engine of the energy is provided by the electrical converter. The electric converters with the control of an electromagnetic strike machine as functions of time and armature movement, which form the unipolar supply pulses of voltage and current necessary for the normal operation of a pulse linear electromagnetic engine, are proposed. Electric converters are stable in operation, implement the necessary range of output parameters control determined by the technological process conditions, have noise immunity and automatic disconnection of power supply in emergency modes.

XRF inductive bead fusion and PLC based control system

NASA Astrophysics Data System (ADS)

Zhu, Jin-hong; Wang, Ying-jie; Shi, Hong-xin; Chen, Qing-ling; Chen, Yu-xi

2009-03-01

In order to ensure high-quality X-ray fluorescence spectrometry (XRF) analysis, an inductive bead fusion machine was developed. The prototype consists of super-audio IGBT induction heating power supply, rotation and swing mechanisms, and programmable logic controller (PLC). The system can realize sequence control, mechanical movement control, output current and temperature control. Experimental results show that the power supply can operate at an ideal quasi-resonant state, in which the expected power output and the required temperature can be achieved for rapid heating and the uniform formation of glass beads respectively.

Magnetization of ternary alloys based on Fe0.65Ni0.35 invar with 3d transition metal additions: An ab initio study

NASA Astrophysics Data System (ADS)

Onoue, Masatoshi; Trimarchi, Giancarlo; Freeman, Arthur J.; Popescu, Voicu; Matsen, Marc R.

2015-01-01

Smart susceptors are being developed for use as tooling surfaces in molding machines that use apply electro-magnetic induction heating to mold and form plastics or metal powders into structural parts, e.g., on aerospace and automotive manufacturing lines. The optimal magnetic materials for the induction heating process should have large magnetization, high magnetic permeability, but also small thermal expansion coefficient. The Fe0.65Ni0.35 invar alloy with its negligible thermal expansion coefficient is thus a natural choice for this application. Here, we use density functional theory as implemented through the Korringa-Kohn-Rostoker method within the coherent-potential approximation, to design new alloys with the large magnetization desired for smart susceptor applications. We consider the Fe0.65-xNi0.35-yMx+y alloys derived from Fe0.65Ni0.35 invar adding a third element M = Sc, Ti, V, Cr, Mn, or Co with concentration (x + y) reaching up to 5 at. %. We find that the total magnetization depends linearly on the concentration of M. Specifically, the early 3d transition metals from Sc to Cr decrease the magnetization with respect to that of the invar alloy whereas Mn and Co increase it.

Measurements of the neutron dose equivalent for various radiation qualities, treatment machines and delivery techniques in radiation therapy

NASA Astrophysics Data System (ADS)

Hälg, R. A.; Besserer, J.; Boschung, M.; Mayer, S.; Lomax, A. J.; Schneider, U.

2014-05-01

In radiation therapy, high energy photon and proton beams cause the production of secondary neutrons. This leads to an unwanted dose contribution, which can be considerable for tissues outside of the target volume regarding the long term health of cancer patients. Due to the high biological effectiveness of neutrons in regards to cancer induction, small neutron doses can be important. This study quantified the neutron doses for different radiation therapy modalities. Most of the reports in the literature used neutron dose measurements free in air or on the surface of phantoms to estimate the amount of neutron dose to the patient. In this study, dose measurements were performed in terms of neutron dose equivalent inside an anthropomorphic phantom. The neutron dose equivalent was determined using track etch detectors as a function of the distance to the isocenter, as well as for radiation sensitive organs. The dose distributions were compared with respect to treatment techniques (3D-conformal, volumetric modulated arc therapy and intensity-modulated radiation therapy for photons; spot scanning and passive scattering for protons), therapy machines (Varian, Elekta and Siemens linear accelerators) and radiation quality (photons and protons). The neutron dose equivalent varied between 0.002 and 3 mSv per treatment gray over all measurements. Only small differences were found when comparing treatment techniques, but substantial differences were observed between the linear accelerator models. The neutron dose equivalent for proton therapy was higher than for photons in general and in particular for double-scattered protons. The overall neutron dose equivalent measured in this study was an order of magnitude lower than the stray dose of a treatment using 6 MV photons, suggesting that the contribution of the secondary neutron dose equivalent to the integral dose of a radiotherapy patient is small.

Measurements of the neutron dose equivalent for various radiation qualities, treatment machines and delivery techniques in radiation therapy.

PubMed

Hälg, R A; Besserer, J; Boschung, M; Mayer, S; Lomax, A J; Schneider, U

2014-05-21

In radiation therapy, high energy photon and proton beams cause the production of secondary neutrons. This leads to an unwanted dose contribution, which can be considerable for tissues outside of the target volume regarding the long term health of cancer patients. Due to the high biological effectiveness of neutrons in regards to cancer induction, small neutron doses can be important. This study quantified the neutron doses for different radiation therapy modalities. Most of the reports in the literature used neutron dose measurements free in air or on the surface of phantoms to estimate the amount of neutron dose to the patient. In this study, dose measurements were performed in terms of neutron dose equivalent inside an anthropomorphic phantom. The neutron dose equivalent was determined using track etch detectors as a function of the distance to the isocenter, as well as for radiation sensitive organs. The dose distributions were compared with respect to treatment techniques (3D-conformal, volumetric modulated arc therapy and intensity-modulated radiation therapy for photons; spot scanning and passive scattering for protons), therapy machines (Varian, Elekta and Siemens linear accelerators) and radiation quality (photons and protons). The neutron dose equivalent varied between 0.002 and 3 mSv per treatment gray over all measurements. Only small differences were found when comparing treatment techniques, but substantial differences were observed between the linear accelerator models. The neutron dose equivalent for proton therapy was higher than for photons in general and in particular for double-scattered protons. The overall neutron dose equivalent measured in this study was an order of magnitude lower than the stray dose of a treatment using 6 MV photons, suggesting that the contribution of the secondary neutron dose equivalent to the integral dose of a radiotherapy patient is small.

Power electromagnetic strike machine for engineering-geological surveys

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Chetverikov, E. A.; Kargin, V. A.; Moiseev, A. P.; Ivanova, Z. I.

2017-10-01

When implementing the processes of dynamic sensing of soils and pulsed nonexplosive seismic exploration, the most common and effective method is the strike one, which is provided by a variety of structure and parameters of pneumatic, hydraulic, electrical machines of strike action. The creation of compact portable strike machines which do not require transportation and use of mechanized means is important. A promising direction in the development of strike machines is the use of pulsed electromagnetic actuator characterized by relatively low energy consumption, relatively high specific performance and efficiency, and providing direct conversion of electrical energy into mechanical work of strike mass with linear movement trajectory. The results of these studies allowed establishing on the basis of linear electromagnetic motors the electromagnetic pulse machines with portable performance for dynamic sensing of soils and land seismic pulse of small depths.

Comparative investigation of diagnosis media for induction machine mechanical unbalance fault.

PubMed

Salah, Mohamed; Bacha, Khmais; Chaari, Abdelkader

2013-11-01

For an induction machine, we suggest a theoretical development of the mechanical unbalance effect on the analytical expressions of radial vibration and stator current. Related spectra are described and characteristic defect frequencies are determined. Moreover, the stray flux expressions are developed for both axial and radial sensor coil positions and a substitute diagnosis technique is proposed. In addition, the load torque effect on the detection efficiency of these diagnosis media is discussed and a comparative investigation is performed. The decisive factor of comparison is the fault sensitivity. Experimental results show that spectral analysis of the axial stray flux can be an alternative solution to cover effectiveness limitation of the traditional stator current technique and to substitute the classical vibration practice. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Exploring inductive linearization for pharmacokinetic-pharmacodynamic systems of nonlinear ordinary differential equations.

PubMed

Hasegawa, Chihiro; Duffull, Stephen B

2018-02-01

Pharmacokinetic-pharmacodynamic systems are often expressed with nonlinear ordinary differential equations (ODEs). While there are numerous methods to solve such ODEs these methods generally rely on time-stepping solutions (e.g. Runge-Kutta) which need to be matched to the characteristics of the problem at hand. The primary aim of this study was to explore the performance of an inductive approximation which iteratively converts nonlinear ODEs to linear time-varying systems which can then be solved algebraically or numerically. The inductive approximation is applied to three examples, a simple nonlinear pharmacokinetic model with Michaelis-Menten elimination (E1), an integrated glucose-insulin model and an HIV viral load model with recursive feedback systems (E2 and E3, respectively). The secondary aim of this study was to explore the potential advantages of analytically solving linearized ODEs with two examples, again E3 with stiff differential equations and a turnover model of luteinizing hormone with a surge function (E4). The inductive linearization coupled with a matrix exponential solution provided accurate predictions for all examples with comparable solution time to the matched time-stepping solutions for nonlinear ODEs. The time-stepping solutions however did not perform well for E4, particularly when the surge was approximated by a square wave. In circumstances when either a linear ODE is particularly desirable or the uncertainty in matching the integrator to the ODE system is of potential risk, then the inductive approximation method coupled with an analytical integration method would be an appropriate alternative.

A review on prognostic techniques for non-stationary and non-linear rotating systems

NASA Astrophysics Data System (ADS)

Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph

2015-10-01

The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.

[Effect of compaction pressure on the properties of dental machinable zirconia ceramic].

PubMed

Huang, Hui; Wei, Bin; Zhang, Fu-qiang; Sun, Jing; Gao, Lian

2010-10-01

To investigate the effect of compaction pressure on the linear shrinkage, sintering property and machinability of the dental zirconia ceramic. The nano-size zirconia powder was compacted at different isostatic pressure and sintered at different temperature. The linear shrinkage of sintered body was measured and the relative density was tested using the Archimedes method. The cylindrical surface of pre-sintering blanks was traversed using a hard metal tool. Surface and edge quality were checked visually using light stereo microscopy. The sintering behaviour depended on the compaction pressure. Increasing compaction pressure led to higher sintering rate and lower sintering temperature. Increasing compaction pressure also led to decreasing linear shrinkage of the sintered bodies, from 24.54% of 50 MPa to 20.9% of 400 MPa. Compaction pressure showed only a weak influence on machinability of zirconia blanks, but the higher compaction pressure resulted in the poor surface quality. The better sintering property and machinability of dental zirconia ceramic is found for 200-300 MPa compaction pressure.

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics

PubMed Central

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications. PMID:27806075

Comparing Machine Learning Classifiers and Linear/Logistic Regression to Explore the Relationship between Hand Dimensions and Demographic Characteristics.

PubMed

Miguel-Hurtado, Oscar; Guest, Richard; Stevenage, Sarah V; Neil, Greg J; Black, Sue

2016-01-01

Understanding the relationship between physiological measurements from human subjects and their demographic data is important within both the biometric and forensic domains. In this paper we explore the relationship between measurements of the human hand and a range of demographic features. We assess the ability of linear regression and machine learning classifiers to predict demographics from hand features, thereby providing evidence on both the strength of relationship and the key features underpinning this relationship. Our results show that we are able to predict sex, height, weight and foot size accurately within various data-range bin sizes, with machine learning classification algorithms out-performing linear regression in most situations. In addition, we identify the features used to provide these relationships applicable across multiple applications.

Increased Resistance to Flow and Ventilator Failure Secondary to Faulty CO2 Absorbent Insert Not Detected During Automated Anesthesia Machine Check: A Case Report.

PubMed

Moreno-Duarte, Ingrid; Montenegro, Julio; Balonov, Konstantin; Schumann, Roman

2017-04-15

Most modern anesthesia workstations provide automated checkout, which indicates the readiness of the anesthesia machine. In this case report, an anesthesia machine passed the automated machine checkout. Minutes after the induction of general anesthesia, we observed a mismatch between the selected and delivered tidal volumes in the volume auto flow mode with increased inspiratory resistance during manual ventilation. Endotracheal tube kinking, circuit obstruction, leaks, and patient-related factors were ruled out. Further investigation revealed a broken internal insert within the CO2 absorbent canister that allowed absorbent granules to cause a partial obstruction to inspiratory and expiratory flow triggering contradictory alarms. We concluded that even when the automated machine checkout indicates machine readiness, unforeseen equipment failure due to unexpected events can occur and require providers to remain vigilant.

In-duct identification of a rotating sound source with high spatial resolution

NASA Astrophysics Data System (ADS)

Heo, Yong-Ho; Ih, Jeong-Guon; Bodén, Hans

2015-11-01

To understand and reduce the flow noise generation from in-duct fluid machines, it is necessary to identify the acoustic source characteristics precisely. In this work, a source identification technique, which can identify the strengths and positions of the major sound radiators in the source plane, is studied for an in-duct rotating source. A linear acoustic theory including the effects of evanescent modes and source rotation is formulated based on the modal summation method, which is the underlying theory for the inverse source reconstruction. A validation experiment is conducted on a duct system excited by a loudspeaker in static and rotating conditions, with two different speeds, in the absence of flow. Due to the source rotation, the measured pressure spectra reveal the Doppler effect, and the amount of frequency shift corresponds to the multiplication of the circumferential mode order and the rotation speed. Amplitudes of participating modes are estimated at the shifted frequencies in the stationary reference frame, and the modal amplitude set including the effect of source rotation is collected to investigate the source behavior in the rotating reference frame. By using the estimated modal amplitudes, the near-field pressure is re-calculated and compared with the measured pressure. The obtained maximum relative error is about -25 and -10 dB for rotation speeds at 300 and 600 rev/min, respectively. The spatial distribution of acoustic source parameters is restored from the estimated modal amplitude set. The result clearly shows that the position and magnitude of the main sound source can be identified with high spatial resolution in the rotating reference frame.

Finite Element Analysis in the Estimation of Air-Gap Torque and Surface Temperature of Induction Machine

NASA Astrophysics Data System (ADS)

Mr., J. Ravi Kumar; Banakara, Basavaraja, Dr.

2017-08-01

This paper presents electromagnetic and thermal behavior of Induction Motor (IM) through the modeling and analysis by applying multiphysics coupled Finite Element Analysis (FEA). Therefore prediction of the magnetic flux, electromagnetic torque, stator and rotor losses and temperature distribution inside an operating electric motor are the most important issues during its design. Prediction and estimation of these parameters allows design engineers to decide capability of the machine for the proposed load, temperature rating and its application for which it is being designed ensuring normal motor operation at rated conditions. In this work, multiphysics coupled electromagnetic - thermal modeling and analysis of induction motor at rated and high frequency has carried out applying Arkkio’s torque method. COMSOL Multiphysics software is used for modeling and finite element analysis of IM. Transient electromagnetic torque, magnetic field distribution, speed-torque characteristics of IM were plotted and studied at different frequencies. This proposed work helps in the design and prediction of accurate performance of induction motor specific to various industrial drive applications. Results obtained are also validated with experimental analysis. The main purpose of this model is to use it as an integral part of the design aiming to system optimization of Variable Speed Drive (VSD) and its components using coupled simulations.

The neural basis of attaining conscious awareness of sad mood.

PubMed

Smith, Ryan; Braden, B Blair; Chen, Kewei; Ponce, Francisco A; Lane, Richard D; Baxter, Leslie C

2015-09-01

The neural processes associated with becoming aware of sad mood are not fully understood. We examined the dynamic process of becoming aware of sad mood and recovery from sad mood. Sixteen healthy subjects underwent fMRI while participating in a sadness induction task designed to allow for variable mood induction times. Individualized regressors linearly modeled the time periods during the attainment of self-reported sad and baseline "neutral" mood states, and the validity of the linearity assumption was further tested using independent component analysis. During sadness induction the dorsomedial and ventrolateral prefrontal cortices, and anterior insula exhibited a linear increase in the blood oxygen level-dependent (BOLD) signal until subjects became aware of a sad mood and then a subsequent linear decrease as subjects transitioned from sadness back to the non-sadness baseline condition. These findings extend understanding of the neural basis of conscious emotional experience.

Semi-supervised prediction of gene regulatory networks using machine learning algorithms.

PubMed

Patel, Nihir; Wang, Jason T L

2015-10-01

Use of computational methods to predict gene regulatory networks (GRNs) from gene expression data is a challenging task. Many studies have been conducted using unsupervised methods to fulfill the task; however, such methods usually yield low prediction accuracies due to the lack of training data. In this article, we propose semi-supervised methods for GRN prediction by utilizing two machine learning algorithms, namely, support vector machines (SVM) and random forests (RF). The semi-supervised methods make use of unlabelled data for training. We investigated inductive and transductive learning approaches, both of which adopt an iterative procedure to obtain reliable negative training data from the unlabelled data. We then applied our semi-supervised methods to gene expression data of Escherichia coli and Saccharomyces cerevisiae, and evaluated the performance of our methods using the expression data. Our analysis indicated that the transductive learning approach outperformed the inductive learning approach for both organisms. However, there was no conclusive difference identified in the performance of SVM and RF. Experimental results also showed that the proposed semi-supervised methods performed better than existing supervised methods for both organisms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schlossberg, David J.; Bodner, Grant M.; Bongard, Michael W.

This public data set contains openly-documented, machine readable digital research data corresponding to figures published in D.J. Schlossberg et al., 'Non-Inductively Driven Tokamak Plasmas at Near-Unity Toroidal Beta,' Phys. Rev. Lett. 119, 035001 (2017).

Design and application of electromechanical actuators for deep space missions

NASA Technical Reports Server (NTRS)

Haskew, Tim A.; Wander, John

1993-01-01

The annual report Design and Application of Electromechanical Actuators for Deep Space Missions is presented. The reporting period is 16 Aug. 1992 to 15 Aug. 1993. However, the primary focus will be work performed since submission of our semi-annual progress report in Feb. 1993. Substantial progress was made. We currently feel confident in providing guidelines for motor and control strategy selection in electromechanical actuators to be used in thrust vector control (TVC) applications. A small portion was presented in the semi-annual report. At this point, we have implemented highly detailed simulations of various motor/drive systems. The primary motor candidates were the brushless dc machine, permanent magnet synchronous machine, and the induction machine. The primary control implementations were pulse width modulation and hysteresis current control. Each of the two control strategies were applied to each of the three motor choices. With either pulse width modulation or hysteresis current control, the induction machine was always vector controlled. A standard test position command sequence for system performance evaluation is defined. Currently, we are gathering all of the necessary data for formal presentation of the results. Briefly stated for TVC application, we feel that the brushless dc machine operating under PWM current control is the best option. Substantial details on the topic, with supporting simulation results, will be provided later, in the form of a technical paper prepared for submission and also in the next progress report with more detail than allowed for paper publication.

Comparison between Two Linear Supervised Learning Machines' Methods with Principle Component Based Methods for the Spectrofluorimetric Determination of Agomelatine and Its Degradants.

PubMed

Elkhoudary, Mahmoud M; Naguib, Ibrahim A; Abdel Salam, Randa A; Hadad, Ghada M

2017-05-01

Four accurate, sensitive and reliable stability indicating chemometric methods were developed for the quantitative determination of Agomelatine (AGM) whether in pure form or in pharmaceutical formulations. Two supervised learning machines' methods; linear artificial neural networks (PC-linANN) preceded by principle component analysis and linear support vector regression (linSVR), were compared with two principle component based methods; principle component regression (PCR) as well as partial least squares (PLS) for the spectrofluorimetric determination of AGM and its degradants. The results showed the benefits behind using linear learning machines' methods and the inherent merits of their algorithms in handling overlapped noisy spectral data especially during the challenging determination of AGM alkaline and acidic degradants (DG1 and DG2). Relative mean squared error of prediction (RMSEP) for the proposed models in the determination of AGM were 1.68, 1.72, 0.68 and 0.22 for PCR, PLS, SVR and PC-linANN; respectively. The results showed the superiority of supervised learning machines' methods over principle component based methods. Besides, the results suggested that linANN is the method of choice for determination of components in low amounts with similar overlapped spectra and narrow linearity range. Comparison between the proposed chemometric models and a reported HPLC method revealed the comparable performance and quantification power of the proposed models.

Soft Computing Application in Fault Detection of Induction Motor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konar, P.; Puhan, P. S.; Chattopadhyay, P. Dr.

2010-10-26

The paper investigates the effectiveness of different patter classifier like Feed Forward Back Propagation (FFBPN), Radial Basis Function (RBF) and Support Vector Machine (SVM) for detection of bearing faults in Induction Motor. The steady state motor current with Park's Transformation has been used for discrimination of inner race and outer race bearing defects. The RBF neural network shows very encouraging results for multi-class classification problems and is hoped to set up a base for incipient fault detection of induction motor. SVM is also found to be a very good fault classifier which is highly competitive with RBF.

Prediction of B-cell linear epitopes with a combination of support vector machine classification and amino acid propensity identification.

PubMed

Wang, Hsin-Wei; Lin, Ya-Chi; Pai, Tun-Wen; Chang, Hao-Teng

2011-01-01

Epitopes are antigenic determinants that are useful because they induce B-cell antibody production and stimulate T-cell activation. Bioinformatics can enable rapid, efficient prediction of potential epitopes. Here, we designed a novel B-cell linear epitope prediction system called LEPS, Linear Epitope Prediction by Propensities and Support Vector Machine, that combined physico-chemical propensity identification and support vector machine (SVM) classification. We tested the LEPS on four datasets: AntiJen, HIV, a newly generated PC, and AHP, a combination of these three datasets. Peptides with globally or locally high physicochemical propensities were first identified as primitive linear epitope (LE) candidates. Then, candidates were classified with the SVM based on the unique features of amino acid segments. This reduced the number of predicted epitopes and enhanced the positive prediction value (PPV). Compared to four other well-known LE prediction systems, the LEPS achieved the highest accuracy (72.52%), specificity (84.22%), PPV (32.07%), and Matthews' correlation coefficient (10.36%).

Opportunistic Constructive Induction: Using Fragments of Domain Knowledge to Guide Construction

DTIC Science & Technology

1991-01-01

contribute to its success in ways which they are often unaware of and, unfortunately, which go by unacknowledged. At the risk of omitting some people I am...ference on Machine Learning, pages 322 -329, Austin, TX, June 1990. [Blumer e_1 al... 19871 Anselm Blurner, Andrzej Ehrenfeucht, David Haussler, and...and Ryszard S. Michalki. A Comparative Review of Selected Methods fur Learning from Examples. In- Machine Learning: An A rtificialIntelligence

Superconductivity for Electromagnetic Guns

DTIC Science & Technology

1984-03-01

greater than that for a pulsed homopolar machine when the time constant is less than 0.1 sec (ref 32) (See fig. 18). Since the energy density in a...transferred from the capacitor to the induct- or. If the capacitor is replaced by a homopolar machine, then, as is well-known, the kinetic energy of the...rotor plays the role of an "electrical" capacitance and the two arrangements (capacitance and homopolar ) are functionally equivalent. Group 3. In

Electric field prediction for a human body-electric machine system.

PubMed

Ioannides, Maria G; Papadopoulos, Peter J; Dimitropoulou, Eugenia

2004-01-01

A system consisting of an electric machine and a human body is studied and the resulting electric field is predicted. A 3-phase induction machine operating at full load is modeled considering its geometry, windings, and materials. A human model is also constructed approximating its geometry and the electric properties of tissues. Using the finite element technique the electric field distribution in the human body is determined for a distance of 1 and 5 m from the machine and its effects are studied. Particularly, electric field potential variations are determined at specific points inside the human body and for these points the electric field intensity is computed and compared to the limit values for exposure according to international standards.

Three dimensional magnetic fields in extra high speed modified Lundell alternators computed by a combined vector-scalar magnetic potential finite element method

NASA Technical Reports Server (NTRS)

Demerdash, N. A.; Wang, R.; Secunde, R.

1992-01-01

A 3D finite element (FE) approach was developed and implemented for computation of global magnetic fields in a 14.3 kVA modified Lundell alternator. The essence of the new method is the combined use of magnetic vector and scalar potential formulations in 3D FEs. This approach makes it practical, using state of the art supercomputer resources, to globally analyze magnetic fields and operating performances of rotating machines which have truly 3D magnetic flux patterns. The 3D FE-computed fields and machine inductances as well as various machine performance simulations of the 14.3 kVA machine are presented in this paper and its two companion papers.

Wireless Monitoring of Induction Machine Rotor Physical Variables

PubMed Central

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; de Paiva, José Alvaro

2017-01-01

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor’s shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor. PMID:29156564

Wireless Monitoring of Induction Machine Rotor Physical Variables.

PubMed

Doolan Fernandes, Jefferson; Carvalho Souza, Francisco Elvis; Cipriano Maniçoba, Glauco George; Salazar, Andrés Ortiz; de Paiva, José Alvaro

2017-11-18

With the widespread use of electric machines, there is a growing need to extract information from the machines to improve their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of the rotor physical variables of a squirrel cage induction motor. The system is comprised of: a circuit to acquire desirable rotor variable(s) and value(s) that send it to the computer; a rectifier and power storage circuit that converts an alternating current in a continuous current but also stores energy for a certain amount of time to wait for the motor's shutdown; and a magnetic generator that harvests energy from the rotating field to power the circuits mentioned above. The embedded system is set on the rotor of a 5 HP squirrel cage induction motor, making it difficult to power the system because it is rotating. This problem can be solved with the construction of a magnetic generator device to avoid the need of using batteries or collector rings and will send data to the computer using a wireless NRF24L01 module. For the proposed system, initial validation tests were made using a temperature sensor (DS18b20), as this variable is known as the most important when identifying the need for maintenance and control systems. Few tests have shown promising results that, with further improvements, can prove the feasibility of using sensors in the rotor.

Design considerations for ultra-precision magnetic bearing supported slides

NASA Technical Reports Server (NTRS)

Slocum, Alexander H.; Eisenhaure, David B.

1993-01-01

Development plans for a prototype servocontrolled machine with 1 angstrom resolution of linear motion and 50 mm range of travel are described. Two such devices could then be combined to produce a two dimensional machine for probing large planar objects with atomic resolution, the Angstrom Resolution Measuring Machine (ARMM).

Active balance system and vibration balanced machine

NASA Technical Reports Server (NTRS)

White, Maurice A. (Inventor); Qiu, Songgang (Inventor); Augenblick, John E. (Inventor); Peterson, Allen A. (Inventor)

2005-01-01

An active balance system is provided for counterbalancing vibrations of an axially reciprocating machine. The balance system includes a support member, a flexure assembly, a counterbalance mass, and a linear motor or an actuator. The support member is configured for attachment to the machine. The flexure assembly includes at least one flat spring having connections along a central portion and an outer peripheral portion. One of the central portion and the outer peripheral portion is fixedly mounted to the support member. The counterbalance mass is fixedly carried by the flexure assembly along another of the central portion and the outer peripheral portion. The linear motor has one of a stator and a mover fixedly mounted to the support member and another of the stator and the mover fixedly mounted to the counterbalance mass. The linear motor is operative to axially reciprocate the counterbalance mass.

Punching influence on magnetic properties of the stator teeth of an induction motor

NASA Astrophysics Data System (ADS)

Kedous-Lebouc, A.; Cornut, B.; Perrier, J. C.; Manfé, Ph.; Chevalier, Th.

2003-01-01

In order to study the effects of punching of electrical steel sheets, a suitable geometrical structure able to characterize the stator teeth behavior of an induction motor is proposed and validated. The influence of the punching on a fully processed M330-65A is then characterized. A spectacular degradation of loss and B( H) curves is observed. This leads to a perceptible increase of the no-load machine current.

Effect of hole geometry and Electric-Discharge Machining (EDM) on airflow rates through small diameter holes in turbine blade material

NASA Technical Reports Server (NTRS)

Hippensteele, S. A.; Cochran, R. P.

1980-01-01

The effects of two design parameters, electrode diameter and hole angle, and two machine parameters, electrode current and current-on time, on air flow rates through small-diameter (0.257 to 0.462 mm) electric-discharge-machined holes were measured. The holes were machined individually in rows of 14 each through 1.6 mm thick IN-100 strips. The data showed linear increase in air flow rate with increases in electrode cross sectional area and current-on time and little change with changes in hole angle and electrode current. The average flow-rate deviation (from the mean flow rate for a given row) decreased linearly with electrode diameter and increased with hole angle. Burn time and finished hole diameter were also measured.

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-1 and PERL-11). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

Lawrence Livermore National Laboratory ULTRA-350 Test Bed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hopkins, D J; Wulff, T A; Carlisle, K

2001-04-10

LLNL has many in-house designed high precision machine tools. Some of these tools include the Large Optics Diamond Turning Machine (LODTM) [1], Diamond Turning Machine No.3 (DTM-3) and two Precision Engineering Research Lathes (PERL-I and PERL-II). These machines have accuracy in the sub-micron range and in most cases position resolution in the couple of nanometers range. All of these machines are built with similar underlying technologies. The machines use capstan drive technology, laser interferometer position feedback, tachometer velocity feedback, permanent magnet (PM) brush motors and analog velocity and position loop servo compensation [2]. The machine controller does not perform anymore » servo compensation it simply computes the differences between the commanded position and the actual position (the following error) and sends this to a D/A for the analog servo position loop. LLNL is designing a new high precision diamond turning machine. The machine is called the ULTRA 350 [3]. In contrast to many of the proven technologies discussed above, the plan for the new machine is to use brushless linear motors, high precision linear scales, machine controller motor commutation and digital servo compensation for the velocity and position loops. Although none of these technologies are new and have been in use in industry, applications of these technologies to high precision diamond turning is limited. To minimize the risks of these technologies in the new machine design, LLNL has established a test bed to evaluate these technologies for application in high precision diamond turning. The test bed is primarily composed of commercially available components. This includes the slide with opposed hydrostatic bearings, the oil system, the brushless PM linear motor, the two-phase input three-phase output linear motor amplifier and the system controller. The linear scales are not yet commercially available but use a common electronic output format. As of this writing, the final verdict for the use of these technologies is still out but the first part of the work has been completed with promising results. The goal of this part of the work was to close a servo position loop around a slide incorporating these technologies and to measure the performance. This paper discusses the tests that were setup for system evaluation and the results of the measurements made. Some very promising results include; slide positioning to nanometer level and slow speed slide direction reversal at less than 100nm/min with no observed discontinuities. This is very important for machine contouring in diamond turning. As a point of reference, at 100 nm/min it would take the slide almost 7 years to complete the full designed travel of 350 mm. This speed has been demonstrated without the use of a velocity sensor. The velocity is derived from the position sensor. With what has been learned on the test bed, the paper finishes with a brief comparison of the old and new technologies. The emphasis of this comparison will be on the servo performance as illustrated with bode plot diagrams.« less

An inductance Fourier decomposition-based current-hysteresis control strategy for switched reluctance motors

NASA Astrophysics Data System (ADS)

Hua, Wei; Qi, Ji; Jia, Meng

2017-05-01

Switched reluctance machines (SRMs) have attracted extensive attentions due to the inherent advantages, including simple and robust structure, low cost, excellent fault-tolerance and wide speed range, etc. However, one of the bottlenecks limiting the SRMs for further applications is its unfavorable torque ripple, and consequently noise and vibration due to the unique doubly-salient structure and pulse-current-based power supply method. In this paper, an inductance Fourier decomposition-based current-hysteresis-control (IFD-CHC) strategy is proposed to reduce torque ripple of SRMs. After obtaining a nonlinear inductance-current-position model based Fourier decomposition, reference currents can be calculated by reference torque and the derived inductance model. Both the simulations and experimental results confirm the effectiveness of the proposed strategy.

Modelling daily water temperature from air temperature for the Missouri River.

PubMed

Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana

2018-01-01

The bio-chemical and physical characteristics of a river are directly affected by water temperature, which thereby affects the overall health of aquatic ecosystems. It is a complex problem to accurately estimate water temperature. Modelling of river water temperature is usually based on a suitable mathematical model and field measurements of various atmospheric factors. In this article, the air-water temperature relationship of the Missouri River is investigated by developing three different machine learning models (Artificial Neural Network (ANN), Gaussian Process Regression (GPR), and Bootstrap Aggregated Decision Trees (BA-DT)). Standard models (linear regression, non-linear regression, and stochastic models) are also developed and compared to machine learning models. Analyzing the three standard models, the stochastic model clearly outperforms the standard linear model and nonlinear model. All the three machine learning models have comparable results and outperform the stochastic model, with GPR having slightly better results for stations No. 2 and 3, while BA-DT has slightly better results for station No. 1. The machine learning models are very effective tools which can be used for the prediction of daily river temperature.

A Navier-Strokes Chimera Code on the Connection Machine CM-5: Design and Performance

NASA Technical Reports Server (NTRS)

Jespersen, Dennis C.; Levit, Creon; Kwak, Dochan (Technical Monitor)

1994-01-01

We have implemented a three-dimensional compressible Navier-Stokes code on the Connection Machine CM-5. The code is set up for implicit time-stepping on single or multiple structured grids. For multiple grids and geometrically complex problems, we follow the 'chimera' approach, where flow data on one zone is interpolated onto another in the region of overlap. We will describe our design philosophy and give some timing results for the current code. A parallel machine like the CM-5 is well-suited for finite-difference methods on structured grids. The regular pattern of connections of a structured mesh maps well onto the architecture of the machine. So the first design choice, finite differences on a structured mesh, is natural. We use centered differences in space, with added artificial dissipation terms. When numerically solving the Navier-Stokes equations, there are liable to be some mesh cells near a solid body that are small in at least one direction. This mesh cell geometry can impose a very severe CFL (Courant-Friedrichs-Lewy) condition on the time step for explicit time-stepping methods. Thus, though explicit time-stepping is well-suited to the architecture of the machine, we have adopted implicit time-stepping. We have further taken the approximate factorization approach. This creates the need to solve large banded linear systems and creates the first possible barrier to an efficient algorithm. To overcome this first possible barrier we have considered two options. The first is just to solve the banded linear systems with data spread over the whole machine, using whatever fast method is available. This option is adequate for solving scalar tridiagonal systems, but for scalar pentadiagonal or block tridiagonal systems it is somewhat slower than desired. The second option is to 'transpose' the flow and geometry variables as part of the time-stepping process: Start with x-lines of data in-processor. Form explicit terms in x, then transpose so y-lines of data are in-processor. Form explicit terms in y, then transpose so z-lines are in processor. Form explicit terms in z, then solve linear systems in the z-direction. Transpose to the y-direction, then solve linear systems in the y-direction. Finally transpose to the x direction and solve linear systems in the x-direction. This strategy avoids inter-processor communication when differencing and solving linear systems, but requires a large amount of communication when doing the transposes. The transpose method is more efficient than the non-transpose strategy when dealing with scalar pentadiagonal or block tridiagonal systems. For handling geometrically complex problems the chimera strategy was adopted. For multiple zone cases we compute on each zone sequentially (using the whole parallel machine), then send the chimera interpolation data to a distributed data structure (array) laid out over the whole machine. This information transfer implies an irregular communication pattern, and is the second possible barrier to an efficient algorithm. We have implemented these ideas on the CM-5 using CMF (Connection Machine Fortran), a data parallel language which combines elements of Fortran 90 and certain extensions, and which bears a strong similarity to High Performance Fortran. We make use of the Connection Machine Scientific Software Library (CMSSL) for the linear solver and array transpose operations.

Applications of Support Vector Machines In Chemo And Bioinformatics

NASA Astrophysics Data System (ADS)

Jayaraman, V. K.; Sundararajan, V.

2010-10-01

Conventional linear & nonlinear tools for classification, regression & data driven modeling are being replaced on a rapid scale by newer techniques & tools based on artificial intelligence and machine learning. While the linear techniques are not applicable for inherently nonlinear problems, newer methods serve as attractive alternatives for solving real life problems. Support Vector Machine (SVM) classifiers are a set of universal feed-forward network based classification algorithms that have been formulated from statistical learning theory and structural risk minimization principle. SVM regression closely follows the classification methodology. In this work recent applications of SVM in Chemo & Bioinformatics will be described with suitable illustrative examples.

Stable Spheromaks Sustained by Neutral Beam Injection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, T K; Jayakumar, R; McLean, H S

It is shown that spheromak equilibria, stable at zero-beta but departing from the Taylor state, could be sustained by non-inductive current drive at acceptable power levels. Stability to both ideal MHD and tearing modes is verified using the NIMROD code for linear stability analysis. Non-linear NIMROD calculations with non-inductive current drive and pressure effects could point the way to improved fusion reactors.

Characterization of Diesel and Gasoline Compression Ignition Combustion in a Rapid Compression-Expansion Machine using OH* Chemiluminescence Imaging

NASA Astrophysics Data System (ADS)

Krishnan, Sundar Rajan; Srinivasan, Kalyan Kumar; Stegmeir, Matthew

2015-11-01

Direct-injection compression ignition combustion of diesel and gasoline were studied in a rapid compression-expansion machine (RCEM) using high-speed OH* chemiluminescence imaging. The RCEM (bore = 84 mm, stroke = 110-250 mm) was used to simulate engine-like operating conditions at the start of fuel injection. The fuels were supplied by a high-pressure fuel cart with an air-over-fuel pressure amplification system capable of providing fuel injection pressures up to 2000 bar. A production diesel fuel injector was modified to provide a single fuel spray for both diesel and gasoline operation. Time-resolved combustion pressure in the RCEM was measured using a Kistler piezoelectric pressure transducer mounted on the cylinder head and the instantaneous piston displacement was measured using an inductive linear displacement sensor (0.05 mm resolution). Time-resolved, line-of-sight OH* chemiluminescence images were obtained using a Phantom V611 CMOS camera (20.9 kHz @ 512 x 512 pixel resolution, ~ 48 μs time resolution) coupled with a short wave pass filter (cut-off ~ 348 nm). The instantaneous OH* distributions, which indicate high temperature flame regions within the combustion chamber, were used to discern the characteristic differences between diesel and gasoline compression ignition combustion. The authors gratefully acknowledge facilities support for the present work from the Energy Institute at Mississippi State University.

Linear microbunching analysis for recirculation machines

DOE PAGES

Tsai, C. -Y.; Douglas, D.; Li, R.; ...

2016-11-28

Microbunching instability (MBI) has been one of the most challenging issues in designs of magnetic chicanes for short-wavelength free-electron lasers or linear colliders, as well as those of transport lines for recirculating or energy-recovery-linac machines. To quantify MBI for a recirculating machine and for more systematic analyses, we have recently developed a linear Vlasov solver and incorporated relevant collective effects into the code, including the longitudinal space charge, coherent synchrotron radiation, and linac geometric impedances, with extension of the existing formulation to include beam acceleration. In our code, we semianalytically solve the linearized Vlasov equation for microbunching amplification factor formore » an arbitrary linear lattice. In this study we apply our code to beam line lattices of two comparative isochronous recirculation arcs and one arc lattice preceded by a linac section. The resultant microbunching gain functions and spectral responses are presented, with some results compared to particle tracking simulation by elegant (M. Borland, APS Light Source Note No. LS-287, 2002). These results demonstrate clearly the impact of arc lattice design on the microbunching development. Lastly, the underlying physics with inclusion of those collective effects is elucidated and the limitation of the existing formulation is also discussed.« less

Active vibration and balance system for closed cycle thermodynamic machines

NASA Technical Reports Server (NTRS)

Augenblick, John E. (Inventor); Peterson, Allen A. (Inventor); White, Maurice A. (Inventor); Qiu, Songgang (Inventor)

2004-01-01

An active balance system is provided for counterbalancing vibrations of an axially reciprocating machine. The balance system includes a support member, a flexure assembly, a counterbalance mass, and a linear motor or an actuator. The support member is configured for attachment to the machine. The flexure assembly includes at least one flat spring having connections along a central portion and an outer peripheral portion. One of the central portion and the outer peripheral portion is fixedly mounted to the support member. The counterbalance mass is fixedly carried by the flexure assembly along another of the central portion and the outer peripheral portion. The linear motor has one of a stator and a mover fixedly mounted to the support member and another of the stator and the mover fixedly mounted to the counterbalance mass. The linear motor is operative to axially reciprocate the counterbalance mass. A method is also provided.

Using a PC and external media to quantitatively investigate electromagnetic induction

NASA Astrophysics Data System (ADS)

Bonanno, A.; Bozzo, G.; Camarca, M.; Sapia, P.

2011-07-01

In this article we describe an experimental learning path about electromagnetic induction which uses an Atwood machine where one of the two hanging bodies is a cylindrical magnet falling through a plexiglass guide, surrounded either by a coil or by a copper pipe. The first configuration (magnet falling across a coil) allows students to quantitatively study the Faraday-Neumann-Lenz law, while the second configuration (falling through a copper pipe) permits learners to investigate the complex phenomena of induction by quantifying the amount of electric power dissipated through the pipe as a result of Foucault eddy currents, when the magnet travels through the pipe. The magnet's fall acceleration can be set by adjusting the counterweight of the Atwood machine so that both the kinematic quantities associated with it and the electromotive force induced within the coil are continuously and quantitatively monitored (respectively, by a common personal computer (PC) equipped with a webcam and by freely available software that makes it possible to use the audio card to convert the PC into an oscilloscope). Measurements carried out when the various experimental parameters are changed provide a useful framework for a thorough understanding and clarification of the conceptual nodes related to electromagnetic induction. The proposed learning path is under evaluation in various high schools participating in the project 'Lauree Scientifiche' promoted by the Italian Department of Education.

On the divergence-free condition in Godunov-type schemes for ideal magnetohydrodynamics: the upwind constrained transport method

NASA Astrophysics Data System (ADS)

Londrillo, P.; del Zanna, L.

2004-03-01

We present a general framework to design Godunov-type schemes for multidimensional ideal magnetohydrodynamic (MHD) systems, having the divergence-free relation and the related properties of the magnetic field B as built-in conditions. Our approach mostly relies on the constrained transport (CT) discretization technique for the magnetic field components, originally developed for the linear induction equation, which assures [∇.B]num=0 and its preservation in time to within machine accuracy in a finite-volume setting. We show that the CT formalism, when fully exploited, can be used as a general guideline to design the reconstruction procedures of the B vector field, to adapt standard upwind procedures for the momentum and energy equations, avoiding the onset of numerical monopoles of O(1) size, and to formulate approximate Riemann solvers for the induction equation. This general framework will be named here upwind constrained transport (UCT). To demonstrate the versatility of our method, we apply it to a variety of schemes, which are finally validated numerically and compared: a novel implementation for the MHD case of the second-order Roe-type positive scheme by Liu and Lax [J. Comput. Fluid Dyn. 5 (1996) 133], and both the second- and third-order versions of a central-type MHD scheme presented by Londrillo and Del Zanna [Astrophys. J. 530 (2000) 508], where the basic UCT strategies have been first outlined.

Rise time analysis of pulsed klystron-modulator for efficiency improvement of linear colliders

NASA Astrophysics Data System (ADS)

Oh, J. S.; Cho, M. H.; Namkung, W.; Chung, K. H.; Shintake, T.; Matsumoto, H.

2000-04-01

In linear accelerators, the periods during the rise and fall of a klystron-modulator pulse cannot be used to generate RF power. Thus, these periods need to be minimized to get high efficiency, especially in large-scale machines. In this paper, we present a simplified and generalized voltage rise time function of a pulsed modulator with a high-power klystron load using the equivalent circuit analysis method. The optimum pulse waveform is generated when this pulsed power system is tuned with a damping factor of ˜0.85. The normalized rise time chart presented in this paper allows one to predict the rise time and pulse shape of the pulsed power system in general. The results can be summarized as follows: The large distributed capacitance in the pulse tank and operating parameters, Vs× Tp , where Vs is load voltage and Tp is the pulse width, are the main factors determining the pulse rise time in the high-power RF system. With an RF pulse compression scheme, up to ±3% ripple of the modulator voltage is allowed without serious loss of compressor efficiency, which allows the modulator efficiency to be improved as well. The wiring inductance should be minimized to get the fastest rise time.

An Efficient Fuzzy Controller Design for Parallel Connected Induction Motor Drives

NASA Astrophysics Data System (ADS)

Usha, S.; Subramani, C.

2018-04-01

Generally, an induction motors are highly non-linear and has a complex time varying dynamics. This makes the speed control of an induction motor a challenging issue in the industries. But, due to the recent trends in the power electronic devices and intelligent controllers, the speed control of the induction motor is achieved by including non-linear characteristics also. Conventionally a single inverter is used to run one induction motor in industries. In the traction applications, two or more inductions motors are operated in parallel to reduce the size and cost of induction motors. In this application, the parallel connected induction motors can be driven by a single inverter unit. The stability problems may introduce in the parallel operation under low speed operating conditions. Hence, the speed deviations should be reduce with help of suitable controllers. The speed control of the parallel connected system is performed by PID controller and fuzzy logic controller. In this paper the speed response of the induction motor for the rating of IHP, 1440 rpm, and 50Hz with these controller are compared in time domain specifications. The stability analysis of the system also performed under low speed using matlab platform. The hardware model is developed for speed control using fuzzy logic controller which exhibited superior performances over the other controller.

MABE multibeam accelerator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasti, D.E.; Ramirez, J.J.; Coleman, P.D.

1985-01-01

The Megamp Accelerator and Beam Experiment (MABE) was the technology development testbed for the multiple beam, linear induction accelerator approach for Hermes III, a new 20 MeV, 0.8 MA, 40 ns accelerator being developed at Sandia for gamma-ray simulation. Experimental studies of a high-current, single-beam accelerator (8 MeV, 80 kA), and a nine-beam injector (1.4 MeV, 25 kA/beam) have been completed, and experiments on a nine-beam linear induction accelerator are in progress. A two-beam linear induction accelerator is designed and will be built as a gamma-ray simulator to be used in parallel with Hermes III. The MABE pulsed power systemmore » and accelerator for the multiple beam experiments is described. Results from these experiments and the two-beam design are discussed. 11 refs., 6 figs.« less

Signal injection as a fault detection technique.

PubMed

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies.

Support vector machine based decision for mechanical fault condition monitoring in induction motor using an advanced Hilbert-Park transform.

PubMed

Ben Salem, Samira; Bacha, Khmais; Chaari, Abdelkader

2012-09-01

In this work we suggest an original fault signature based on an improved combination of Hilbert and Park transforms. Starting from this combination we can create two fault signatures: Hilbert modulus current space vector (HMCSV) and Hilbert phase current space vector (HPCSV). These two fault signatures are subsequently analysed using the classical fast Fourier transform (FFT). The effects of mechanical faults on the HMCSV and HPCSV spectrums are described, and the related frequencies are determined. The magnitudes of spectral components, relative to the studied faults (air-gap eccentricity and outer raceway ball bearing defect), are extracted in order to develop the input vector necessary for learning and testing the support vector machine with an aim of classifying automatically the various states of the induction motor. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Grid-connected in-stream hydroelectric generation based on the doubly fed induction machine

NASA Astrophysics Data System (ADS)

Lenberg, Timothy J.

Within the United States, there is a growing demand for new environmentally friendly power generation. This has led to a surge in wind turbine development. Unfortunately, wind is not a stable prime mover, but water is. Why not apply the advances made for wind to in-stream hydroelectric generation? One important advancement is the creation of the Doubly Fed Induction Machine (DFIM). This thesis covers the application of a gearless DFIM topology for hydrokinetic generation. After providing background, this thesis presents many of the options available for the mechanical portion of the design. A mechanical turbine is then specified. Next, a method is presented for designing a DFIM including the actual design for this application. In Chapter 4, a simulation model of the system is presented, complete with a control system that maximizes power generation based on water speed. This section then goes on to present simulation results demonstrating proper operation.

Signal Injection as a Fault Detection Technique

PubMed Central

Cusidó, Jordi; Romeral, Luis; Ortega, Juan Antonio; Garcia, Antoni; Riba, Jordi

2011-01-01

Double frequency tests are used for evaluating stator windings and analyzing the temperature. Likewise, signal injection on induction machines is used on sensorless motor control fields to find out the rotor position. Motor Current Signature Analysis (MCSA), which focuses on the spectral analysis of stator current, is the most widely used method for identifying faults in induction motors. Motor faults such as broken rotor bars, bearing damage and eccentricity of the rotor axis can be detected. However, the method presents some problems at low speed and low torque, mainly due to the proximity between the frequencies to be detected and the small amplitude of the resulting harmonics. This paper proposes the injection of an additional voltage into the machine being tested at a frequency different from the fundamental one, and then studying the resulting harmonics around the new frequencies appearing due to the composition between injected and main frequencies. PMID:22163801

Dynamics of a Flywheel Energy Storage System Supporting a Wind Turbine Generator in a Microgrid

NASA Astrophysics Data System (ADS)

Nair S, Gayathri; Senroy, Nilanjan

2016-02-01

Integration of an induction machine based flywheel energy storage system with a wind energy conversion system is implemented in this paper. The nonlinear and linearized models of the flywheel are studied, compared and a reduced order model of the same simulated to analyze the influence of the flywheel inertia and control in system response during a wind power change. A quantification of the relation between the inertia of the flywheel and the controller gain is obtained which allows the system to be considered as a reduced order model that is more controllable in nature. A microgrid setup comprising of the flywheel energy storage system, a two mass model of a DFIG based wind turbine generator and a reduced order model of a diesel generator is utilized to analyse the microgrid dynamics accurately in the event of frequency variations arising due to wind power change. The response of the microgrid with and without the flywheel is studied.

High power microwave source development

NASA Astrophysics Data System (ADS)

Benford, James N.; Miller, Gabriel; Potter, Seth; Ashby, Steve; Smith, Richard R.

1995-05-01

The requirements of this project have been to: (1) improve and expand the sources available in the facility for testing purposes and (2) perform specific tasks under direction of the Defense Nuclear Agency about the applications of high power microwaves (HPM). In this project the HPM application was power beaming. The requirements of this program were met in the following way: (1) We demonstrated that a compact linear induction accelerator can drive HPM sources at repetition rates in excess of 100 HZ at peak microwave powers of a GW. This was done for the relativistic magnetron. Since the conclusion of this contract such specifications have also been demonstrated for the relativistic klystron under Ballistic Missile Defense Organization funding. (2) We demonstrated an L band relativistic magnetron. This device has been used both on our single pulse machines, CAMEL and CAMEL X, and the repetitive system CLIA. (3) We demonstrated that phase locking of sources together in large numbers is a feasible technology and showed the generation of multigigawatt S-band radiation in an array of relativistic magnetrons.

Intra-regional classification of grape seeds produced in Mendoza province (Argentina) by multi-elemental analysis and chemometrics tools.

PubMed

Canizo, Brenda V; Escudero, Leticia B; Pérez, María B; Pellerano, Roberto G; Wuilloud, Rodolfo G

2018-03-01

The feasibility of the application of chemometric techniques associated with multi-element analysis for the classification of grape seeds according to their provenance vineyard soil was investigated. Grape seed samples from different localities of Mendoza province (Argentina) were evaluated. Inductively coupled plasma mass spectrometry (ICP-MS) was used for the determination of twenty-nine elements (Ag, As, Ce, Co, Cs, Cu, Eu, Fe, Ga, Gd, La, Lu, Mn, Mo, Nb, Nd, Ni, Pr, Rb, Sm, Te, Ti, Tl, Tm, U, V, Y, Zn and Zr). Once the analytical data were collected, supervised pattern recognition techniques such as linear discriminant analysis (LDA), partial least square discriminant analysis (PLS-DA), k-nearest neighbors (k-NN), support vector machine (SVM) and Random Forest (RF) were applied to construct classification/discrimination rules. The results indicated that nonlinear methods, RF and SVM, perform best with up to 98% and 93% accuracy rate, respectively, and therefore are excellent tools for classification of grapes. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive

PubMed Central

Gutierrez-Villalobos, Jose M.; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A.; Martínez-Hernández, Moisés A.

2015-01-01

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor. PMID:26131677

Sensorless FOC Performance Improved with On-Line Speed and Rotor Resistance Estimator Based on an Artificial Neural Network for an Induction Motor Drive.

PubMed

Gutierrez-Villalobos, Jose M; Rodriguez-Resendiz, Juvenal; Rivas-Araiza, Edgar A; Martínez-Hernández, Moisés A

2015-06-29

Three-phase induction motor drive requires high accuracy in high performance processes in industrial applications. Field oriented control, which is one of the most employed control schemes for induction motors, bases its function on the electrical parameter estimation coming from the motor. These parameters make an electrical machine driver work improperly, since these electrical parameter values change at low speeds, temperature changes, and especially with load and duty changes. The focus of this paper is the real-time and on-line electrical parameters with a CMAC-ADALINE block added in the standard FOC scheme to improve the IM driver performance and endure the driver and the induction motor lifetime. Two kinds of neural network structures are used; one to estimate rotor speed and the other one to estimate rotor resistance of an induction motor.

Design and analysis of an unconventional permanent magnet linear machine for energy harvesting

NASA Astrophysics Data System (ADS)

Zeng, Peng

This Ph.D. dissertation proposes an unconventional high power density linear electromagnetic kinetic energy harvester, and a high-performance two-stage interface power electronics to maintain maximum power abstraction from the energy source and charge the Li-ion battery load with constant current. The proposed machine architecture is composed of a double-sided flat type silicon steel stator with winding slots, a permanent magnet mover, coil windings, a linear motion guide and an adjustable spring bearing. The unconventional design of the machine is that NdFeB magnet bars in the mover are placed with magnetic fields in horizontal direction instead of vertical direction and the same magnetic poles are facing each other. The derived magnetic equivalent circuit model proves the average air-gap flux density of the novel topology is as high as 0.73 T with 17.7% improvement over that of the conventional topology at the given geometric dimensions of the proof-of-concept machine. Subsequently, the improved output voltage and power are achieved. The dynamic model of the linear generator is also developed, and the analytical equations of output maximum power are derived for the case of driving vibration with amplitude that is equal, smaller and larger than the relative displacement between the mover and the stator of the machine respectively. Furthermore, the finite element analysis (FEA) model has been simulated to prove the derived analytical results and the improved power generation capability. Also, an optimization framework is explored to extend to the multi-Degree-of-Freedom (n-DOF) vibration based linear energy harvesting devices. Moreover, a boost-buck cascaded switch mode converter with current controller is designed to extract the maximum power from the harvester and charge the Li-ion battery with trickle current. Meanwhile, a maximum power point tracking (MPPT) algorithm is proposed and optimized for low frequency driving vibrations. Finally, a proof-of-concept unconventional permanent magnet (PM) linear generator is prototyped and tested to verify the simulation results of the FEA model. For the coil windings of 33, 66 and 165 turns, the output power of the machine is tested to have the output power of 65.6 mW, 189.1 mW, and 497.7 mW respectively with the maximum power density of 2.486 mW/cm3.

Segmented rail linear induction motor

DOEpatents

Cowan, Jr., Maynard; Marder, Barry M.

1996-01-01

A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces.

First Stage of a Highly Reliable Reusable Launch System

NASA Technical Reports Server (NTRS)

Kloesel, Kurt J.; Pickrel, Jonathan B.; Sayles, Emily L.; Wright, Michael; Marriott, Darin; Holland, Leo; Kuznetsov, Stephen

2009-01-01

Electromagnetic launch assist has the potential to provide a highly reliable reusable first stage to a space access system infrastructure at a lower overall cost. This paper explores the benefits of a smaller system that adds the advantages of a high specific impulse air-breathing stage and supersonic launch speeds. The method of virtual specific impulse is introduced as a tool to emphasize the gains afforded by launch assist. Analysis shows launch assist can provide a 278-s virtual specific impulse for a first-stage solid rocket. Additional trajectory analysis demonstrates that a system composed of a launch-assisted first-stage ramjet plus a bipropellant second stage can provide a 48-percent gross lift-off weight reduction versus an all-rocket system. The combination of high-speed linear induction motors and ramjets is identified, as the enabling technologies and benchtop prototypes are investigated. The high-speed response of a standard 60 Hz linear induction motor was tested with a pulse width modulated variable frequency drive to 150 Hz using a 10-lb load, achieving 150 mph. A 300-Hz stator-compensated linear induction motor was constructed and static-tested to 1900 lbf average. A matching ramjet design was developed for use on the 300-Hz linear induction motor.

An M-step preconditioned conjugate gradient method for parallel computation

NASA Technical Reports Server (NTRS)

Adams, L.

1983-01-01

This paper describes a preconditioned conjugate gradient method that can be effectively implemented on both vector machines and parallel arrays to solve sparse symmetric and positive definite systems of linear equations. The implementation on the CYBER 203/205 and on the Finite Element Machine is discussed and results obtained using the method on these machines are given.

Effect of electric arc, gas oxygen torch and induction melting techniques on the marginal accuracy of cast base-metal and noble metal-ceramic crowns.

PubMed

Gómez-Cogolludo, Pablo; Castillo-Oyagüe, Raquel; Lynch, Christopher D; Suárez-García, María-Jesús

2013-09-01

The aim of this study was to identify the most appropriate alloy composition and melting technique by evaluating the marginal accuracy of cast metal-ceramic crowns. Seventy standardised stainless-steel abutments were prepared to receive metal-ceramic crowns and were randomly divided into four alloy groups: Group 1: palladium-gold (Pd-Au), Group 2: nickel-chromium-titanium (Ni-Cr-Ti), Group 3: nickel-chromium (Ni-Cr) and Group 4: titanium (Ti). Groups 1, 2 and 3 were in turn subdivided to be melted and cast using: (a) gas oxygen torch and centrifugal casting machine (TC) or (b) induction and centrifugal casting machine (IC). Group 4 was melted and cast using electric arc and vacuum/pressure machine (EV). All of the metal-ceramic crowns were luted with glass-ionomer cement. The marginal fit was measured under an optical microscope before and after cementation using image analysis software. All data was subjected to two-way analysis of variance (ANOVA). Duncan's multiple range test was run for post-hoc comparisons. The Student's t-test was used to investigate the influence of cementation (α=0.05). Uncemented Pd-Au/TC samples achieved the best marginal adaptation, while the worst fit corresponded to the luted Ti/EV crowns. Pd-Au/TC, Ni-Cr and Ti restorations demonstrated significantly increased misfit after cementation. The Ni-Cr-Ti alloy was the most predictable in terms of differences in misfit when either torch or induction was applied before or after cementation. Cemented titanium crowns exceeded the clinically acceptable limit of 120μm. The combination of alloy composition, melting technique, casting method and luting process influences the vertical seal of cast metal-ceramic crowns. An accurate use of the gas oxygen torch may overcome the results attained with the induction system concerning the marginal adaptation of fixed dental prostheses. Copyright © 2013 Elsevier Ltd. All rights reserved.

On-line diagnosis of defaults on squirrel cage motors using FEM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bentounsi, A.; Nicolas, A.

1998-09-01

In industry, the predictive maintenance has become a strategic concept. Economic interest of on-line diagnosis of faults in electric machines gave rise to various researches in that field. This paper proposes a local approach to tackle the problem of breaking bars and end-rings of squirrel cage in induction machines based mainly on the signature of the local variables, such as the normal flux density. This allows a finer analysis, by use of a finite element based simulation.

Machine learning approaches to the social determinants of health in the health and retirement study.

PubMed

Seligman, Benjamin; Tuljapurkar, Shripad; Rehkopf, David

2018-04-01

Social and economic factors are important predictors of health and of recognized importance for health systems. However, machine learning, used elsewhere in the biomedical literature, has not been extensively applied to study relationships between society and health. We investigate how machine learning may add to our understanding of social determinants of health using data from the Health and Retirement Study. A linear regression of age and gender, and a parsimonious theory-based regression additionally incorporating income, wealth, and education, were used to predict systolic blood pressure, body mass index, waist circumference, and telomere length. Prediction, fit, and interpretability were compared across four machine learning methods: linear regression, penalized regressions, random forests, and neural networks. All models had poor out-of-sample prediction. Most machine learning models performed similarly to the simpler models. However, neural networks greatly outperformed the three other methods. Neural networks also had good fit to the data ( R 2 between 0.4-0.6, versus <0.3 for all others). Across machine learning models, nine variables were frequently selected or highly weighted as predictors: dental visits, current smoking, self-rated health, serial-seven subtractions, probability of receiving an inheritance, probability of leaving an inheritance of at least $10,000, number of children ever born, African-American race, and gender. Some of the machine learning methods do not improve prediction or fit beyond simpler models, however, neural networks performed well. The predictors identified across models suggest underlying social factors that are important predictors of biological indicators of chronic disease, and that the non-linear and interactive relationships between variables fundamental to the neural network approach may be important to consider.

Generation of Custom DSP Transform IP Cores: Case Study Walsh-Hadamard Transform

DTIC Science & Technology

2002-09-01

mathematics and hardware design What I know: Finite state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing...state machine Pipelining Systolic array … What I know: Linear algebra Digital signal processing Adaptive filter theory … A math guy A hardware engineer...Synthesis Technology Libary Bit-width (8) HF factor (1,2,3,6) VF factor (1,2,4, ... 32) Xilinx FPGA Place&Route Xilinx FPGA Place&Route Performance

Non-linear effects in bunch compressor of TARLA

NASA Astrophysics Data System (ADS)

Yildiz, Hüseyin; Aksoy, Avni; Arikan, Pervin

2016-03-01

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects on bunch compressor of TARLA.

Single-machine common/slack due window assignment problems with linear decreasing processing times

NASA Astrophysics Data System (ADS)

Zhang, Xingong; Lin, Win-Chin; Wu, Wen-Hsiang; Wu, Chin-Chia

2017-08-01

This paper studies linear non-increasing processing times and the common/slack due window assignment problems on a single machine, where the actual processing time of a job is a linear non-increasing function of its starting time. The aim is to minimize the sum of the earliness cost, tardiness cost, due window location and due window size. Some optimality results are discussed for the common/slack due window assignment problems and two O(n log n) time algorithms are presented to solve the two problems. Finally, two examples are provided to illustrate the correctness of the corresponding algorithms.

Electric converters of electromagnetic strike machine with capacitor supply

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Kargin, V. A.; Moiseev, A. P.; Chetverikov, E. A.

2018-03-01

The application of pulse linear electromagnetic engines in small power strike machines (energy impact is 0.01...1.0 kJ), where the characteristic mode of rare beats (pulse seismic vibrator, the arch crash device bins bulk materials), is quite effective. At the same time, the technical and economic performance of such machines is largely determined by the ability of the power source to provide a large instantaneous power of the supply pulses in the winding of the linear electromagnetic motor. The use of intermediate energy storage devices in power systems of rare-shock LEME makes it possible to obtain easily large instantaneous powers, forced energy conversion, and increase the performance of the machine. A capacitor power supply of a pulsed source of seismic waves is proposed for the exploration of shallow depths. The sections of the capacitor storage (CS) are connected to the winding of the linear electromagnetic motor by thyristor dischargers, the sequence of activation of which is determined by the control device. The charge of the capacitors to the required voltage is made directly from the battery source, or through the converter from a battery source with a smaller number of batteries.

Dimension Reduction With Extreme Learning Machine.

PubMed

Kasun, Liyanaarachchi Lekamalage Chamara; Yang, Yan; Huang, Guang-Bin; Zhang, Zhengyou

2016-08-01

Data may often contain noise or irrelevant information, which negatively affect the generalization capability of machine learning algorithms. The objective of dimension reduction algorithms, such as principal component analysis (PCA), non-negative matrix factorization (NMF), random projection (RP), and auto-encoder (AE), is to reduce the noise or irrelevant information of the data. The features of PCA (eigenvectors) and linear AE are not able to represent data as parts (e.g. nose in a face image). On the other hand, NMF and non-linear AE are maimed by slow learning speed and RP only represents a subspace of original data. This paper introduces a dimension reduction framework which to some extend represents data as parts, has fast learning speed, and learns the between-class scatter subspace. To this end, this paper investigates a linear and non-linear dimension reduction framework referred to as extreme learning machine AE (ELM-AE) and sparse ELM-AE (SELM-AE). In contrast to tied weight AE, the hidden neurons in ELM-AE and SELM-AE need not be tuned, and their parameters (e.g, input weights in additive neurons) are initialized using orthogonal and sparse random weights, respectively. Experimental results on USPS handwritten digit recognition data set, CIFAR-10 object recognition, and NORB object recognition data set show the efficacy of linear and non-linear ELM-AE and SELM-AE in terms of discriminative capability, sparsity, training time, and normalized mean square error.

Vowel Imagery Decoding toward Silent Speech BCI Using Extreme Learning Machine with Electroencephalogram

PubMed Central

Kim, Jongin; Park, Hyeong-jun

2016-01-01

The purpose of this study is to classify EEG data on imagined speech in a single trial. We recorded EEG data while five subjects imagined different vowels, /a/, /e/, /i/, /o/, and /u/. We divided each single trial dataset into thirty segments and extracted features (mean, variance, standard deviation, and skewness) from all segments. To reduce the dimension of the feature vector, we applied a feature selection algorithm based on the sparse regression model. These features were classified using a support vector machine with a radial basis function kernel, an extreme learning machine, and two variants of an extreme learning machine with different kernels. Because each single trial consisted of thirty segments, our algorithm decided the label of the single trial by selecting the most frequent output among the outputs of the thirty segments. As a result, we observed that the extreme learning machine and its variants achieved better classification rates than the support vector machine with a radial basis function kernel and linear discrimination analysis. Thus, our results suggested that EEG responses to imagined speech could be successfully classified in a single trial using an extreme learning machine with a radial basis function and linear kernel. This study with classification of imagined speech might contribute to the development of silent speech BCI systems. PMID:28097128

Segmented rail linear induction motor

DOEpatents

Cowan, M. Jr.; Marder, B.M.

1996-09-03

A segmented rail linear induction motor has a segmented rail consisting of a plurality of nonferrous electrically conductive segments aligned along a guideway. The motor further includes a carriage including at least one pair of opposed coils fastened to the carriage for moving the carriage. A power source applies an electric current to the coils to induce currents in the conductive surfaces to repel the coils from adjacent edges of the conductive surfaces. 6 figs.

High Energy Colliders

NASA Astrophysics Data System (ADS)

Palmer, R. B.; Gallardo, J. C.

INTRODUCTION PHYSICS CONSIDERATIONS GENERAL REQUIRED LUMINOSITY FOR LEPTON COLLIDERS THE EFFECTIVE PHYSICS ENERGIES OF HADRON COLLIDERS HADRON-HADRON MACHINES LUMINOSITY SIZE AND COST CIRCULAR e^{+}e^- MACHINES LUMINOSITY SIZE AND COST e^{+}e^- LINEAR COLLIDERS LUMINOSITY CONVENTIONAL RF SUPERCONDUCTING RF AT HIGHER ENERGIES γ - γ COLLIDERS μ ^{+} μ^- COLLIDERS ADVANTAGES AND DISADVANTAGES DESIGN STUDIES STATUS AND REQUIRED R AND D COMPARISION OF MACHINES CONCLUSIONS DISCUSSION

The circular form of the linear superconducting machine for marine propulsion

NASA Astrophysics Data System (ADS)

Rakels, J. H.; Mahtani, J. L.; Rhodes, R. G.

1981-01-01

The superconducting linear synchronous machine (LSM) is an efficient method of propulsion of advanced ground transport systems and can also be used in marine engineering for the propulsion of large commercial vessels, tankers, and military ships. It provides high torque at low shaft speeds and ease of reversibility; a circular LSM design is proposed as a drive motor. The equipment is compared with the superconducting homopolar motors, showing flexibility in design, built in redundancy features, and reliability.

A Very Fast and Angular Momentum Conserving Tree Code

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marcello, Dominic C., E-mail: dmarce504@gmail.com

There are many methods used to compute the classical gravitational field in astrophysical simulation codes. With the exception of the typically impractical method of direct computation, none ensure conservation of angular momentum to machine precision. Under uniform time-stepping, the Cartesian fast multipole method of Dehnen (also known as the very fast tree code) conserves linear momentum to machine precision. We show that it is possible to modify this method in a way that conserves both angular and linear momenta.

Performance Analysis of Three-Phase Induction Motor with AC Direct and VFD

NASA Astrophysics Data System (ADS)

Kumar, Dinesh

2018-03-01

The electrical machine analysis and performance calculation is a very important aspect of efficient drive system design. The development of power electronics devices and power converters provide smooth speed control of Induction Motors by changing the frequency of input supply. These converters, on one hand are providing a more flexible speed control that also leads to problems of harmonics and their associated ailments like pulsating torque, distorted current and voltage waveforms, increasing losses etc. This paper includes the performance analysis of three phase induction motor with three-phase AC direct and variable frequency drives (VFD). The comparison has been concluded with respect to various parameters. MATLAB-SIMULINKTM is used for the analysis.

Two models for identification and predicting behaviour of an induction motor system

NASA Astrophysics Data System (ADS)

Kuo, Chien-Hsun

2018-01-01

System identification or modelling is the process of building mathematical models of dynamical systems based on the available input and output data from the systems. This paper introduces system identification by using ARX (Auto Regressive with eXogeneous input) and ARMAX (Auto Regressive Moving Average with eXogeneous input) models. Through the identified system model, the predicted output could be compared with the measured one to help prevent the motor faults from developing into a catastrophic machine failure and avoid unnecessary costs and delays caused by the need to carry out unscheduled repairs. The induction motor system is illustrated as an example. Numerical and experimental results are shown for the identified induction motor system.

Dual linear structured support vector machine tracking method via scale correlation filter

NASA Astrophysics Data System (ADS)

Li, Weisheng; Chen, Yanquan; Xiao, Bin; Feng, Chen

2018-01-01

Adaptive tracking-by-detection methods based on structured support vector machine (SVM) performed well on recent visual tracking benchmarks. However, these methods did not adopt an effective strategy of object scale estimation, which limits the overall tracking performance. We present a tracking method based on a dual linear structured support vector machine (DLSSVM) with a discriminative scale correlation filter. The collaborative tracker comprised of a DLSSVM model and a scale correlation filter obtains good results in tracking target position and scale estimation. The fast Fourier transform is applied for detection. Extensive experiments show that our tracking approach outperforms many popular top-ranking trackers. On a benchmark including 100 challenging video sequences, the average precision of the proposed method is 82.8%.

Quick-Turn Finite Element Analysis for Plug-and-Play Satellite Structures

DTIC Science & Technology

2007-03-01

produced from 0.375 inch round stock and turned on a machine lathe to achieve the shoulder feature and drilled to make it hollow. Figure 3.1...component, a linear taper was machined from the connection shoulder to the solar panel connecting fork. The part was then turned using the machine lathe ...utilizing a modern five-axis Computer Numerical Code ( CNC ) machine mill, the process time could be reduced by as much as seventy-five percent and the

Field-circuit analysis and measurements of a single-phase self-excited induction generator

NASA Astrophysics Data System (ADS)

Makowski, Krzysztof; Leicht, Aleksander

2017-12-01

The paper deals with a single-phase induction machine operating as a stand-alone self-excited single-phase induction generator for generation of electrical energy from renewable energy sources. By changing number of turns and size of wires in the auxiliary stator winding, an improvement of performance characteristics of the generator were obtained as regards no-load and load voltage of the stator windings as well as stator winding currents of the generator. Field-circuit simulation models of the generator were developed using Flux2D software package for the generator with shunt capacitor in the main stator winding. The obtained results have been validated experimentally at the laboratory setup using the single-phase capacitor induction motor of 1.1 kW rated power and 230 V voltage as a base model of the generator.

Magnetic Flux Distribution of Linear Machines with Novel Three-Dimensional Hybrid Magnet Arrays

PubMed Central

Yao, Nan; Yan, Liang; Wang, Tianyi; Wang, Shaoping

2017-01-01

The objective of this paper is to propose a novel tubular linear machine with hybrid permanent magnet arrays and multiple movers, which could be employed for either actuation or sensing technology. The hybrid magnet array produces flux distribution on both sides of windings, and thus helps to increase the signal strength in the windings. The multiple movers are important for airspace technology, because they can improve the system’s redundancy and reliability. The proposed design concept is presented, and the governing equations are obtained based on source free property and Maxwell equations. The magnetic field distribution in the linear machine is thus analytically formulated by using Bessel functions and harmonic expansion of magnetization vector. Numerical simulation is then conducted to validate the analytical solutions of the magnetic flux field. It is proved that the analytical model agrees with the numerical results well. Therefore, it can be utilized for the formulation of signal or force output subsequently, depending on its particular implementation. PMID:29156577

A comparison of optimal MIMO linear and nonlinear models for brain machine interfaces

NASA Astrophysics Data System (ADS)

Kim, S.-P.; Sanchez, J. C.; Rao, Y. N.; Erdogmus, D.; Carmena, J. M.; Lebedev, M. A.; Nicolelis, M. A. L.; Principe, J. C.

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Magnetic Flux Distribution of Linear Machines with Novel Three-Dimensional Hybrid Magnet Arrays.

PubMed

Yao, Nan; Yan, Liang; Wang, Tianyi; Wang, Shaoping

2017-11-18

The objective of this paper is to propose a novel tubular linear machine with hybrid permanent magnet arrays and multiple movers, which could be employed for either actuation or sensing technology. The hybrid magnet array produces flux distribution on both sides of windings, and thus helps to increase the signal strength in the windings. The multiple movers are important for airspace technology, because they can improve the system's redundancy and reliability. The proposed design concept is presented, and the governing equations are obtained based on source free property and Maxwell equations. The magnetic field distribution in the linear machine is thus analytically formulated by using Bessel functions and harmonic expansion of magnetization vector. Numerical simulation is then conducted to validate the analytical solutions of the magnetic flux field. It is proved that the analytical model agrees with the numerical results well. Therefore, it can be utilized for the formulation of signal or force output subsequently, depending on its particular implementation.

A comparison of optimal MIMO linear and nonlinear models for brain-machine interfaces.

PubMed

Kim, S-P; Sanchez, J C; Rao, Y N; Erdogmus, D; Carmena, J M; Lebedev, M A; Nicolelis, M A L; Principe, J C

2006-06-01

The field of brain-machine interfaces requires the estimation of a mapping from spike trains collected in motor cortex areas to the hand kinematics of the behaving animal. This paper presents a systematic investigation of several linear (Wiener filter, LMS adaptive filters, gamma filter, subspace Wiener filters) and nonlinear models (time-delay neural network and local linear switching models) applied to datasets from two experiments in monkeys performing motor tasks (reaching for food and target hitting). Ensembles of 100-200 cortical neurons were simultaneously recorded in these experiments, and even larger neuronal samples are anticipated in the future. Due to the large size of the models (thousands of parameters), the major issue studied was the generalization performance. Every parameter of the models (not only the weights) was selected optimally using signal processing and machine learning techniques. The models were also compared statistically with respect to the Wiener filter as the baseline. Each of the optimization procedures produced improvements over that baseline for either one of the two datasets or both.

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Gravitational induction

NASA Astrophysics Data System (ADS)

Bini, Donato; Cherubini, Christian; Chicone, Carmen; Mashhoon, Bahram

2008-11-01

We study the linear post-Newtonian approximation to general relativity known as gravitoelectromagnetism (GEM); in particular, we examine the similarities and differences between GEM and electrodynamics. Notwithstanding some significant differences between them, we find that a special nonstationary metric in GEM can be employed to show explicitly that it is possible to introduce gravitational induction within GEM in close analogy with Faraday's law of induction and Lenz's law in electrodynamics. Some of the physical implications of gravitational induction are briefly discussed.

Non-linear effects in bunch compressor of TARLA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yildiz, Hüseyin, E-mail: huseyinyildiz006@gmail.com, E-mail: huseyinyildiz@gazi.edu.tr; Aksoy, Avni; Arikan, Pervin

2016-03-25

Transport of a beam through an accelerator beamline is affected by high order and non-linear effects such as space charge, coherent synchrotron radiation, wakefield, etc. These effects damage form of the beam, and they lead particle loss, emittance growth, bunch length variation, beam halo formation, etc. One of the known non-linear effects on low energy machine is space charge effect. In this study we focus on space charge effect for Turkish Accelerator and Radiation Laboratory in Ankara (TARLA) machine which is designed to drive InfraRed Free Electron Laser covering the range of 3-250 µm. Moreover, we discuss second order effects onmore » bunch compressor of TARLA.« less

Study of Various Slanted Air-Gap Structures of Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tolbert, Leon M; Lee, Seong T

2010-01-01

This paper shows how to maximize the effect of the slanted air-gap structure of an interior permanent magnet synchronous motor with brushless field excitation (BFE) for application in a hybrid electric vehicle. The BFE structure offers high torque density at low speed and weakened flux at high speed. The unique slanted air-gap is intended to increase the output torque of the machine as well as to maximize the ratio of the back-emf of a machine that is controllable by BFE. This irregularly shaped air-gap makes a flux barrier along the d-axis flux path and decreases the d-axis inductance; as amore » result, the reluctance torque of the machine is much higher than a uniform air-gap machine, and so is the output torque. Also, the machine achieves a higher ratio of the magnitude of controllable back-emf. The determination of the slanted shape was performed by using magnetic equivalent circuit analysis and finite element analysis (FEA).« less

Comparison of Solid State Inverters for AC Induction Motor Traction Propulsion Systems

DOT National Transportation Integrated Search

1980-12-01

This report is one of a series concerned with the application of ac machines as traction motors for railroad motive power. It presents results of a laboratory evaluation and computer analysis of different inverter systems. Three inverter systems, sin...

Comparaison de méthodes d'identification des paramètres d'une machine asynchrone

NASA Astrophysics Data System (ADS)

Bellaaj-Mrabet, N.; Jelassi, K.

1998-07-01

Interests, in Genetic Algorithms (G.A.) expands rapidly. This paper consists initially to apply G.A. for identifying induction motor parameters. Next, we compare the performances with classical methods like Maximum Likelihood and classical electrotechnical methods. These methods are applied on three induction motors of different powers to compare results following a set of criteria. Les algorithmes génétiques sont des méthodes adaptatives de plus en plus utilisée pour la résolution de certains problèmes d'optimisation. Le présent travail consiste d'une part, à mettre en œuvre un A.G sur des problèmes d'identification des machines électriques, et d'autre part à comparer ses performances avec les méthodes classiques tels que la méthode du maximum de vraisemblance et la méthode électrotechnique basée sur des essais à vides et en court-circuit. Ces méthodes sont appliquées sur des machines asynchrones de différentes puissances. Les résultats obtenus sont comparés selon certains critères, permettant de conclure sur la validité et la performance de chaque méthode.

Stochastic subset selection for learning with kernel machines.

PubMed

Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Chromatic induction from surrounding stimuli under perceptual suppression.

PubMed

Horiuchi, Koji; Kuriki, Ichiro; Tokunaga, Rumi; Matsumiya, Kazumichi; Shioiri, Satoshi

2014-11-01

The appearance of colors can be affected by their spatiotemporal context. The shift in color appearance according to the surrounding colors is called color induction or chromatic induction; in particular, the shift in opponent color of the surround is called chromatic contrast. To investigate whether chromatic induction occurs even when the chromatic surround is imperceptible, we measured chromatic induction during interocular suppression. A multicolor or uniform color field was presented as the surround stimulus, and a colored continuous flash suppression (CFS) stimulus was presented to the dominant eye of each subject. The subjects were asked to report the appearance of the test field only when the stationary surround stimulus is invisible by interocular suppression with CFS. The resulting shifts in color appearance due to chromatic induction were significant even under the conditions of interocular suppression for all surround stimuli. The magnitude of chromatic induction differed with the surround conditions, and this difference was preserved regardless of the viewing conditions. The chromatic induction effect was reduced by CFS, in proportion to the magnitude of chromatic induction under natural (i.e., no-CFS) viewing conditions. According to an analysis with linear model fitting, we revealed the presence of at least two kinds of subprocesses for chromatic induction that reside at higher and lower levels than the site of interocular suppression. One mechanism yields different degrees of chromatic induction based on the complexity of the surround, which is unaffected by interocular suppression, while the other mechanism changes its output with interocular suppression acting as a gain control. Our results imply that the total chromatic induction effect is achieved via a linear summation of outputs from mechanisms that reside at different levels of visual processing.

Optimizing Support Vector Machine Parameters with Genetic Algorithm for Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Manurung, Jonson; Mawengkang, Herman; Zamzami, Elviawaty

2017-12-01

Support vector machine (SVM) is a popular classification method known to have strong generalization capabilities. SVM can solve the problem of classification and linear regression or nonlinear kernel which can be a learning algorithm for the ability of classification and regression. However, SVM also has a weakness that is difficult to determine the optimal parameter value. SVM calculates the best linear separator on the input feature space according to the training data. To classify data which are non-linearly separable, SVM uses kernel tricks to transform the data into a linearly separable data on a higher dimension feature space. The kernel trick using various kinds of kernel functions, such as : linear kernel, polynomial, radial base function (RBF) and sigmoid. Each function has parameters which affect the accuracy of SVM classification. To solve the problem genetic algorithms are proposed to be applied as the optimal parameter value search algorithm thus increasing the best classification accuracy on SVM. Data taken from UCI repository of machine learning database: Australian Credit Approval. The results show that the combination of SVM and genetic algorithms is effective in improving classification accuracy. Genetic algorithms has been shown to be effective in systematically finding optimal kernel parameters for SVM, instead of randomly selected kernel parameters. The best accuracy for data has been upgraded from kernel Linear: 85.12%, polynomial: 81.76%, RBF: 77.22% Sigmoid: 78.70%. However, for bigger data sizes, this method is not practical because it takes a lot of time.

Faraday's first dynamo: A retrospective

NASA Astrophysics Data System (ADS)

Smith, Glenn S.

2013-12-01

In the early 1830s, Michael Faraday performed his seminal experimental research on electromagnetic induction, in which he created the first electric dynamo—a machine for continuously converting rotational mechanical energy into electrical energy. His machine was a conducting disc, rotating between the poles of a permanent magnet, with the voltage/current obtained from brushes contacting the disc. In his first dynamo, the magnetic field was asymmetric with respect to the axis of the disc. This is to be contrasted with some of his later symmetric designs, which are the ones almost invariably discussed in textbooks on electromagnetism. In this paper, a theoretical analysis is developed for Faraday's first dynamo. From this analysis, the eddy currents in the disc and the open-circuit voltage for arbitrary positioning of the brushes are determined. The approximate analysis is verified by comparing theoretical results with measurements made on an experimental recreation of the dynamo. Quantitative results from the analysis are used to elucidate Faraday's qualitative observations, from which he learned so much about electromagnetic induction. For the asymmetric design, the eddy currents in the disc dissipate energy that makes the dynamo inefficient, prohibiting its use as a practical generator of electric power. Faraday's experiments with his first dynamo provided valuable insight into electromagnetic induction, and this insight was quickly used by others to design practical generators.

Correlation of Noise Signature to Pulsed Power Events at the HERMES III Accelerator.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lewis, Barbara; Joseph, Nathan Ryan; Salazar, Juan Diego

2016-11-01

The HERMES III accelerator, which is located at Sandia National Laboratories' Tech Area IV, is the largest pulsed gamma X-ray source in the world. The accelerator is made up of 20 inductive cavities that are charged to 1 MV each by complex pulsed power circuitry. The firing time of the machine components ranges between the microsecond and nanosecond timescales. This results in a variety of electromagnetic frequencies when the accelerator fires. Testing was done to identify the HERMES electromagnetic noise signal and to map it to the various accelerator trigger events. This report will show the measurement methods used tomore » capture the noise spectrum produced from the machine and correlate this noise signature with machine events.« less

PWM Inverter control and the application thereof within electric vehicles

DOEpatents

Geppert, Steven

1982-01-01

An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

EV drivetrain inverter with V/HZ optimization

DOEpatents

Gritter, David J.; O'Neil, Walter K.

1986-01-01

An inverter (34) which provides power to an A.C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A.C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A.C. machine is optimized. The control circuit includes a micro-computer which calculates optimized machine control data signals from various parametric inputs and during steady state load conditions, seeks a best V/HZ ratio to minimize battery current drawn (system losses) from a D.C. power source (32). In the preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack and a three-phase induction motor (18).

SU-F-BRD-16: Relative Biological Effectiveness of Double-Strand Break Induction for Modeling Cell Survival in Pristine Proton Beams of Different Dose-Averaged Linear Energy Transfers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peeler, C; Bronk, L; UT Graduate School of Biomedical Sciences at Houston, Houston, TX

2015-06-15

Purpose: High throughput in vitro experiments assessing cell survival following proton radiation indicate that both the alpha and the beta parameters of the linear quadratic model increase with increasing proton linear energy transfer (LET). We investigated the relative biological effectiveness (RBE) of double-strand break (DSB) induction as a means of explaining the experimental results. Methods: Experiments were performed with two lung cancer cell lines and a range of proton LET values (0.94 – 19.4 keV/µm) using an experimental apparatus designed to irradiate cells in a 96 well plate such that each column encounters protons of different dose-averaged LET (LETd). Traditionalmore » linear quadratic survival curve fitting was performed, and alpha, beta, and RBE values obtained. Survival curves were also fit with a model incorporating RBE of DSB induction as the sole fit parameter. Fitted values of the RBE of DSB induction were then compared to values obtained using Monte Carlo Damage Simulation (MCDS) software and energy spectra calculated with Geant4. Other parameters including alpha, beta, and number of DSBs were compared to those obtained from traditional fitting. Results: Survival curve fitting with RBE of DSB induction yielded alpha and beta parameters that increase with proton LETd, which follows from the standard method of fitting; however, relying on a single fit parameter provided more consistent trends. The fitted values of RBE of DSB induction increased beyond what is predicted from MCDS data above proton LETd of approximately 10 keV/µm. Conclusion: In order to accurately model in vitro proton irradiation experiments performed with high throughput methods, the RBE of DSB induction must increase more rapidly than predicted by MCDS above LETd of 10 keV/µm. This can be explained by considering the increased complexity of DSBs or the nature of intra-track pairwise DSB interactions in this range of LETd values. NIH Grant 2U19CA021239-35.« less

Fast mental states decoding in mixed reality.

PubMed

De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F M J; Birbaumer, Niels; Caria, Andrea

2014-01-01

The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR.

Fast mental states decoding in mixed reality

PubMed Central

De Massari, Daniele; Pacheco, Daniel; Malekshahi, Rahim; Betella, Alberto; Verschure, Paul F. M. J.; Birbaumer, Niels; Caria, Andrea

2014-01-01

The combination of Brain-Computer Interface (BCI) technology, allowing online monitoring and decoding of brain activity, with virtual and mixed reality (MR) systems may help to shape and guide implicit and explicit learning using ecological scenarios. Real-time information of ongoing brain states acquired through BCI might be exploited for controlling data presentation in virtual environments. Brain states discrimination during mixed reality experience is thus critical for adapting specific data features to contingent brain activity. In this study we recorded electroencephalographic (EEG) data while participants experienced MR scenarios implemented through the eXperience Induction Machine (XIM). The XIM is a novel framework modeling the integration of a sensing system that evaluates and measures physiological and psychological states with a number of actuators and effectors that coherently reacts to the user's actions. We then assessed continuous EEG-based discrimination of spatial navigation, reading and calculation performed in MR, using linear discriminant analysis (LDA) and support vector machine (SVM) classifiers. Dynamic single trial classification showed high accuracy of LDA and SVM classifiers in detecting multiple brain states as well as in differentiating between high and low mental workload, using a 5 s time-window shifting every 200 ms. Our results indicate overall better performance of LDA with respect to SVM and suggest applicability of our approach in a BCI-controlled MR scenario. Ultimately, successful prediction of brain states might be used to drive adaptation of data representation in order to boost information processing in MR. PMID:25505878

On the Effects of Training Inductive Reasoning: How Far Does It Transfer and How Long Do the Effects Persist?

ERIC Educational Resources Information Center

Tomic, Welko; Klauer, Karl Josef

1996-01-01

Reports on two training experiments in which it was expected that training in inductive reasoning would transfer to intelligence tests measuring inductive reasoning and on mathematics performance. Shows that transfer on intelligence tests as well as on mathematics performance was linearly dependent on the amount of prior training. (DSK)

The eXperience Induction Machine: A New Paradigm for Mixed-Reality Interaction Design and Psychological Experimentation

NASA Astrophysics Data System (ADS)

Bernardet, Ulysses; Bermúdez I Badia, Sergi; Duff, Armin; Inderbitzin, Martin; Le Groux, Sylvain; Manzolli, Jônatas; Mathews, Zenon; Mura, Anna; Väljamäe, Aleksander; Verschure, Paul F. M. J.

The eXperience Induction Machine (XIM) is one of the most advanced mixed-reality spaces available today. XIM is an immersive space that consists of physical sensors and effectors and which is conceptualized as a general-purpose infrastructure for research in the field of psychology and human-artifact interaction. In this chapter, we set out the epistemological rational behind XIM by putting the installation in the context of psychological research. The design and implementation of XIM are based on principles and technologies of neuromorphic control. We give a detailed description of the hardware infrastructure and software architecture, including the logic of the overall behavioral control. To illustrate the approach toward psychological experimentation, we discuss a number of practical applications of XIM. These include the so-called, persistent virtual community, the application in the research of the relationship between human experience and multi-modal stimulation, and an investigation of a mixed-reality social interaction paradigm.

Universal Parameter Measurement and Sensorless Vector Control of Induction and Permanent Magnet Synchronous Motors

NASA Astrophysics Data System (ADS)

Yamamoto, Shu; Ara, Takahiro

Recently, induction motors (IMs) and permanent-magnet synchronous motors (PMSMs) have been used in various industrial drive systems. The features of the hardware device used for controlling the adjustable-speed drive in these motors are almost identical. Despite this, different techniques are generally used for parameter measurement and speed-sensorless control of these motors. If the same technique can be used for parameter measurement and sensorless control, a highly versatile adjustable-speed-drive system can be realized. In this paper, the authors describe a new universal sensorless control technique for both IMs and PMSMs (including salient pole and nonsalient pole machines). A mathematical model applicable for IMs and PMSMs is discussed. Using this model, the authors derive the proposed universal sensorless vector control algorithm on the basis of estimation of the stator flux linkage vector. All the electrical motor parameters are determined by a unified test procedure. The proposed method is implemented on three test machines. The actual driving test results demonstrate the validity of the proposed method.

A Hybrid Method for Opinion Finding Task (KUNLP at TREC 2008 Blog Track)

DTIC Science & Technology

2008-11-01

retrieve relevant documents. For the Opinion Retrieval subtask, we propose a hybrid model of lexicon-based approach and machine learning approach for...estimating and ranking the opinionated documents. For the Polarized Opinion Retrieval subtask, we employ machine learning for predicting the polarity...and linear combination technique for ranking polar documents. The hybrid model which utilize both lexicon-based approach and machine learning approach

Teaching Machines, Programming, Computers, and Instructional Technology: The Roots of Performance Technology.

ERIC Educational Resources Information Center

Deutsch, William

1992-01-01

Reviews the history of the development of the field of performance technology. Highlights include early teaching machines, instructional technology, learning theory, programed instruction, the systems approach, needs assessment, branching versus linear program formats, programing languages, and computer-assisted instruction. (LRW)

Taxi-Out Time Prediction for Departures at Charlotte Airport Using Machine Learning Techniques

NASA Technical Reports Server (NTRS)

Lee, Hanbong; Malik, Waqar; Jung, Yoon C.

2016-01-01

Predicting the taxi-out times of departures accurately is important for improving airport efficiency and takeoff time predictability. In this paper, we attempt to apply machine learning techniques to actual traffic data at Charlotte Douglas International Airport for taxi-out time prediction. To find the key factors affecting aircraft taxi times, surface surveillance data is first analyzed. From this data analysis, several variables, including terminal concourse, spot, runway, departure fix and weight class, are selected for taxi time prediction. Then, various machine learning methods such as linear regression, support vector machines, k-nearest neighbors, random forest, and neural networks model are applied to actual flight data. Different traffic flow and weather conditions at Charlotte airport are also taken into account for more accurate prediction. The taxi-out time prediction results show that linear regression and random forest techniques can provide the most accurate prediction in terms of root-mean-square errors. We also discuss the operational complexity and uncertainties that make it difficult to predict the taxi times accurately.

Analysis of laser-induction hybrid cladding processing conditions

NASA Astrophysics Data System (ADS)

Huang, Yongjun; Zeng, Xiaoyan; Hu, Qianwu

2007-12-01

A new cladding approach based on laser-induction hybrid technique on flat sheets is presented in this paper. Coating is produced by means of 5kw cw CO II laser equipped with 100kw high frequent inductor, and the experiments set-up, involving a special machining-head, which can provide laser-induction hybrid heat resources simultaneously. The formation of thick NiCrSiB coating on a steel substrate by off-axial powder feeding is studied from an experimental point of view. A substrate melting energy model is developed to describe the energy relationship between laser-induction hybrid cladding and laser cladding alone quantitatively. By comparing the experimental results with the calculational ones, it is shown that the tendency of fusion zone height of theoretical calculation is in agreement with that of tests in laser-induction hybrid cladding. Via analyses and tests, the conclusions can be lead to that the fusion zone height can be increased easily and the good bond of cladding track can be achieved within wide cladding processing window in laser-induction hybrid processing. It shows that the induction heating has an obvious effect on substrate melting and metallurgical bond.

Preliminary results of Linear Induction Accelerator LIA-200

NASA Astrophysics Data System (ADS)

Sharma, Archana; Senthil, K.; Praveen Kumar, D. D.; Mitra, S.; Sharma, V.; Patel, A.; Sharma, D. K.; Rehim, R.; Kolge, T. S.; Saroj, P. C.; Acharya, S.; Amitava, Roy; Rakhee, M.; Nagesh, K. V.; Chakravarthy, D. P.

2010-05-01

Repetitive Pulsed Power Technology is being developed keeping in mind the potential applications of this technology in material modifications, disinfections of water, timber, and food pasteurization etc. BARC has indigenously developed a Linear Induction Accelerator (LIA-200) rated for 200 kV, 4 kA, 100 ns, 10 Hz. The satisfactory performance of all the sub-systems including solid state power modulator, amorphous core based pulsed transformers, magnetic switches, water capacitors, water pulse- forming line, induction adder and field-emission diode have been demonstrated. This paper presents some design details and operational results of this pulsed power system. It also highlights the need for further research and development to build reliable and economic high-average power systems for industrial applications.

Bending Distortion Analysis of a Steel Shaft Manufacturing Chain from Cold Drawing to Grinding

NASA Astrophysics Data System (ADS)

Dias, Vinicius Waechter; da Silva Rocha, Alexandre; Zottis, Juliana; Dong, Juan; Epp, Jérémy; Zoch, Hans Werner

2017-04-01

Shafts are usually manufactured from bars that are cold drawn, cut machined, induction hardened, straightened, and finally ground. The main distortion is characterized by bending that appears after induction hardening and is corrected by straightening and/or grinding. In this work, the consequence of the variation of manufacturing parameters on the distortion was analyzed for a complete manufacturing route for production of induction hardened shafts made of Grade 1045 steel. A DoE plan was implemented varying the drawing angle, cutting method, induction hardening layer depth, and grinding penetration depth. The distortion was determined by calculating curvature vectors from dimensional analysis by 3D coordinate measurements. Optical microscopy, microhardness testing, residual stress analysis, and FEM process simulation were used to evaluate and understand effects of the main carriers of distortion potential. The drawing process was identified as the most significant influence on the final distortion of the shafts.

Submicrosecond linear pulse transformer for 800 kV voltage with modular low-inductance primary power supply

NASA Astrophysics Data System (ADS)

Bykov, Yu. A.; Krastelev, E. G.; Popov, G. V.; Sedin, A. A.; Feduschak, V. F.

2016-12-01

A pulsed power source with voltage amplitude up to 800 kV for fast charging (350-400 ns) of the forming line of a high-current nanosecond accelerator is developed. The source includes capacitive energy storage and a linear pulse transformer. The linear transformer consists of a set of 20 inductors with circular ferromagnetic cores surrounded by primary windings inside of which a common stock adder of voltage with film-glycerol insulation is placed. The primary energy storage consists of ten modules, each of which is a low-inductance assembly of two capacitors with a capacitance of 0.35 μF and one gas switch mounted in the same frame. The total energy stored in capacitors is 5.5 kJ at the operating voltage of 40 kV. According to test results, the parameters of the equivalent circuit of the source are the following: shock capacitance = 17.5 nF, inductance = 2 μH, resistance = 3.2 Ω.

Linear transformer and primary low-inductance switch and capacitor modules for fast charging of PFL

NASA Astrophysics Data System (ADS)

Bykov, Yu A.; Krastelev, E. G.; Popov, G. V.; Sedin, A. A.; Feduschak, V. F.

2017-05-01

A step-up linear pulse transformer and a modular primary powering system were developed for fast (≈350 ns) charging of a pulse forming line (PFL) of a high-current electron accelerator. The linear transformer is assembled of a set of 20 inductors with circular ferromagnetic cores and one-turn primary windings. The secondary turn is formed by housing tube walls and a voltage adder with a film-glycerol insulation installed inside of the inductors. The primary powering system assembles 10 modules, each of them is a low-inductance site of two capacitors of 0,35 µF and one gas switch mounted at the same enclosure. The total stored energy is 5.5 kJ at the charging voltage of 40 kV. According to test results, the equivalent parameters at the output of the transformer are the next: a capacity - 17.5 nF, an inductance - 2 µH, a resistance - 3.2 Ohms.

Submicrosecond linear pulse transformer for 800 kV voltage with modular low-inductance primary power supply

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bykov, Yu. A.; Krastelev, E. G., E-mail: ekrastelev@yandex.ru; Popov, G. V.

A pulsed power source with voltage amplitude up to 800 kV for fast charging (350–400 ns) of the forming line of a high-current nanosecond accelerator is developed. The source includes capacitive energy storage and a linear pulse transformer. The linear transformer consists of a set of 20 inductors with circular ferromagnetic cores surrounded by primary windings inside of which a common stock adder of voltage with film-glycerol insulation is placed. The primary energy storage consists of ten modules, each of which is a low-inductance assembly of two capacitors with a capacitance of 0.35 μF and one gas switch mounted inmore » the same frame. The total energy stored in capacitors is 5.5 kJ at the operating voltage of 40 kV. According to test results, the parameters of the equivalent circuit of the source are the following: shock capacitance = 17.5 nF, inductance = 2 μH, resistance = 3.2 Ω.« less

Fuzzy Logic Controlled Solar Module for Driving Three- Phase Induction Motor

NASA Astrophysics Data System (ADS)

Afiqah Zainal, Nurul; Sooi Tat, Chan; Ajisman

2016-02-01

Renewable energy produced by solar module gives advantages for generated three- phase induction motor in remote area. But, solar module's ou tput is uncertain and complex. Fuzzy logic controller is one of controllers that can handle non-linear system and maximum power of solar module. Fuzzy logic controller used for Maximum Power Point Tracking (MPPT) technique to control Pulse-Width Modulation (PWM) for switching power electronics circuit. DC-DC boost converter used to boost up photovoltaic voltage to desired output and supply voltage source inverter which controlled by three-phase PWM generated by microcontroller. IGBT switched Voltage source inverter (VSI) produced alternating current (AC) voltage from direct current (DC) source to control speed of three-phase induction motor from boost converter output. Results showed that, the output power of solar module is optimized and controlled by using fuzzy logic controller. Besides that, the three-phase induction motor can be drive and control using VSI switching by the PWM signal generated by the fuzzy logic controller. This concluded that the non-linear system can be controlled and used in driving three-phase induction motor.

Development of a linear induction motor based artificial muscle system.

PubMed

Gruber, A; Arguello, E; Silva, R

2013-01-01

We present the design of a linear induction motor based on electromagnetic interactions. The engine is capable of producing a linear movement from electricity. The design consists of stators arranged in parallel, which produce a magnetic field sufficient to displace a plunger along its axial axis. Furthermore, the winding has a shell and cap of ferromagnetic material that amplifies the magnetic field. This produces a force along the length of the motor that is similar to that of skeletal muscle. In principle, the objective is to use the engine in the development of an artificial muscle system for prosthetic applications, but it could have multiple applications, not only in the medical field, but in other industries.

Theory-Based Causal Induction

ERIC Educational Resources Information Center

Griffiths, Thomas L.; Tenenbaum, Joshua B.

2009-01-01

Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various settings, from diverse forms of data: observations…

USSR Report, Electronics and Electrical Engineering, No. 104

DTIC Science & Technology

1983-06-13

shaping of silicon crystals during their growth is a modification of inductive contactless forming of rods and tubes directly from the melt on a...MANUFACTURING TECHNOLOGY Induction Systems for Electromagnetic Shaping of Silicon Crystal During.Growth (L. R. Lev; ELEKTROTEKHNIKA, Feb 83) • • • x...et al.; IZVESTIYA VYSSHIKH UCHEBNYKH ZAVEDENIY: ELEKTROMEKHANIKA, Dec 82) 18 Basic Design of Linear- Induction Traction Motors for High-Speed

Solid-state resistor for pulsed power machines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoltzfus, Brian; Savage, Mark E.; Hutsel, Brian Thomas

2016-12-06

A flexible solid-state resistor comprises a string of ceramic resistors that can be used to charge the capacitors of a linear transformer driver (LTD) used in a pulsed power machine. The solid-state resistor is able to absorb the energy of a switch prefire, thereby limiting LTD cavity damage, yet has a sufficiently low RC charge time to allow the capacitor to be recharged without disrupting the operation of the pulsed power machine.

Source localization in an ocean waveguide using supervised machine learning.

PubMed

Niu, Haiqiang; Reeves, Emma; Gerstoft, Peter

2017-09-01

Source localization in ocean acoustics is posed as a machine learning problem in which data-driven methods learn source ranges directly from observed acoustic data. The pressure received by a vertical linear array is preprocessed by constructing a normalized sample covariance matrix and used as the input for three machine learning methods: feed-forward neural networks (FNN), support vector machines (SVM), and random forests (RF). The range estimation problem is solved both as a classification problem and as a regression problem by these three machine learning algorithms. The results of range estimation for the Noise09 experiment are compared for FNN, SVM, RF, and conventional matched-field processing and demonstrate the potential of machine learning for underwater source localization.

Applying spectral unmixing and support vector machine to airborne hyperspectral imagery for detecting giant reed

USDA-ARS?s Scientific Manuscript database

This study evaluated linear spectral unmixing (LSU), mixture tuned matched filtering (MTMF) and support vector machine (SVM) techniques for detecting and mapping giant reed (Arundo donax L.), an invasive weed that presents a severe threat to agroecosystems and riparian areas throughout the southern ...

Teaching Machines and Programmed Instruction.

ERIC Educational Resources Information Center

Kay, Harry; And Others

The various devices used in programed instruction range from the simple linear programed book to branching and skip branching programs, adaptive teaching machines, and even complex computer based systems. In order to provide a background for the would-be programer, the essential principles of each of these devices is outlined. Different ideas of…

Linear- and Repetitive Feature Detection Within Remotely Sensed Imagery

DTIC Science & Technology

2017-04-01

applicable to Python or other pro- gramming languages with image- processing capabilities. 4.1 Classification machine learning The first methodology uses...remotely sensed images that are in panchromatic or true-color formats. Image- processing techniques, in- cluding Hough transforms, machine learning, and...data fusion .................................................................................................... 44 6.3 Context-based processing

Diagnosis of the three-phase induction motor using thermal imaging

NASA Astrophysics Data System (ADS)

Glowacz, Adam; Glowacz, Zygfryd

2017-03-01

Three-phase induction motors are used in the industry commonly for example woodworking machines, blowers, pumps, conveyors, elevators, compressors, mining industry, automotive industry, chemical industry and railway applications. Diagnosis of faults is essential for proper maintenance. Faults may damage a motor and damaged motors generate economic losses caused by breakdowns in production lines. In this paper the authors develop fault diagnostic techniques of the three-phase induction motor. The described techniques are based on the analysis of thermal images of three-phase induction motor. The authors analyse thermal images of 3 states of the three-phase induction motor: healthy three-phase induction motor, three-phase induction motor with 2 broken bars, three-phase induction motor with faulty ring of squirrel-cage. In this paper the authors develop an original method of the feature extraction of thermal images MoASoID (Method of Areas Selection of Image Differences). This method compares many training sets together and it selects the areas with the biggest changes for the recognition process. Feature vectors are obtained with the use of mentioned MoASoID and image histogram. Next 3 methods of classification are used: NN (the Nearest Neighbour classifier), K-means, BNN (the back-propagation neural network). The described fault diagnostic techniques are useful for protection of three-phase induction motor and other types of rotating electrical motors such as: DC motors, generators, synchronous motors.

A study of normoxic polymer gel using monomer 2-hydroxyethyl methacrylate (HEMA)

NASA Astrophysics Data System (ADS)

Ishak, Siti Atiqah; Mustafa, Iskandar Shahrim; Rahman, Azhar Abdul; Moktar, Mohd; Min, Ung Ngie

2015-04-01

The aim of this study is to determine the sensitivity of HEMA-polymer gel mixture consist of monomer 2-hydroxyethyl methacrylate (HEMA) with different types of composition. Several composition of HEMA-polymer gel were fabricated and the gels were irradiated with radiation dose between 10 cGy to 100cGy by using x-ray machine and 100 cGy to 1400 cGy by using 6 MV photon beam energy of linear accelerator. The degree of polymerization was evaluated by using magnetic resonance imaging (MRI) with dependence of R2-dose response. Polymer gel consists of cross-linker, anti-oxidant Tetrakis(Hydroxymethyl)phosphonium chloride solution (THPC) and oxygen scavenger hydroquinone shows a stable sensitivity with highest dose dependency. Besides, the results shows the stage polymerization consist of induction, propagation, termination, and chain transfer were dependence with type of chemical mixture and radiation dose. Thus, normoxic HEMA-polymer gel with the different gel formulations can have a better dose resolution and an appropriate recipe must be selected to increase of the sensitivity required and the stability of the dosimeter.

A study of normoxic polymer gel using monomer 2-hydroxyethyl methacrylate (HEMA)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ishak, Siti Atiqah; Mustafa, Iskandar Shahrim; Rahman, Azhar Abdul

2015-04-24

The aim of this study is to determine the sensitivity of HEMA-polymer gel mixture consist of monomer 2-hydroxyethyl methacrylate (HEMA) with different types of composition. Several composition of HEMA-polymer gel were fabricated and the gels were irradiated with radiation dose between 10 cGy to 100cGy by using x-ray machine and 100 cGy to 1400 cGy by using 6 MV photon beam energy of linear accelerator. The degree of polymerization was evaluated by using magnetic resonance imaging (MRI) with dependence of R2-dose response. Polymer gel consists of cross-linker, anti-oxidant Tetrakis(Hydroxymethyl)phosphonium chloride solution (THPC) and oxygen scavenger hydroquinone shows a stable sensitivitymore » with highest dose dependency. Besides, the results shows the stage polymerization consist of induction, propagation, termination, and chain transfer were dependence with type of chemical mixture and radiation dose. Thus, normoxic HEMA-polymer gel with the different gel formulations can have a better dose resolution and an appropriate recipe must be selected to increase of the sensitivity required and the stability of the dosimeter.« less

EEG Responses to Auditory Stimuli for Automatic Affect Recognition

PubMed Central

Hettich, Dirk T.; Bolinger, Elaina; Matuz, Tamara; Birbaumer, Niels; Rosenstiel, Wolfgang; Spüler, Martin

2016-01-01

Brain state classification for communication and control has been well established in the area of brain-computer interfaces over the last decades. Recently, the passive and automatic extraction of additional information regarding the psychological state of users from neurophysiological signals has gained increased attention in the interdisciplinary field of affective computing. We investigated how well specific emotional reactions, induced by auditory stimuli, can be detected in EEG recordings. We introduce an auditory emotion induction paradigm based on the International Affective Digitized Sounds 2nd Edition (IADS-2) database also suitable for disabled individuals. Stimuli are grouped in three valence categories: unpleasant, neutral, and pleasant. Significant differences in time domain domain event-related potentials are found in the electroencephalogram (EEG) between unpleasant and neutral, as well as pleasant and neutral conditions over midline electrodes. Time domain data were classified in three binary classification problems using a linear support vector machine (SVM) classifier. We discuss three classification performance measures in the context of affective computing and outline some strategies for conducting and reporting affect classification studies. PMID:27375410

FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

EPA Science Inventory

The paper describes a variable-speed wind generation system where fuzzy logic principles are used to optimize efficiency and enhance performance control. A squirrel cage induction generator feeds the power to a double-sided pulse width modulated converter system which either pump...

FUZZY LOGIC BASED INTELLIGENT CONTROL OF A VARIABLE SPEED CAGE MACHINE WIND GENERATION SYSTEM

EPA Science Inventory

The report gives results of a demonstration of the successful application of fuzzy logic to enhance the performance and control of a variable-speed wind generation system. A squirrel cage induction generator feeds the power to either a double-sided pulse-width modulation converte...

Incremental Inductive Learning in a Constructivist Agent

NASA Astrophysics Data System (ADS)

Perotto, Filipo Studzinski; Älvares, Luís Otávio

The constructivist paradigm in Artificial Intelligence has been definitively inaugurated in the earlier 1990's by Drescher's pioneer work [10]. He faces the challenge of design an alternative model for machine learning, founded in the human cognitive developmental process described by Piaget [x]. His effort has inspired many other researchers.

Methods of Cost Reduction for United States Coast Guard Telephone Systems.

DTIC Science & Technology

1981-03-01

System (’FTS) for a single low utilization command is questionable. Small FAX machines such as EXXON’s QWIP /FAX can be purchased at approxi- mately...unsatisfactory operating condi- tion. Electrical faults, such as leakage or poor insulation, noise induction, crosstalk, or poor transmission

NASTRAN buckling study of a linear induction motor reaction rail

NASA Technical Reports Server (NTRS)

Williams, J. G.

1973-01-01

NASTRAN was used to study problems associated with the installation of a linear induction motor reaction rail test track. Specific problems studied include determination of the critical axial compressive buckling stress and establishment of the lateral stiffness of the reaction rail under combined loads. NASTRAN results were compared with experimentally obtained values and satisfactory agreement was obtained. The reaction rail was found to buckle at an axial compressive stress of 11,400 pounds per square inch. The results of this investigation were used to select procedures for installation of the reaction rail.

Stable Spheromaks with Profile Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fowler, T K; Jayakumar, R

A spheromak equilibrium with zero edge current is shown to be stable to both ideal MHD and tearing modes that normally produce Taylor relaxation in gun-injected spheromaks. This stable equilibrium differs from the stable Taylor state in that the current density j falls to zero at the wall. Estimates indicate that this current profile could be sustained by non-inductive current drive at acceptable power levels. Stability is determined using the NIMROD code for linear stability analysis. Non-linear NIMROD calculations with non-inductive current drive could point the way to improved fusion reactors.

Comparison of linear synchronous and induction motors

DOT National Transportation Integrated Search

2004-06-01

A propulsion prade study was conducted as part of the Colorado Maglev Project of FTA's Urban Maglev Technology Development Program to identify and evaluate prospective linear motor designs that could potentially meet the system performance requiremen...

Optical realization of optimal symmetric real state quantum cloning machine

NASA Astrophysics Data System (ADS)

Hu, Gui-Yu; Zhang, Wen-Hai; Ye, Liu

2010-01-01

We present an experimentally uniform linear optical scheme to implement the optimal 1→2 symmetric and optimal 1→3 symmetric economical real state quantum cloning machine of the polarization state of the single photon. This scheme requires single-photon sources and two-photon polarization entangled state as input states. It also involves linear optical elements and three-photon coincidence. Then we consider the realistic realization of the scheme by using the parametric down-conversion as photon resources. It is shown that under certain condition, the scheme is feasible by current experimental technology.

Estimation of perceptible water vapor of atmosphere using artificial neural network, support vector machine and multiple linear regression algorithm and their comparative study

NASA Astrophysics Data System (ADS)

Shastri, Niket; Pathak, Kamlesh

2018-05-01

The water vapor content in atmosphere plays very important role in climate. In this paper the application of GPS signal in meteorology is discussed, which is useful technique that is used to estimate the perceptible water vapor of atmosphere. In this paper various algorithms like artificial neural network, support vector machine and multiple linear regression are use to predict perceptible water vapor. The comparative studies in terms of root mean square error and mean absolute errors are also carried out for all the algorithms.

A Tightly Coupled Non-Equilibrium Magneto-Hydrodynamic Model for Inductively Coupled RF Plasmas

DTIC Science & Technology

2016-02-29

development a tightly coupled magneto-hydrodynamic model for Inductively Coupled Radio- Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE...for Inductively Coupled Radio-Frequency (RF) Plasmas. Non Local Thermodynamic Equilibrium (NLTE) effects are described based on a hybrid State-to-State... thermodynamic variable. This choice allows one to hide the non-linearity of the gas (total) thermal conductivity κ and can partially alle- 2 viate numerical

Management Perspectives Pertaining to Root Cause Analyses of Nunn-McCurdy Breaches. Volume 4

DTIC Science & Technology

2013-01-01

the FY2012 NDAA, the Army revised its initial budget request, allocating money from the purchase of new M2 .50 caliber machine guns to the...Quick-change machine gun barrel Explosive reactive armor Linear demolition charge system Full width, surface mine ploughs On-board vehicle power...Quantity Oversight of ACAT II Programs 45 for a restart to the program citing a “critical shortage of serviceable machine guns for our Soldiers who

The effect of sample size and disease prevalence on supervised machine learning of narrative data.

PubMed Central

McKnight, Lawrence K.; Wilcox, Adam; Hripcsak, George

2002-01-01

This paper examines the independent effects of outcome prevalence and training sample sizes on inductive learning performance. We trained 3 inductive learning algorithms (MC4, IB, and Naïve-Bayes) on 60 simulated datasets of parsed radiology text reports labeled with 6 disease states. Data sets were constructed to define positive outcome states at 4 prevalence rates (1, 5, 10, 25, and 50%) in training set sizes of 200 and 2,000 cases. We found that the effect of outcome prevalence is significant when outcome classes drop below 10% of cases. The effect appeared independent of sample size, induction algorithm used, or class label. Work is needed to identify methods of improving classifier performance when output classes are rare. PMID:12463878

A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment

NASA Astrophysics Data System (ADS)

Liu, Jingli; Li, Jianping; Xu, Weixuan; Shi, Yong

Least squares support vector machine (LS-SVM) is a revised version of support vector machine (SVM) and has been proved to be a useful tool for pattern recognition. LS-SVM had excellent generalization performance and low computational cost. In this paper, we propose a new method called two-layer least squares support vector machine which combines kernel principle component analysis (KPCA) and linear programming form of least square support vector machine. With this method sparseness and robustness is obtained while solving large dimensional and large scale database. A U.S. commercial credit card database is used to test the efficiency of our method and the result proved to be a satisfactory one.

Automatic inference of multicellular regulatory networks using informative priors.

PubMed

Sun, Xiaoyun; Hong, Pengyu

2009-01-01

To fully understand the mechanisms governing animal development, computational models and algorithms are needed to enable quantitative studies of the underlying regulatory networks. We developed a mathematical model based on dynamic Bayesian networks to model multicellular regulatory networks that govern cell differentiation processes. A machine-learning method was developed to automatically infer such a model from heterogeneous data. We show that the model inference procedure can be greatly improved by incorporating interaction data across species. The proposed approach was applied to C. elegans vulval induction to reconstruct a model capable of simulating C. elegans vulval induction under 73 different genetic conditions.

Electric motor-transformer aggregate in hermetic objects of transport vehicles

NASA Astrophysics Data System (ADS)

Zabora, Igor

2017-10-01

The construction and features of operation for new electrical unit - electric motor-transformer aggregate (DTA) are considered. Induction motors are intended for operation in hermetic plants with extreme conditions surrounding gas, steam-to-gas and liquid environment at a high temperature (to several hundred of degrees). Main objective of spent researches is the substantiation of possibility reliable and effective electric power transform with electric machine means directly in hermetic objects with extreme conditions environment by means of new DTA. The principle and job analysis of new disk induction motors of block-module type are observed.

Inductive Linear-Position Sensor/Limit-Sensor Units

NASA Technical Reports Server (NTRS)

Alhom, Dean; Howard, David; Smith, Dennis; Dutton, Kenneth

2007-01-01

A new sensor provides an absolute position measurement. A schematic view of a motorized linear-translation stage that contains, at each end, an electronic unit that functions as both (1) a non-contact sensor that measures the absolute position of the stage and (2) a non-contact equivalent of a limit switch that is tripped when the stage reaches the nominal limit position. The need for such an absolute linear position-sensor/limit-sensor unit arises in the case of a linear-translation stage that is part of a larger system in which the actual stopping position of the stage (relative to the nominal limit position) must be known. Because inertia inevitably causes the stage to run somewhat past the nominal limit position, tripping of a standard limit switch or other limit sensor does not provide the required indication of the actual stopping position. This innovative sensor unit operates on an electromagnetic-induction principle similar to that of linear variable differential transformers (LVDTs)

Studies on Muon Induction Acceleration and an Objective Lens Design for Transmission Muon Microscope

NASA Astrophysics Data System (ADS)

Artikova, Sayyora; Yoshida, Mitsuhiro; Naito, Fujio

Muon acceleration will be accomplished by a set of induction cells, where each increases the energy of the muon beam by an increment of up to 30 kV. The cells are arranged in a linear way resulting in total accelerating voltage of 300 kV. Acceleration time in the linac is about hundred nanoseconds. Induction field calculation is based on an electrostatic approximation. Beam dynamics in the induction accelerator is investigated and final beam focusing on specimen is realized by designing a pole piece lens.

Application de la methode de la reponse frequentielle a l'arret "SSFR", sur une machine synchrone a poles saillants de grande puissance

NASA Astrophysics Data System (ADS)

Belqorchi, Abdelghafour

Forty years after Watson and Manchur conducted the Stand-Still Frequency Response (SSFR) test on a large turbogenerator, the applicability of this technic on a powerful salient pole synchronous generator has yet to be confirmed. The scientific literature on the subject is rare and very few have attempted to compare SSFR parameter results with those deduced by classical tests. The validity of SSFR on large salient pole machines has still to be proven. The present work aims in participating to fill this knowledge gap. It can be used to build a database of measurements highly needed to draw the validity of the technic. Also, the author hopes to demonstrate the potential of SSFR model to represent the machine, not only in cases of weak disturbances but also strong ones such as instantaneous three-phase short-circuit faults. The difficulties raised by previous searchers are: The lack of accuracy in very low frequency measurements; The difficulty in rotor positioning, according to d and q axes, in case of salient pole machines; The measurement current level influence on magnetizing inductances, in axes-d and; The rotation impact on damper circuits for some rotors design. Aware of the above difficulties, the author conducted an SSFR test on a large salient pole machine (285 MVA). The generator under test has laminated non isolated rotor and an integral slot number. The damper windings in adjacent poles are connected together, via the polar core and the rotor rim. Finally, the damping circuit is unaffected by rotation. To improve the measurement accuracy, in very low frequencies, the most precise frequency response analyser available on the market was used. Besides, the frequency responses of the signals conditioning modules (i.e., isolation, amplification...) were accounted for to correct the four measured SSFR transfer functions. Immunization against noise and use of instrumentation in their optimum range, were other technics rigorously applied. Magnetizing inductances, being influenced by the measurement current magnitude, the latter was maintained constant in the range 1mHz-20Hz. Other problems such as the rotation impact on damper circuits or the difficulty of rotor positioning are eliminated or attenuated by the intrinsic characteristics of the machine. Regarding the data analysis, the Maximum Likelihood Estimation (MLE) method was used to determine the third and second order equivalent circuit from SSFR measurements. In d-axis, the approaches of adjustment to two and three transfer functions (Ld(s), sG(s) and Lafo(s)) were explored. The second order model, derived from (Ld( s) and G(s)), was used to deduce the machine standard parameters. The latter were compared with the values given by the manufacturer and by conventional on-site tests: Instantaneous three-phase short-circuit, Dalton-Cameron and the d-axis transient time constant at open stator (T'do). The comparison showed the good accuracy of SSFR values. Subsequently, a machine model was built in EMTP-RV based on SSFR standard parameters. The model was able to reproduce stator and rotor currents measured during instantaneous three-phase short-circuit test. Some adjustments, to SSFR parameters, were needed to reproduce stator voltage and rotor current acquired during load rejection d-axis test. It is worthwhile noting that the load rejection d-axis test, recently added to IEEE 115-2009 annex, must be modified to take into account the saturation and excitation impedance impact on deduced parameters. Regarding this issue, some suggestions are proposed by the author. The obtained SSFR results, contribute to raise confidence on SSFR application on large salient pole machines. In addition, it shows the aptitude of the SSFR model to represent the machine in both cases of weak and strong disturbances, at least on machines similar the one studied. Index Terms: Salient pole, frequency response, SSFR, equivalent circuit, operational inductance.

A linear induction motor with a coated conductor superconducting secondary

NASA Astrophysics Data System (ADS)

Chen, Xin; Zheng, Shijun; Li, Jing; Ma, Guang Tong; Yen, Fei

2018-07-01

A linear induction motor system composed of a high-Tc superconducting secondary with close-ended coils made of REBCO coated conductor wire was designed and tested experimentally. The measured thrust, normal force and power loss are presented and explained by combining the flux dynamics inside superconductors with existing linear drive theory. It is found that an inherent capacitive component associated to the flux motion of vortices in the Type-II superconductor reduces the impedance of the coils; from such, the associated Lorentz forces are drastically increased. The resulting breakout thrust of the designed linear motor system was found to be extremely high (up to 4.7 kN/m2) while the associated normal forces only a fraction of the thrust. Compared to its conventional counterparts, high-Tc superconducting secondaries appear to be more feasible for use in maglev propulsion and electromagnetic launchers.

Development of a Low Inductance Linear Alternator for Stirling Power Convertors

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper, eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations, and compares the predictions with experimental data for one of the configurations that has been built and is currently being tested.

Development of a Low-Inductance Linear Alternator for Stirling Power Convertors

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high-efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-the-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations. Additionally, one of the configurations was built and tested at GRC, and the experimental data is compared with the predictions.

Gesture-controlled interfaces for self-service machines and other applications

NASA Technical Reports Server (NTRS)

Cohen, Charles J. (Inventor); Jacobus, Charles J. (Inventor); Paul, George (Inventor); Beach, Glenn (Inventor); Foulk, Gene (Inventor); Obermark, Jay (Inventor); Cavell, Brook (Inventor)

2004-01-01

A gesture recognition interface for use in controlling self-service machines and other devices is disclosed. A gesture is defined as motions and kinematic poses generated by humans, animals, or machines. Specific body features are tracked, and static and motion gestures are interpreted. Motion gestures are defined as a family of parametrically delimited oscillatory motions, modeled as a linear-in-parameters dynamic system with added geometric constraints to allow for real-time recognition using a small amount of memory and processing time. A linear least squares method is preferably used to determine the parameters which represent each gesture. Feature position measure is used in conjunction with a bank of predictor bins seeded with the gesture parameters, and the system determines which bin best fits the observed motion. Recognizing static pose gestures is preferably performed by localizing the body/object from the rest of the image, describing that object, and identifying that description. The disclosure details methods for gesture recognition, as well as the overall architecture for using gesture recognition to control of devices, including self-service machines.

Comparing statistical and machine learning classifiers: alternatives for predictive modeling in human factors research.

PubMed

Carnahan, Brian; Meyer, Gérard; Kuntz, Lois-Ann

2003-01-01

Multivariate classification models play an increasingly important role in human factors research. In the past, these models have been based primarily on discriminant analysis and logistic regression. Models developed from machine learning research offer the human factors professional a viable alternative to these traditional statistical classification methods. To illustrate this point, two machine learning approaches--genetic programming and decision tree induction--were used to construct classification models designed to predict whether or not a student truck driver would pass his or her commercial driver license (CDL) examination. The models were developed and validated using the curriculum scores and CDL exam performances of 37 student truck drivers who had completed a 320-hr driver training course. Results indicated that the machine learning classification models were superior to discriminant analysis and logistic regression in terms of predictive accuracy. Actual or potential applications of this research include the creation of models that more accurately predict human performance outcomes.

Base drive and overlap protection circuit

DOEpatents

Gritter, David J.

1983-01-01

An inverter (34) which provides power to an A. C. machine (28) is controlled by a circuit (36) employing PWM control strategy whereby A. C. power is supplied to the machine at a preselectable frequency and preselectable voltage. This is accomplished by the technique of waveform notching in which the shapes of the notches are varied to determine the average energy content of the overall waveform. Through this arrangement, the operational efficiency of the A. C. machine is optimized. The control circuit includes a microcomputer and memory element which receive various parametric inputs and calculate optimized machine control data signals therefrom. The control data is asynchronously loaded into the inverter through an intermediate buffer (38). A base drive and overlap protection circuit is included to insure that both transistors of a complimentary pair are not conducting at the same time. In its preferred embodiment, the present invention is incorporated within an electric vehicle (10) employing a 144 VDC battery pack (32) and a three-phase induction motor (18).

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Transducer-actuator systems and methods for performing on-machine measurements and automatic part alignment

DOEpatents

Barkman, William E.; Dow, Thomas A.; Garrard, Kenneth P.; Marston, Zachary

2016-07-12

Systems and methods for performing on-machine measurements and automatic part alignment, including: a measurement component operable for determining the position of a part on a machine; and an actuation component operable for adjusting the position of the part by contacting the part with a predetermined force responsive to the determined position of the part. The measurement component consists of a transducer. The actuation component consists of a linear actuator. Optionally, the measurement component and the actuation component consist of a single linear actuator operable for contacting the part with a first lighter force for determining the position of the part and with a second harder force for adjusting the position of the part. The actuation component is utilized in a substantially horizontal configuration and the effects of gravitational drop of the part are accounted for in the force applied and the timing of the contact.

Reactive power compensating system

DOEpatents

Williams, Timothy J.; El-Sharkawi, Mohamed A.; Venkata, Subrahmanyam S.

1987-01-01

The reactive power of an induction machine is compensated by providing fixed capacitors on each phase line for the minimum compensation required, sensing the current on one line at the time its voltage crosses zero to determine the actual compensation required for each phase, and selecting switched capacitors on each line to provide the balance of the compensation required.

Deployment of an inductance-based quasi-digital sensor to detect metallic wear debris in lubricant oil of rotating machinery

NASA Astrophysics Data System (ADS)

Sanga, Ramesh; Srinivasan, V. S.; Sivaramakrishna, M.; Prabhakara Rao, G.

2018-07-01

In rotating machinery due to continuous rotational induced wear and tear, metallic debris will be produced and mixes with the in-service lubricant oil over the course of time. This debris gives the sign of potential machine failure due to the aging of critical parts like gears and bearings. The size and type of wear debris has a direct relationship with the degree of wear in the machine and gives information about the healthiness of equipment. This article presents an inductive quasi-digital sensor to detect the metallic debris, its type; size in the lubrication oil of rotating machinery. A microcontroller based low cost, low power, high resolution and high precise instrument with alarm indication and LCD is developed to detect ferrous debris of sizes from 30 µm and non-ferrous debris of 50 µm. It is thoroughly tested and calibrated with ferrous, non-ferrous debris of different sizes in the air environment. Finally, an experiment is conducted to check the performance of the instrument by circulating lubricant oil containing ferrous, non-ferrous debris through the sensor.

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Acceleration modules in linear induction accelerators

NASA Astrophysics Data System (ADS)

Wang, Shao-Heng; Deng, Jian-Jun

2014-05-01

The Linear Induction Accelerator (LIA) is a unique type of accelerator that is capable of accelerating kilo-Ampere charged particle current to tens of MeV energy. The present development of LIA in MHz bursting mode and the successful application into a synchrotron have broadened LIA's usage scope. Although the transformer model is widely used to explain the acceleration mechanism of LIAs, it is not appropriate to consider the induction electric field as the field which accelerates charged particles for many modern LIAs. We have examined the transition of the magnetic cores' functions during the LIA acceleration modules' evolution, distinguished transformer type and transmission line type LIA acceleration modules, and re-considered several related issues based on transmission line type LIA acceleration module. This clarified understanding should help in the further development and design of LIA acceleration modules.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartolac, S; Letourneau, D; University of Toronto, Toronto, Ontario

Purpose: Application of process control theory in quality assurance programs promises to allow earlier identification of problems and potentially better quality in delivery than traditional paradigms based primarily on tolerances and action levels. The purpose of this project was to characterize underlying seasonal variations in linear accelerator output that can be used to improve performance or trigger preemptive maintenance. Methods: Review of runtime plots of daily (6 MV) output data acquired using in house ion chamber based devices over three years and for fifteen linear accelerators of varying make and model were evaluated. Shifts in output due to known interventionsmore » with the machines were subtracted from the data to model an uncorrected scenario for each linear accelerator. Observable linear trends were also removed from the data prior to evaluation of periodic variations. Results: Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all units, irrespective of manufacturer, model or age of machine. The average amplitude of the variation was on the order of 1%. Peak and minimum variations were found to correspond to early April and September, respectively. Approximately 48% of output adjustments made over the period examined were potentially avoidable if baseline levels had corresponded to the mean output, rather than to points near a peak or valley. Linear trends were observed for three of the fifteen units, with annual increases in output ranging from 2–3%. Conclusion: Characterization of cyclical seasonal trends allows for better separation of potentially innate accelerator behaviour from other behaviours (e.g. linear trends) that may be better described as true out of control states (i.e. non-stochastic deviations from otherwise expected behavior) and could indicate service requirements. Results also pointed to an optimal setpoint for accelerators such that output of machines is maintained within set tolerances and interventions are required less frequently.« less

Color line scan camera technology and machine vision: requirements to consider

NASA Astrophysics Data System (ADS)

Paernaenen, Pekka H. T.

1997-08-01

Color machine vision has shown a dynamic uptrend in use within the past few years as the introduction of new cameras and scanner technologies itself underscores. In the future, the movement from monochrome imaging to color will hasten, as machine vision system users demand more knowledge about their product stream. As color has come to the machine vision, certain requirements for the equipment used to digitize color images are needed. Color machine vision needs not only a good color separation but also a high dynamic range and a good linear response from the camera used. Good dynamic range and linear response is necessary for color machine vision. The importance of these features becomes even more important when the image is converted to another color space. There is always lost some information when converting integer data to another form. Traditionally the color image processing has been much slower technique than the gray level image processing due to the three times greater data amount per image. The same has applied for the three times more memory needed. The advancements in computers, memory and processing units has made it possible to handle even large color images today cost efficiently. In some cases he image analysis in color images can in fact even be easier and faster than with a similar gray level image because of more information per pixel. Color machine vision sets new requirements for lighting, too. High intensity and white color light is required in order to acquire good images for further image processing or analysis. New development in lighting technology is bringing eventually solutions for color imaging.

Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table

NASA Astrophysics Data System (ADS)

Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Esa Juhani Mononen, Mika; Lipponen, Antti; Reunanen, Juha; Vilhelm Lindfors, Anders; Mikkonen, Santtu; Erkki Juhani Lehtinen, Kari; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti

2016-07-01

In order to have a good estimate of the current forcing by anthropogenic aerosols, knowledge on past aerosol levels is needed. Aerosol optical depth (AOD) is a good measure for aerosol loading. However, dedicated measurements of AOD are only available from the 1990s onward. One option to lengthen the AOD time series beyond the 1990s is to retrieve AOD from surface solar radiation (SSR) measurements taken with pyranometers. In this work, we have evaluated several inversion methods designed for this task. We compared a look-up table method based on radiative transfer modelling, a non-linear regression method and four machine learning methods (Gaussian process, neural network, random forest and support vector machine) with AOD observations carried out with a sun photometer at an Aerosol Robotic Network (AERONET) site in Thessaloniki, Greece. Our results show that most of the machine learning methods produce AOD estimates comparable to the look-up table and non-linear regression methods. All of the applied methods produced AOD values that corresponded well to the AERONET observations with the lowest correlation coefficient value being 0.87 for the random forest method. While many of the methods tended to slightly overestimate low AODs and underestimate high AODs, neural network and support vector machine showed overall better correspondence for the whole AOD range. The differences in producing both ends of the AOD range seem to be caused by differences in the aerosol composition. High AODs were in most cases those with high water vapour content which might affect the aerosol single scattering albedo (SSA) through uptake of water into aerosols. Our study indicates that machine learning methods benefit from the fact that they do not constrain the aerosol SSA in the retrieval, whereas the LUT method assumes a constant value for it. This would also mean that machine learning methods could have potential in reproducing AOD from SSR even though SSA would have changed during the observation period.

Slip control for LIM propelled transit vehicles

NASA Astrophysics Data System (ADS)

Wallace, A. K.; Parker, J. H.; Dawson, G. E.

1980-09-01

Short stator linear induction motors, with an iron-backed aluminum sheet reaction rail and powered by a controlled inverter, have been selected as the propulsion system for transit vehicles in an intermediate capacity system (12-20,000 pphpd). The linear induction motor is capable of adhesion independent braking and acceleration levels which permit safe, close headways. In addition, simple control is possible allowing moving block automatic train control. This paper presents a slip frequency control scheme for the LIM. Experimental results for motoring and braking obtained from a test vehicle are also presented. These values are compared with theoretical predictions.

Simple Procedure to Compute the Inductance of a Toroidal Ferrite Core from the Linear to the Saturation Regions

PubMed Central

Salas, Rosa Ana; Pleite, Jorge

2013-01-01

We propose a specific procedure to compute the inductance of a toroidal ferrite core as a function of the excitation current. The study includes the linear, intermediate and saturation regions. The procedure combines the use of Finite Element Analysis in 2D and experimental measurements. Through the two dimensional (2D) procedure we are able to achieve convergence, a reduction of computational cost and equivalent results to those computed by three dimensional (3D) simulations. The validation is carried out by comparing 2D, 3D and experimental results. PMID:28809283

Tool setting device

DOEpatents

Brown, Raymond J.

1977-01-01

The present invention relates to a tool setting device for use with numerically controlled machine tools, such as lathes and milling machines. A reference position of the machine tool relative to the workpiece along both the X and Y axes is utilized by the control circuit for driving the tool through its program. This reference position is determined for both axes by displacing a single linear variable displacement transducer (LVDT) with the machine tool through a T-shaped pivotal bar. The use of the T-shaped bar allows the cutting tool to be moved sequentially in the X or Y direction for indicating the actual position of the machine tool relative to the predetermined desired position in the numerical control circuit by using a single LVDT.

Intelligent image processing for machine safety

NASA Astrophysics Data System (ADS)

Harvey, Dennis N.

1994-10-01

This paper describes the use of intelligent image processing as a machine guarding technology. One or more color, linear array cameras are positioned to view the critical region(s) around a machine tool or other piece of manufacturing equipment. The image data is processed to provide indicators of conditions dangerous to the equipment via color content, shape content, and motion content. The data from these analyses is then sent to a threat evaluator. The purpose of the evaluator is to determine if a potentially machine-damaging condition exists based on the analyses of color, shape, and motion, and on `knowledge' of the specific environment of the machine. The threat evaluator employs fuzzy logic as a means of dealing with uncertainty in the vision data.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders.

PubMed

Viejo, Guillaume; Cortier, Thomas; Peyrache, Adrien

2018-03-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains.

Brain-state invariant thalamo-cortical coordination revealed by non-linear encoders

PubMed Central

Cortier, Thomas; Peyrache, Adrien

2018-01-01

Understanding how neurons cooperate to integrate sensory inputs and guide behavior is a fundamental problem in neuroscience. A large body of methods have been developed to study neuronal firing at the single cell and population levels, generally seeking interpretability as well as predictivity. However, these methods are usually confronted with the lack of ground-truth necessary to validate the approach. Here, using neuronal data from the head-direction (HD) system, we present evidence demonstrating how gradient boosted trees, a non-linear and supervised Machine Learning tool, can learn the relationship between behavioral parameters and neuronal responses with high accuracy by optimizing the information rate. Interestingly, and unlike other classes of Machine Learning methods, the intrinsic structure of the trees can be interpreted in relation to behavior (e.g. to recover the tuning curves) or to study how neurons cooperate with their peers in the network. We show how the method, unlike linear analysis, reveals that the coordination in thalamo-cortical circuits is qualitatively the same during wakefulness and sleep, indicating a brain-state independent feed-forward circuit. Machine Learning tools thus open new avenues for benchmarking model-based characterization of spike trains. PMID:29565979

Micro-Machined High-Frequency (80 MHz) PZT Thick Film Linear Arrays

PubMed Central

Zhou, Qifa; Wu, Dawei; Liu, Changgeng; Zhu, Benpeng; Djuth, Frank; Shung, K. Kirk

2010-01-01

This paper presents the development of a micro-machined high-frequency linear array using PZT piezoelectric thick films. The linear array has 32 elements with an element width of 24 μm and an element length of 4 mm. Array elements were fabricated by deep reactive ion etching of PZT thick films, which were prepared from spin-coating of PZT solgel composite. Detailed fabrication processes, especially PZT thick film etching conditions and a novel transferring-and-etching method, are presented and discussed. Array designs were evaluated by simulation. Experimental measurements show that the array had a center frequency of 80 MHz and a fractional bandwidth (−6 dB) of 60%. An insertion loss of −41 dB and adjacent element crosstalk of −21 dB were found at the center frequency. PMID:20889407

Integrative relational machine-learning for understanding drug side-effect profiles

PubMed Central

2013-01-01

Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs. PMID:23802887

Integrative relational machine-learning for understanding drug side-effect profiles.

PubMed

Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika

2013-06-26

Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Evaluation of half wave induction motor drive for use in passenger vehicles

NASA Technical Reports Server (NTRS)

Hoft, R. G.; Kawamura, A.; Goodarzi, A.; Yang, G. Q.; Erickson, C. L.

1985-01-01

Research performed at the University of Missouri-Columbia to devise and design a lower cost inverter induction motor drive for electrical propulsion of passenger vehicles is described. A two phase inverter motor system is recommended. The new design is predicted to provide comparable vehicle performance, improved reliability and a cost advantage for a high production vehicle, decreased total rating of the power semiconductor switches, and a somewhat simpler control hardware compared to the conventional three phase bridge inverter motor drive system. The major disadvantages of the two phase inverter motor drive are that it is larger and more expensive than a three phase machine, the design of snubbers for the power leakage inductances produce higher transient voltages, and the torque pulsations are relatively large because of the necessity to limit the inverter switching frequency to achieve high efficiency.

Power-Factor Calculation under Consideration of Cross Saturation of the Interior Permanent Magnet Synchronous Motor with Brushless Field Excitation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Seong T; Burress, Timothy A; Hsu, John S

2009-01-01

This paper introduces a new method for calculating the power factor with consideration of the cross saturation between the direct-axis (d-axis) and the quadrature-axis (q-axis) of an interior permanent magnet synchronous motor (IPMSM). The conventional two-axis IPMSM model is modified to include the cross-saturation effect by adding the cross-coupled inductance terms. This paper also contains the new method of calculating the cross-coupled inductance values as well as self-inductance values in d- and q-axes. The analyzed motor is a high-speed brushless field excitation machine that offers high torque per ampere per core length at low speed and weakened flux at highmore » speed, which was developed for the traction motor of a hybrid electric vehicle.« less

Knowledge discovery with classification rules in a cardiovascular dataset.

PubMed

Podgorelec, Vili; Kokol, Peter; Stiglic, Milojka Molan; Hericko, Marjan; Rozman, Ivan

2005-12-01

In this paper we study an evolutionary machine learning approach to data mining and knowledge discovery based on the induction of classification rules. A method for automatic rules induction called AREX using evolutionary induction of decision trees and automatic programming is introduced. The proposed algorithm is applied to a cardiovascular dataset consisting of different groups of attributes which should possibly reveal the presence of some specific cardiovascular problems in young patients. A case study is presented that shows the use of AREX for the classification of patients and for discovering possible new medical knowledge from the dataset. The defined knowledge discovery loop comprises a medical expert's assessment of induced rules to drive the evolution of rule sets towards more appropriate solutions. The final result is the discovery of a possible new medical knowledge in the field of pediatric cardiology.

Intense X-ray machine for penetrating radiography

NASA Astrophysics Data System (ADS)

Lucht, Roy A.; Eckhouse, Shimon

Penetrating radiography has been used for many years in the nuclear weapons research programs. Infrequently penetrating radiography has been used in conventional weapons research programs. For example the Los Alamos PHERMEX machine was used to view uranium rods penetrating steel for the GAU-8 program, and the Ector machine was used to see low density regions in forming metal jets. The armor/anti-armor program at Los Alamos has created a need for an intense flash X-ray machine that can be dedicated to conventional weapons research. The Balanced Technology Initiative, through DARPA, has funded the design and construction of such a machine at Los Alamos. It will be an 8- to 10-MeV diode machine capable of delivering a dose of 500 R at 1 m with a spot size of less than 5 mm. The machine used an 87.5-stage low inductance Marx generator that charges up a 7.4-(Omega), 32-ns water line. The water line is discharged through a self-breakdown oil switch into a 12.4-(Omega) water line that rings up the voltage into the high impendance X-ray diode. A long (233-cm) vacuum drift tube is used to separate the large diameter oil-insulated diode region from the X-ray source area that may be exposed to high overpressures by the explosive experiments. The electron beam is selffocused at the target area using a low pressure background gas.

A New Apparatus for Measuring the Temperature at Machine Parts Rotating at High Speeds

NASA Technical Reports Server (NTRS)

Gnam, E.

1945-01-01

After a brief survey of the available methods for measuring the temperatures of machine parts at high speed, in particular turbine blades and rotors, an apparatus is described which is constructed on the principle of induction. Transmission of the measuring current by sliding contacts therefore is avoided. Up-to-date experiments show that it is possible to give the apparatus a high degree of sensitivity and accuracy. In comparison with sliding contact types, the present apparatus shows the important advantage that it operates for any length of time without wear, and that the contact difficulties, particularly occurring at high sliding speeds,are avoided.

Influence of cutting strains and magnetic anisotropy of electrical steel on the air gap flux distribution of an induction motor

NASA Astrophysics Data System (ADS)

Hribernik, Božo

1984-02-01

This paper describes an iterative algorithm for the simulation of various real magnetic materials in a small induction motor and their influence on the flux distribution in the air gap. Two standard materials, fully-, and semi-processed steel strips were used. The nonlinearity of the magnetization curve, the influence of cutting strains and magnetic anisotropy are also considered. All these influences bring out the facts that the uniformly rotated and sine form exitation causes a nonuniformly rotated and deformed magnetic field in the air gap of the machine and that the magnetization current is winding place dependent.

Fractography of induction-hardened steel fractured in fatigue and overload

DOE Office of Scientific and Technical Information (OSTI.GOV)

Santos, C.G.; Laird, C.

1997-07-01

The fracture surfaces of induction-hardened steel specimens obtained from an auto axle were characterized, macroscopically and microscopically, after being fractured in fatigue and monotonic overload. Specimens were tested in cyclic three-point bending under load control, and the S-N curve was established for specimens that had been notched by spark machining to facilitate fractography. Scanning electron microscopy of the fractured surfaces obtained for lives spanning the range 17,000 to 418,000 cycles revealed diverse fracture morphologies, including intergranular fracture and transgranular fatigue fracture. The results are being offered to assist in the analysis of complex field failures in strongly hardened steel.

Using a Model to Describe Students' Inductive Reasoning in Problem Solving

ERIC Educational Resources Information Center

Canadas, Maria C.; Castro, Encarnacion; Castro, Enrique

2009-01-01

Introduction: We present some aspects of a wider investigation (Canadas, 2007), whose main objective is to describe and characterize inductive reasoning used by Spanish students in years 9 and 10 when they work on problems that involved linear and quadratic sequences. Method: We produced a test composed of six problems with different…

A model of annular linear induction pumps

DOE Office of Scientific and Technical Information (OSTI.GOV)

Momozaki, Yoichi

2016-10-27

The present work explains how the magnetic field and the induced current are obtained when the distributed coils are powered by a 3 phase power supply.  From the magnetic field and the induced current, the thrust and the induction losses in the pump can be calculated to estimate the pump performance.

Channel Efficiency with Security Enhancement for Remote Condition Monitoring of Multi Machine System Using Hybrid Huffman Coding

NASA Astrophysics Data System (ADS)

Datta, Jinia; Chowdhuri, Sumana; Bera, Jitendranath

2016-12-01

This paper presents a novel scheme of remote condition monitoring of multi machine system where a secured and coded data of induction machine with different parameters is communicated between a state-of-the-art dedicated hardware Units (DHU) installed at the machine terminal and a centralized PC based machine data management (MDM) software. The DHUs are built for acquisition of different parameters from the respective machines, and hence are placed at their nearby panels in order to acquire different parameters cost effectively during their running condition. The MDM software collects these data through a communication channel where all the DHUs are networked using RS485 protocol. Before transmitting, the parameter's related data is modified with the adoption of differential pulse coded modulation (DPCM) and Huffman coding technique. It is further encrypted with a private key where different keys are used for different DHUs. In this way a data security scheme is adopted during its passage through the communication channel in order to avoid any third party attack into the channel. The hybrid mode of DPCM and Huffman coding is chosen to reduce the data packet length. A MATLAB based simulation and its practical implementation using DHUs at three machine terminals (one healthy three phase, one healthy single phase and one faulty three phase machine) proves its efficacy and usefulness for condition based maintenance of multi machine system. The data at the central control room are decrypted and decoded using MDM software. In this work it is observed that Chanel efficiency with respect to different parameter measurements has been increased very much.

Burner Rig in the Material and Stresses Building

NASA Image and Video Library

1969-11-21

A burner rig heats up a material sample in the Materials and Stresses Building at the National Aeronautics and Space Administration (NASA) Lewis Research Center. Materials technology is an important element in the successful development of advanced airbreathing and rocket propulsion systems. Different types of engines operate in different environments so an array of dependable materials is needed. NASA Lewis began investigating the characteristics of different materials shortly after World War II. In 1949 the materials group was expanded into its own division. The Lewis researchers sought to study and test materials in environments that simulate the environment in which they would operate. The Materials and Stresses Building, built in 1949, contained a number of laboratories to analyze the materials. They are subjected to high temperatures, high stresses, corrosion, irradiation, and hot gasses. The Physics of Solids Laboratory included a cyclotron, cloud chamber, helium cryostat, and metallurgy cave. The Metallographic Laboratory possessed six x-ray diffraction machines, two metalloscopes, and other equipment. The Furnace Room had two large induction machines, a 4500⁰ F graphite furnace, and heat treating equipment. The Powder Laboratory included 60-ton and 3000-ton presses. The Stresses Laboratory included stress rupture machines, fatigue machines, and tensile strength machines.

SU-F-T-459: ArcCHECK Machine QA : Highly Efficient Quality Assurance Tool for VMAT, SRS & SBRT Linear Accelerator Delivery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mhatre, V; Patwe, P; Dandekar, P

Purpose: Quality assurance (QA) of complex linear accelerators is critical and highly time consuming. ArcCHECK Machine QA tool is used to test geometric and delivery aspects of linear accelerator. In this study we evaluated the performance of this tool. Methods: Machine QA feature allows user to perform quality assurance tests using ArcCHECK phantom. Following tests were performed 1) Gantry Speed 2) Gantry Rotation 3) Gantry Angle 4)MLC/Collimator QA 5)Beam Profile Flatness & Symmetry. Data was collected on trueBEAM stX machine for 6 MV for a period of one year. The Gantry QA test allows to view errors in gantry angle,more » rotation & assess how accurately the gantry moves around the isocentre. The MLC/Collimator QA tool is used to analyze & locate the differences between leaf bank & jaw position of linac. The flatness & Symmetry test quantifies beam flatness & symmetry in IEC-y & x direction. The Gantry & Flatness/Symmetry test can be performed for static & dynamic delivery. Results: The Gantry speed was 3.9 deg/sec with speed maximum deviation around 0.3 deg/sec. The Gantry Isocentre for arc delivery was 0.9mm & static delivery was 0.4mm. The maximum percent positive & negative difference was found to be 1.9 % & – 0.25 % & maximum distance positive & negative diff was 0.4mm & – 0.3 mm for MLC/Collimator QA. The Flatness for Arc delivery was 1.8 % & Symmetry for Y was 0.8 % & X was 1.8 %. The Flatness for gantry 0°,270°,90° & 180° was 1.75,1.9,1.8 & 1.6% respectively & Symmetry for X & Y was 0.8,0.6% for 0°, 0.6,0.7% for 270°, 0.6,1% for 90° & 0.6,0.7% for 180°. Conclusion: ArcCHECK Machine QA is an useful tool for QA of Modern linear accelerators as it tests both geometric & delivery aspects. This is very important for VMAT, SRS & SBRT treatments.« less

Racial Disparity in Renal Transplantation: Alemtuzumab the Great Equalizer?

PubMed

Smith, Alison A; John, Mira M; Dortonne, Isabelle S; Paramesh, Anil S; Killackey, Mary; Jaffe, Bernard M; Buell, Joseph F

2015-10-01

Racial disparity as a barrier to successful outcomes in renal transplants for African Americans has been well described. Numerous unsuccessful attempts have been made to identify specific immunologic and socioeconomic factors. The objective of our study was to determine whether alemtuzumab (AL) induction abolishes this discrepancy and improves allograft survival in African American recipients. A retrospective chart review of consecutive adult renal transplants was conducted between 2006 and 2014. Kaplan-Meier analysis and hazard ratios were calculated for the African Americans (AA) and white groups. Multiple linear regressions were performed to assess independent variables (race, retransplant, sex, donor type, induction agent) on allograft survival. A significant difference in allograft survival was identified between whites (n = 272) and AA (n = 445), with AA experiencing more graft losses (18.2% vs 12.1%, P = 0.0351). Induction with AL improved outcomes in all transplant recipients. Multiple linear regression identified that the strongest predictor of allograft failure was induction without AL (P < 0.0001). The data for a subset analysis matched for follow-up length demonstrated that whites compared with AA (n = 157, 67 whites and 90 AA) had lower rates of allograft failure in the absence of AL induction (14.9% vs 44.4%, P = 0.0156, hazard ratio = 2.077). In contrast, AL induction (n = 275, 105 whites and 170 AA) eliminated the racial disparity in allograft failure (5.7% vs 9.4%, P = 0.8248, hazard ratio = 1.504). This is the first study to describe the effects of AL induction therapy on AA renal transplant recipients beyond the first posttransplant year. Our early results suggest that AL induction therapy abolishes the disparity in renal allograft failure.

Incorporating inductances in tissue-scale models of cardiac electrophysiology

NASA Astrophysics Data System (ADS)

Rossi, Simone; Griffith, Boyce E.

2017-09-01

In standard models of cardiac electrophysiology, including the bidomain and monodomain models, local perturbations can propagate at infinite speed. We address this unrealistic property by developing a hyperbolic bidomain model that is based on a generalization of Ohm's law with a Cattaneo-type model for the fluxes. Further, we obtain a hyperbolic monodomain model in the case that the intracellular and extracellular conductivity tensors have the same anisotropy ratio. In one spatial dimension, the hyperbolic monodomain model is equivalent to a cable model that includes axial inductances, and the relaxation times of the Cattaneo fluxes are strictly related to these inductances. A purely linear analysis shows that the inductances are negligible, but models of cardiac electrophysiology are highly nonlinear, and linear predictions may not capture the fully nonlinear dynamics. In fact, contrary to the linear analysis, we show that for simple nonlinear ionic models, an increase in conduction velocity is obtained for small and moderate values of the relaxation time. A similar behavior is also demonstrated with biophysically detailed ionic models. Using the Fenton-Karma model along with a low-order finite element spatial discretization, we numerically analyze differences between the standard monodomain model and the hyperbolic monodomain model. In a simple benchmark test, we show that the propagation of the action potential is strongly influenced by the alignment of the fibers with respect to the mesh in both the parabolic and hyperbolic models when using relatively coarse spatial discretizations. Accurate predictions of the conduction velocity require computational mesh spacings on the order of a single cardiac cell. We also compare the two formulations in the case of spiral break up and atrial fibrillation in an anatomically detailed model of the left atrium, and we examine the effect of intracellular and extracellular inductances on the virtual electrode phenomenon.

Electric Machine with Boosted Inductance to Stabilize Current Control

NASA Technical Reports Server (NTRS)

Abel, Steve

2013-01-01

High-powered motors typically have very low resistance and inductance (R and L) in their windings. This makes the pulse-width modulated (PWM) control of the current very difficult, especially when the bus voltage (V) is high. These R and L values are dictated by the motor size, torque (Kt), and back-emf (Kb) constants. These constants are in turn set by the voltage and the actuation torque-speed requirements. This problem is often addressed by placing inductive chokes within the controller. This approach is undesirable in that space is taken and heat is added to the controller. By keeping the same motor frame, reducing the wire size, and placing a correspondingly larger number of turns in each slot, the resistance, inductance, torque constant, and back-emf constant are all increased. The increased inductance aids the current control but ruins the Kt and Kb selections. If, however, a fraction of the turns is moved from their "correct slot" to an "incorrect slot," the increased R and L values are retained, but the Kt and Kb values are restored to the desired values. This approach assumes that increased resistance is acceptable to a degree. In effect, the heat allocated to the added inductance has been moved from the controller to the motor body, which in some cases is preferred.

Extending the Constant Power Speed Range of the Brushless DC Motor through Dual Mode Inverter Control -- Part I: Theory and Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lawler, J.S.

2001-10-29

An inverter topology and control scheme has been developed that can drive low-inductance, surface-mounted permanent magnet motors over the wide constant power speed range required in electric vehicle applications. This new controller is called the dual-mode inverter control (DMIC) [1]. The DMIC can drive either the Permanent Magnet Synchronous Machine (PMSM) with sinusoidal back emf, or the brushless dc machine (BDCM) with trapezoidal emf in the motoring and regenerative braking modes. In this paper we concentrate on the BDCM under high-speed motoring conditions. Simulation results show that if all motor and inverter loss mechanisms are neglected, the constant power speedmore » range of the DMIC is infinite. The simulation results are supported by closed form expressions for peak and rms motor current and average power derived from analytical solution to the differential equations governing the DMIC/BDCM drive for the lossless case. The analytical solution shows that the range of motor inductance that can be accommodated by the DMIC is more than an order of magnitude such that the DMIC is compatible with both low- and high-inductance BDCMs. Finally, method is given for integrating the classical hysteresis band current control, used for motor control below base speed, with the phase advance of DMIC that is applied above base speed. The power versus speed performance of the DMIC is then simulated across the entire speed range.« less

A Wavelet Support Vector Machine Combination Model for Singapore Tourist Arrival to Malaysia

NASA Astrophysics Data System (ADS)

Rafidah, A.; Shabri, Ani; Nurulhuda, A.; Suhaila, Y.

2017-08-01

In this study, wavelet support vector machine model (WSVM) is proposed and applied for monthly data Singapore tourist time series prediction. The WSVM model is combination between wavelet analysis and support vector machine (SVM). In this study, we have two parts, first part we compare between the kernel function and second part we compare between the developed models with single model, SVM. The result showed that kernel function linear better than RBF while WSVM outperform with single model SVM to forecast monthly Singapore tourist arrival to Malaysia.

Methods, systems and apparatus for adjusting modulation index to improve linearity of phase voltage commands

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gallegos-Lopez, Gabriel; Perisic, Milun; Kinoshita, Michael H.

2017-03-14

Embodiments of the present invention relate to methods, systems and apparatus for controlling operation of a multi-phase machine in a motor drive system. The disclosed embodiments provide a mechanism for adjusting modulation index of voltage commands to improve linearity of the voltage commands.

Optical Coherence Tomography Machine Learning Classifiers for Glaucoma Detection: A Preliminary Study

PubMed Central

Burgansky-Eliash, Zvia; Wollstein, Gadi; Chu, Tianjiao; Ramsey, Joseph D.; Glymour, Clark; Noecker, Robert J.; Ishikawa, Hiroshi; Schuman, Joel S.

2007-01-01

Purpose Machine-learning classifiers are trained computerized systems with the ability to detect the relationship between multiple input parameters and a diagnosis. The present study investigated whether the use of machine-learning classifiers improves optical coherence tomography (OCT) glaucoma detection. Methods Forty-seven patients with glaucoma (47 eyes) and 42 healthy subjects (42 eyes) were included in this cross-sectional study. Of the glaucoma patients, 27 had early disease (visual field mean deviation [MD] ≥ −6 dB) and 20 had advanced glaucoma (MD < −6 dB). Machine-learning classifiers were trained to discriminate between glaucomatous and healthy eyes using parameters derived from OCT output. The classifiers were trained with all 38 parameters as well as with only 8 parameters that correlated best with the visual field MD. Five classifiers were tested: linear discriminant analysis, support vector machine, recursive partitioning and regression tree, generalized linear model, and generalized additive model. For the last two classifiers, a backward feature selection was used to find the minimal number of parameters that resulted in the best and most simple prediction. The cross-validated receiver operating characteristic (ROC) curve and accuracies were calculated. Results The largest area under the ROC curve (AROC) for glaucoma detection was achieved with the support vector machine using eight parameters (0.981). The sensitivity at 80% and 95% specificity was 97.9% and 92.5%, respectively. This classifier also performed best when judged by cross-validated accuracy (0.966). The best classification between early glaucoma and advanced glaucoma was obtained with the generalized additive model using only three parameters (AROC = 0.854). Conclusions Automated machine classifiers of OCT data might be useful for enhancing the utility of this technology for detecting glaucomatous abnormality. PMID:16249492

Self-Centering Reciprocating-Permanent-Magnet Machine

NASA Technical Reports Server (NTRS)

Bhate, Suresh; Vitale, Nick

1988-01-01

New design for monocoil reciprocating-permanent-magnet electric machine provides self-centering force. Linear permanent-magnet electrical motor includes outer stator, inner stator, and permanent-magnet plunger oscillateing axially between extreme left and right positions. Magnets arranged to produce centering force and allows use of only one coil of arbitrary axial length. Axial length of coil chosen to provide required efficiency and power output.

Beam breakup in an advanced linear induction accelerator

DOE PAGES

Ekdahl, Carl August; Coleman, Joshua Eugene; McCuistian, Brian Trent

2016-07-01

Two linear induction accelerators (LIAs) have been in operation for a number of years at the Los Alamos Dual Axis Radiographic Hydrodynamic Test (DARHT) facility. A new multipulse LIA is being developed. We have computationally investigated the beam breakup (BBU) instability in this advanced LIA. In particular, we have explored the consequences of the choice of beam injector energy and the grouping of LIA cells. We find that within the limited range of options presently under consideration for the LIA architecture, there is little adverse effect on the BBU growth. The computational tool that we used for this investigation wasmore » the beam dynamics code linear accelerator model for DARHT (LAMDA). In conclusion, to confirm that LAMDA was appropriate for this task, we first validated it through comparisons with the experimental BBU data acquired on the DARHT accelerators.« less

The development and testing of a linear induction motor being fed from the source with limited electric power

NASA Astrophysics Data System (ADS)

Tiunov, V. V.

2018-02-01

The report provides results of the research related to the tubular linear induction motors’ application. The motors’ design features, a calculation model, a description of test specimens for mining and electric power industry are introduced. The most attention is given to the single-phase motors for high voltage switches drives with the usage of inexpensive standard single-phase transformers for motors’ power supply. The method of the motor’s parameters determination, when the motor is being fed from the transformer, working in the overload mode, was described, and the results of it practical usage were good enough for the engineering practice.

Emittance Growth in the DARHT-II Linear Induction Accelerator

NASA Astrophysics Data System (ADS)

Ekdahl, Carl; Carlson, Carl A.; Frayer, Daniel K.; McCuistian, B. Trent; Mostrom, Christopher B.; Schulze, Martin E.; Thoma, Carsten H.

2017-11-01

The Dual-Axis Radiographic Hydrotest (DARHT) facility uses bremsstrahlung radiation source spots produced by the focused electron beams from two linear induction accelerators (LIAs) to radiograph large hydrodynamic experiments driven by high explosives. Radiographic resolution is determined by the size of the source spot, and beam emittance is the ultimate limitation to spot size. Some of the possible causes for the emittance growth in the DARHT LIA have been investigated using particle-in-cell (PIC) codes, and are discussed in this article. The results suggest that the most likely source of emittance growth is a mismatch of the beam to the magnetic transport, which can cause beam halo.

Toward an Improvement of the Analysis of Neural Coding.

PubMed

Alegre-Cortés, Javier; Soto-Sánchez, Cristina; Albarracín, Ana L; Farfán, Fernando D; Val-Calvo, Mikel; Ferrandez, José M; Fernandez, Eduardo

2017-01-01

Machine learning and artificial intelligence have strong roots on principles of neural computation. Some examples are the structure of the first perceptron, inspired in the retina, neuroprosthetics based on ganglion cell recordings or Hopfield networks. In addition, machine learning provides a powerful set of tools to analyze neural data, which has already proved its efficacy in so distant fields of research as speech recognition, behavioral states classification, or LFP recordings. However, despite the huge technological advances in neural data reduction of dimensionality, pattern selection, and clustering during the last years, there has not been a proportional development of the analytical tools used for Time-Frequency (T-F) analysis in neuroscience. Bearing this in mind, we introduce the convenience of using non-linear, non-stationary tools, EMD algorithms in particular, for the transformation of the oscillatory neural data (EEG, EMG, spike oscillations…) into the T-F domain prior to its analysis with machine learning tools. We support that to achieve meaningful conclusions, the transformed data we analyze has to be as faithful as possible to the original recording, so that the transformations forced into the data due to restrictions in the T-F computation are not extended to the results of the machine learning analysis. Moreover, bioinspired computation such as brain-machine interface may be enriched from a more precise definition of neuronal coding where non-linearities of the neuronal dynamics are considered.

Performance of Ti-multilayer coated tool during machining of MDN431 alloyed steel

NASA Astrophysics Data System (ADS)

Badiger, Pradeep V.; Desai, Vijay; Ramesh, M. R.

2018-04-01

Turbine forgings and other components are required to be high resistance to corrosion and oxidation because which they are highly alloyed with Ni and Cr. Midhani manufactures one of such material MDN431. It's a hard-to-machine steel with high hardness and strength. PVD coated insert provide an answer to problem with its state of art technique on the WC tool. Machinability studies is carried out on MDN431 steel using uncoated and Ti-multilayer coated WC tool insert using Taguchi optimisation technique. During the present investigation, speed (398-625rpm), feed (0.093-0.175mm/rev), and depth of cut (0.2-0.4mm) varied according to Taguchi L9 orthogonal array, subsequently cutting forces and surface roughness (Ra) were measured. Optimizations of the obtained results are done using Taguchi technique for cutting forces and surface roughness. Using Taguchi technique linear fit model regression analysis carried out for the combination of each input variable. Experimented results are compared and found the developed model is adequate which supported by proof trials. Speed, feed and depth of cut are linearly dependent on the cutting force and surface roughness for uncoated insert whereas Speed and depth of cut feed is inversely dependent in coated insert for both cutting force and surface roughness. Machined surface for coated and uncoated inserts during machining of MDN431 is studied using optical profilometer.

Energy landscapes for machine learning

NASA Astrophysics Data System (ADS)

Ballard, Andrew J.; Das, Ritankar; Martiniani, Stefano; Mehta, Dhagash; Sagun, Levent; Stevenson, Jacob D.; Wales, David J.

Machine learning techniques are being increasingly used as flexible non-linear fitting and prediction tools in the physical sciences. Fitting functions that exhibit multiple solutions as local minima can be analysed in terms of the corresponding machine learning landscape. Methods to explore and visualise molecular potential energy landscapes can be applied to these machine learning landscapes to gain new insight into the solution space involved in training and the nature of the corresponding predictions. In particular, we can define quantities analogous to molecular structure, thermodynamics, and kinetics, and relate these emergent properties to the structure of the underlying landscape. This Perspective aims to describe these analogies with examples from recent applications, and suggest avenues for new interdisciplinary research.

An Induction Heating Method with Traveling Magnetic Field for Long Structure Metal

NASA Astrophysics Data System (ADS)

Sekine, Takamitsu; Tomita, Hideo; Obata, Shuji; Saito, Yukio

A novel dismantlable adhesion method for recycling operation of interior materials is proposed. This method is applied a high frequency induction heating and a thermoplastic adhesive. For an adhesion of interior material to long steel stud, a conventional spiral coil as like IH cooking heater gives inadequateness for uniform heating to the stud. Therefore, we have proposed an induction heating method with traveling magnetic field for perfect long structures bonding. In this paper, we describe on the new adhesion method using the 20kHz, three-phase 200V inverter and linear induction coil. From induction heating characteristics to thin steel plates and long studs, the method is cleared the usefulness for uniform heating to long structures.

Parallel spatial direct numerical simulations on the Intel iPSC/860 hypercube

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.; Zubair, Mohammad

1993-01-01

The implementation and performance of a parallel spatial direct numerical simulation (PSDNS) approach on the Intel iPSC/860 hypercube is documented. The direct numerical simulation approach is used to compute spatially evolving disturbances associated with the laminar-to-turbulent transition in boundary-layer flows. The feasibility of using the PSDNS on the hypercube to perform transition studies is examined. The results indicate that the direct numerical simulation approach can effectively be parallelized on a distributed-memory parallel machine. By increasing the number of processors nearly ideal linear speedups are achieved with nonoptimized routines; slower than linear speedups are achieved with optimized (machine dependent library) routines. This slower than linear speedup results because the Fast Fourier Transform (FFT) routine dominates the computational cost and because the routine indicates less than ideal speedups. However with the machine-dependent routines the total computational cost decreases by a factor of 4 to 5 compared with standard FORTRAN routines. The computational cost increases linearly with spanwise wall-normal and streamwise grid refinements. The hypercube with 32 processors was estimated to require approximately twice the amount of Cray supercomputer single processor time to complete a comparable simulation; however it is estimated that a subgrid-scale model which reduces the required number of grid points and becomes a large-eddy simulation (PSLES) would reduce the computational cost and memory requirements by a factor of 10 over the PSDNS. This PSLES implementation would enable transition simulations on the hypercube at a reasonable computational cost.

The classification of explosion-proof protected induction motor into adequate temperature and efficiency class

NASA Astrophysics Data System (ADS)

Brinovar, Iztok; Srpčič, Gregor; Seme, Sebastijan; Štumberger, Bojan; Hadžiselimović, Miralem

2017-07-01

This article deals with the classification of explosion-proof protected induction motors, which are used in hazardous areas, into adequate temperature and efficiency class. Hazardous areas are defined as locations with a potentially explosive atmosphere where explosion may occur due to present of flammable gasses, liquids or combustible dusts (industrial plants, mines, etc.). Electric motors and electrical equipment used in such locations must be specially designed and tested to prevent electrical initiation of explosion due to high surface temperature and arcing contacts. This article presents the basic tests of three-phase explosion-proof protected induction motor with special emphasis on the measuring system and temperature rise test. All the measurements were performed with high-accuracy instrumentation and accessory equipment and carried out at the Institute of energy technology in the Electric machines and drives laboratory and Applied electrical engineering laboratory.

Analysis of field-oriented controlled induction motor drives under sensor faults and an overview of sensorless schemes.

PubMed

Arun Dominic, D; Chelliah, Thanga Raj

2014-09-01

To obtain high dynamic performance on induction motor drives (IMD), variable voltage and variable frequency operation has to be performed by measuring speed of rotation and stator currents through sensors and fed back them to the controllers. When the sensors are undergone a fault, the stability of control system, may be designed for an industrial process, is disturbed. This paper studies the negative effects on a 12.5 hp induction motor drives when the field oriented control system is subjected to sensor faults. To illustrate the importance of this study mine hoist load diagram is considered as shaft load of the tested machine. The methods to recover the system from sensor faults are discussed. In addition, the various speed sensorless schemes are reviewed comprehensively. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Assessment of the microstructure and torsional fatigue performance of an induction hardened vanadium microalloyed medium-carbon steel

NASA Astrophysics Data System (ADS)

Rothleutner, Lee M.

Vanadium microalloying of medium-carbon bar steels is a common practice in industry for a number of hot rolled as well as forged and controlled-cooled components. However, use of vanadium microalloyed steels has expanded into applications beyond their originally designed controlled-cooled processing scheme. Applications such as transmission shafts often require additional heat-treatments such as quench and tempering and/or induction hardening to meet packaging or performance requirements. As a result, there is uncertainty regarding the influence of vanadium on the properties of heat-treated components, specifically the effect of rapid heat-treating such as induction hardening. In the current study, the microstructural evolution and torsional fatigue behavior of induction hardened 1045 and 10V45 (0.08 wt pct V) steels were examined. Torsional fatigue specimens specifically designed for this research were machined from the as-received, hot rolled bars and induction hardened using both scanning (96 kHz/72 kW) and single-shot (31 kHz/128 kW) methods. Four conditions were evaluated, three scan hardened to 25, 32, and 44 pct nominal effective case depths and one single-shot hardened to 44 pct. Torsional fatigue tests were conducted at a stress ratio of 0.1 and shear stress amplitudes of 550, 600, and 650 MPa. Physical simulations using the thermal profiles from select induction hardened conditions were conducted in the GleebleRTM 3500 to augment microstructural analysis of torsional fatigue specimens. Thermal profiles were calculated by a collaborating private company using electro-thermal finite element analysis. Residual stresses were evaluated for all conditions using a strain gage hole drilling technique. The results showed that vanadium microalloying has an influence on the microstructure in the highest hardness region of the induction-hardened case as well as the total case region. Vanadium microalloyed conditions consistently exhibited a greater amount of non-martensitic transformation products in the induction-hardened case. In the total case region, vanadium reduced the total case depth by inhibiting austenite formation at low austenitizing temperatures; however, the non-martensitic constituents in the case microstructure and the reduced total case depth of the vanadium microalloyed steel did not translate directly to a degradation of torsional fatigue properties. In general, vanadium microalloying was not found to affect torsional fatigue performance significantly with one exception. In the 25 pct effective case depth condition, the 10V45 steel had a ~75 pct increase in fatigue life at all shear stress amplitudes when compared to the 1045 steel. The improved fatigue performance is likely a result of the significantly higher case hardness this condition exhibited compared to all other conditions. The direct influence of vanadium on the improved fatigue life of the 25 pct effective case depth condition is confounded with the slightly higher carbon content of the 10V45 steel. In addition, the 10V45 conditions showed a consistently higher case hardness than the in 1045 conditions. The increased hardness of the 10V45 steel did not increase the compressive residual stresses at the surface. Induction hardening parameters were more closely related to changes in residual stress than vanadium microalloying additions. Torsional fatigue data from the current study as well as from literature were used to develop an empirical multiple linear regression model that accounts for case depth as well as carbon content when predicting torsional fatigue life of induction hardened medium-carbon steels.

Physics with e{sup +}e{sup -} Linear Colliders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barklow, Timothy L

2003-05-05

We describe the physics potential of e{sup +}e{sup -} linear colliders in this report. These machines are planned to operate in the first phase at a center-of-mass energy of 500 GeV, before being scaled up to about 1 TeV. In the second phase of the operation, a final energy of about 2 TeV is expected. The machines will allow us to perform precision tests of the heavy particles in the Standard Model, the top quark and the electroweak bosons. They are ideal facilities for exploring the properties of Higgs particles, in particular in the intermediate mass range. New vector bosonsmore » and novel matter particles in extended gauge theories can be searched for and studied thoroughly. The machines provide unique opportunities for the discovery of particles in supersymmetric extensions of the Standard Model, the spectrum of Higgs particles, the supersymmetric partners of the electroweak gauge and Higgs bosons, and of the matter particles. High precision analyses of their properties and interactions will allow for extrapolations to energy scales close to the Planck scale where gravity becomes significant. In alternative scenarios, like compositeness models, novel matter particles and interactions can be discovered and investigated in the energy range above the existing colliders up to the TeV scale. Whatever scenario is realized in Nature, the discovery potential of e{sup +}e{sup -} linear colliders and the high-precision with which the properties of particles and their interactions can be analyzed, define an exciting physics programme complementary to hadron machines.« less

Electronically commutated motors for vehicle applications

NASA Astrophysics Data System (ADS)

Echolds, E. F.

1980-02-01

Two permanent magnet electronically commutated motors for electric vehicle traction are discussed. One, based on existing technology, produces 23 kW (peak) at 26,000 rpm, and 11 kW continuous at 18,000 rpm. The motor has a conventional design: a four-pole permanent magnet rotor and a three-phase stator similar to those used on ordinary induction motors. The other, advanced technology motor, is rated at 27 kW (peak) at 14,000 rpm, and 11 kW continuous at 10,500 rpm. The machine employs a permanent magnet rotor and a novel ironless stator design in an axial air gap, homopolar configuration. Comparison of the new motors with conventional brush type machines indicates potential for substantial cost savings.

Field-Oriented Control Of Induction Motors

NASA Technical Reports Server (NTRS)

Burrows, Linda M.; Roth, Mary Ellen; Zinger, Don S.

1993-01-01

Field-oriented control system provides for feedback control of torque or speed or both. Developed for use with commercial three-phase, 400-Hz, 208-V, 5-hp motor. Systems include resonant power supply operating at 20 kHz. Pulse-population-modulation subsystem selects individual pulses of 20-kHz single-phase waveform as needed to synthesize three waveforms of appropriate lower frequency applied to three phase windings of motor. Electric actuation systems using technology currently being built to peak powers of 70 kW. Amplitude of voltage of effective machine-frequency waveform determined by momentary frequency of pulses, while machine frequency determined by rate of repetition of overall temporal pattern of pulses. System enables independent control of both voltage and frequency.

Method of forming shrink-fit compression seal

NASA Technical Reports Server (NTRS)

Podgorski, T. J. (Inventor)

1977-01-01

A method for making a glass-to-metal seal is described. A domed metal enclosure having a machined seal ring is fitted to a glass post machined to a slight taper and to a desired surface finish. The metal part is then heated by induction in a vacuum. As the metal part heats and expands relative to the glass post, the metal seal ring, possessing a higher coefficient of expansion than the glass post, slides down the tapered post. Upon cooling, the seal ring crushes against the glass post forming the seal. The method results in a glass-to-metal seal possessing extremely good leak resistance, while the parts are kept clean and free of the contaminants.

Fundamental aspects of steady-state conversion of heat to work at the nanoscale

NASA Astrophysics Data System (ADS)

Benenti, Giuliano; Casati, Giulio; Saito, Keiji; Whitney, Robert S.

2017-06-01

In recent years, the study of heat to work conversion has been re-invigorated by nanotechnology. Steady-state devices do this conversion without any macroscopic moving parts, through steady-state flows of microscopic particles such as electrons, photons, phonons, etc. This review aims to introduce some of the theories used to describe these steady-state flows in a variety of mesoscopic or nanoscale systems. These theories are introduced in the context of idealized machines which convert heat into electrical power (heat-engines) or convert electrical power into a heat flow (refrigerators). In this sense, the machines could be categorized as thermoelectrics, although this should be understood to include photovoltaics when the heat source is the sun. As quantum mechanics is important for most such machines, they fall into the field of quantum thermodynamics. In many cases, the machines we consider have few degrees of freedom, however the reservoirs of heat and work that they interact with are assumed to be macroscopic. This review discusses different theories which can take into account different aspects of mesoscopic and nanoscale physics, such as coherent quantum transport, magnetic-field induced effects (including topological ones such as the quantum Hall effect), and single electron charging effects. It discusses the efficiency of thermoelectric conversion, and the thermoelectric figure of merit. More specifically, the theories presented are (i) linear response theory with or without magnetic fields, (ii) Landauer scattering theory in the linear response regime and far from equilibrium, (iii) Green-Kubo formula for strongly interacting systems within the linear response regime, (iv) rate equation analysis for small quantum machines with or without interaction effects, (v) stochastic thermodynamic for fluctuating small systems. In all cases, we place particular emphasis on the fundamental questions about the bounds on ideal machines. Can magnetic-fields change the bounds on power or efficiency? What is the relationship between quantum theories of transport and the laws of thermodynamics? Does quantum mechanics place fundamental bounds on heat to work conversion which are absent in the thermodynamics of classical systems?

SU-F-T-284: The Effect of Linear Accelerator Output Variation On the Quality of Patient Specific Rapid Arc Verification Plans

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sandhu, G; Cao, F; Szpala, S

2016-06-15

Purpose: The aim of the current study is to investigate the effect of machine output variation on the delivery of the RapidArc verification plans. Methods: Three verification plans were generated using Eclipse™ treatment planning system (V11.031) with plan normalization value 100.0%. These plans were delivered on the linear accelerators using ArcCHECK− device, with machine output 1.000 cGy/MU at calibration point. These planned and delivered dose distributions were used as reference plans. Additional plans were created in Eclipse− with normalization values ranging 92.80%–102% to mimic the machine output ranging 1.072cGy/MU-0.980cGy/MU, at the calibration point. These plans were compared against the referencemore » plans using gamma indices (3%, 3mm) and (2%, 2mm). Calculated gammas were studied for its dependence on machine output. Plans were considered passed if 90% of the points satisfy the defined gamma criteria. Results: The gamma index (3%, 3mm) was insensitive to output fluctuation within the output tolerance level (2% of calibration), and showed failures, when the machine output exceeds ≥3%. Gamma (2%, 2mm) was found to be more sensitive to the output variation compared to the gamma (3%, 3mm), and showed failures, when output exceeds ≥1.7%. The variation of the gamma indices with output variability also showed dependence upon the plan parameters (e.g. MLC movement and gantry rotation). The variation of the percentage points passing gamma criteria with output variation followed a non-linear decrease beyond the output tolerance level. Conclusion: Data from the limited plans and output conditions showed that gamma (2%, 2mm) is more sensitive to the output fluctuations compared to Gamma (3%,3mm). Work under progress, including detail data from a large number of plans and a wide range of output conditions, may be able to conclude the quantitative dependence of gammas on machine output, and hence the effect on the quality of delivered rapid arc plans.« less

Possible limits of plasma linear colliders

NASA Astrophysics Data System (ADS)

Zimmermann, F.

2017-07-01

Plasma linear colliders have been proposed as next or next-next generation energy-frontier machines for high-energy physics. I investigate possible fundamental limits on energy and luminosity of such type of colliders, considering acceleration, multiple scattering off plasma ions, intrabeam scattering, bremsstrahlung, and betatron radiation. The question of energy efficiency is also addressed.

Closed-loop torque feedback for a universal field-oriented controller

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.

Closed-loop torque feedback for a universal field-oriented controller

DOEpatents

De Doncker, R.W.A.A.; King, R.D.; Sanza, P.C.; Haefner, K.B.

1992-11-24

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation. 1 figure.

Closed-loop torque feedback for a universal field-oriented controller

DOE Office of Scientific and Technical Information (OSTI.GOV)

De Doncker, Rik W. A. A.; King, Robert D.; Sanza, Peter C.

A torque feedback system is employed in a universal field-oriented (UFO) controller to tune a torque-producing current command and a slip frequency command in order to achieve robust torque control of an induction machine even in the event of current regulator errors and during transitions between pulse width modulated (PWM) and square wave modes of operation.

Compensation for Harmonic Currents and Reactive Power in Wind Power Generation System using PWM Inverter

NASA Astrophysics Data System (ADS)

Shinohara, Katsuji; Shinhatsubo, Kurato; Iimori, Kenichi; Yamamoto, Kichiro; Saruban, Takamichi; Yamaemori, Takahiro

In recent year, consciousness of environmental problems is enhancing, and the price of the electric power purchased by an electric power company is established expensive for the power plant utilizing the natural energy. So, the introduction of the wind power generation is promoted in Japan. Generally, squirrel-cage induction machines are widely used as a generator in wind power generation system because of its small size, lightweight and low-cost. However, the induction machines do not have a source of excitation. Thus, it causes the inrush currents and the instantaneous voltage drop when the generator is directly connected to a power grid. To reduce the inrush currents, an AC power regulator is used. Wind power generations are frequently connected to and disconnected from the power grid. However, when the inrush currents are reduced, harmonic currents are caused by phase control of the AC power regulator. And the phase control of AC power regulator cannot control the power factor. Therefore, we propose the use of the AC power regulator to compensate for the harmonic currents and reactive power in the wind power generation system, and demonstrate the validity of its system by simulated and experimental results.

Integrating machine learning and physician knowledge to improve the accuracy of breast biopsy.

PubMed

Dutra, I; Nassif, H; Page, D; Shavlik, J; Strigel, R M; Wu, Y; Elezaby, M E; Burnside, E

2011-01-01

In this work we show that combining physician rules and machine learned rules may improve the performance of a classifier that predicts whether a breast cancer is missed on percutaneous, image-guided breast core needle biopsy (subsequently referred to as "breast core biopsy"). Specifically, we show how advice in the form of logical rules, derived by a sub-specialty, i.e. fellowship trained breast radiologists (subsequently referred to as "our physicians") can guide the search in an inductive logic programming system, and improve the performance of a learned classifier. Our dataset of 890 consecutive benign breast core biopsy results along with corresponding mammographic findings contains 94 cases that were deemed non-definitive by a multidisciplinary panel of physicians, from which 15 were upgraded to malignant disease at surgery. Our goal is to predict upgrade prospectively and avoid surgery in women who do not have breast cancer. Our results, some of which trended toward significance, show evidence that inductive logic programming may produce better results for this task than traditional propositional algorithms with default parameters. Moreover, we show that adding knowledge from our physicians into the learning process may improve the performance of the learned classifier trained only on data.

Characterizing the plasma of the Rotating Wall Machine

NASA Astrophysics Data System (ADS)

Hannum, David A.

The Rotating Wall Machine (RoWM) is a line-tied linear screw pinch built to study current-driven external kink modes. The plasma column is formed by an array of seven electrostatic washer guns which can also be biased to drive plasma current. The array allows independent control over the electron density ne and current density Jz profiles of the column. Internal measurements of the plasma have been made with singletip Langmuir and magnetic induction ("B-dot") probes for a range of bias currents (Ib = 0, 300, 500 A/gun). Streams from the individual guns are seen to merge at a distance of z ≈ 36 cm from the guns; the exact distance depends on the value of Ib. The density of the column is directly proportional to the Ohmic dissipation power, but the temperature stays at a low, uniform value (Te ≈ 3.5 eV) for each bias level. Electron densities are on the order of ne ˜10 20 m-3. The electron density expands radially (across the Bz guide field) as the plasma moves along the column, though the current density Jz mainly stays parallel to the field lines. The singletip Langmuir probe diagnostic is difficult to analyze for Ib = 500 A/gun plasmas and fails as Ib is raised beyond this level. Spectrographic analysis of the Halpha line indicates that the hydrogen plasmas are nearly fully ionized at each bias level. Azimuthal E x B rotation is axially and radially sheared; rotation slows as the plasma reaches the anode. Perpendicular diffusivity is consistent with the classical value, D⊥ ≈ 5 m2/sec, while parallel resistivity is seen to be twice the classical Spitzer value, 2 x 10-4 O m.

The Influences of Inductive Instruction and Resources on Students' Attitudes toward Reading: Evidence from PISA 2009

ERIC Educational Resources Information Center

Jhang, Fang-Hua

2014-01-01

The declining trend in the positive reading attitude of students' has concerned scholars. This paper aims to apply a 3-level hierarchical linear model to analyse how inductive instruction and resources influence both students' positive and negative attitudes towards reading. Approximately 470,000 15-year-old students, and their school principals,…

Principles of Induction Accelerators

NASA Astrophysics Data System (ADS)

Briggs*, Richard J.

The basic concepts involved in induction accelerators are introduced in this chapter. The objective is to provide a foundation for the more detailed coverage of key technology elements and specific applications in the following chapters. A wide variety of induction accelerators are discussed in the following chapters, from the high current linear electron accelerator configurations that have been the main focus of the original developments, to circular configurations like the ion synchrotrons that are the subject of more recent research. The main focus in the present chapter is on the induction module containing the magnetic core that plays the role of a transformer in coupling the pulsed power from the modulator to the charged particle beam. This is the essential common element in all these induction accelerators, and an understanding of the basic processes involved in its operation is the main objective of this chapter. (See [1] for a useful and complementary presentation of the basic principles in induction linacs.)

Response simulation and theoretical calibration of a dual-induction resistivity LWD tool

NASA Astrophysics Data System (ADS)

Xu, Wei; Ke, Shi-Zhen; Li, An-Zong; Chen, Peng; Zhu, Jun; Zhang, Wei

2014-03-01

In this paper, responses of a new dual-induction resistivity logging-while-drilling (LWD) tool in 3D inhomogeneous formation models are simulated by the vector finite element method (VFEM), the influences of the borehole, invaded zone, surrounding strata, and tool eccentricity are analyzed, and calibration loop parameters and calibration coefficients of the LWD tool are discussed. The results show that the tool has a greater depth of investigation than that of the existing electromagnetic propagation LWD tools and is more sensitive to azimuthal conductivity. Both deep and medium induction responses have linear relationships with the formation conductivity, considering optimal calibration loop parameters and calibration coefficients. Due to the different depths of investigation and resolution, deep induction and medium induction are affected differently by the formation model parameters, thereby having different correction factors. The simulation results can provide theoretical references for the research and interpretation of the dual-induction resistivity LWD tools.

Superconducting six-axis accelerometer

NASA Technical Reports Server (NTRS)

Paik, H. J.

1990-01-01

A new superconducting accelerometer, capable of measuring both linear and angular accelerations, is under development at the University of Maryland. A single superconducting proof mass is magnetically levitated against gravity or any other proof force. Its relative positions and orientations with respect to the platform are monitored by six superconducting inductance bridges sharing a single amplifier, called the Superconducting Quantum Interference Device (SQUID). The six degrees of freedom, the three linear acceleration components and the three angular acceleration components, of the platform are measured simultaneously. In order to improve the linearity and the dynamic range of the instrument, the demodulated outputs of the SQUID are fed back to appropriate levitation coils so that the proof mass remains at the null position for all six inductance bridges. The expected intrinsic noise of the instrument is 4 x 10(exp -12)m s(exp -2) Hz(exp -1/2) for linear acceleration and 3 x 10(exp -11) rad s(exp -2) Hz(exp -1/2) for angular acceleration in 1-g environment. In 0-g, the linear acceleration sensitivity of the superconducting accelerometer could be improved by two orders of magnitude. The design and the operating principle of a laboratory prototype of the new instrument is discussed.

Condition monitoring of Electric Components

NASA Astrophysics Data System (ADS)

Zaman, Ishtiaque

A universal non-intrusive model of a flexible antenna array is presented in this paper to monitor and identify the failures in electric machines. This adjustable antenna is designed to serve the purpose of condition monitoring of a vast range of electrical components including Induction Motor (IM), Printed Circuit Board (PCB), Synchronous Reluctance Motor (SRM), Permanent Magnet Synchronous Machine (PMSM) etc. by capturing the low frequency magnetic field radiated around these machines. The basic design and specification of the proposed antenna array for low frequency components is portrayed first. The design of the antenna is adjustable to fit for an extensive variety of segments. Subsequent to distinguishing the design and specifications of the antenna, the ideal area of the most delicate stray field has been identified for healthy current streaming around the machineries. Following this, short circuit representing faulty situation has been introduced and compared with the healthy cases. Precision has been found recognizing the faults using this one generic model of Antenna and the results are presented for three different machines i.e. IM, SRM and PMSM. Finite element method has been used to design the antenna and detect the optimum location and faults in the machines. Finally, a 3D Printer is proposed to be employed to build the antenna as per the details tended to in this paper contingent upon the power segments.

Application of machine learning techniques to analyse the effects of physical exercise in ventricular fibrillation.

PubMed

Caravaca, Juan; Soria-Olivas, Emilio; Bataller, Manuel; Serrano, Antonio J; Such-Miquel, Luis; Vila-Francés, Joan; Guerrero, Juan F

2014-02-01

This work presents the application of machine learning techniques to analyse the influence of physical exercise in the physiological properties of the heart, during ventricular fibrillation. To this end, different kinds of classifiers (linear and neural models) are used to classify between trained and sedentary rabbit hearts. The use of those classifiers in combination with a wrapper feature selection algorithm allows to extract knowledge about the most relevant features in the problem. The obtained results show that neural models outperform linear classifiers (better performance indices and a better dimensionality reduction). The most relevant features to describe the benefits of physical exercise are those related to myocardial heterogeneity, mean activation rate and activation complexity. © 2013 Published by Elsevier Ltd.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

The Relation of Parental Guilt Induction to Child Internalizing Problems When a Caregiver Has a History of Depression

PubMed Central

Rakow, Aaron; McKee, Laura; Coffelt, Nicole; Champion, Jennifer; Fear, Jessica; Compas, Bruce

2009-01-01

The purpose of this study was to examine the relation between parental guilt induction and child internalizing problems in families where a caregiver had experienced depression. A total of 107 families, including 146 children (age 9–15), participated. Child-reported parental guilt induction, as well as three more traditionally studied parenting behaviors (warmth/involvement, monitoring, and discipline), were assessed, as was parent-report of child internalizing problem behavior. Linear Mixed Models Analysis indicated parental guilt induction was positively related to child internalizing problems in the context of the remaining three parenting behaviors. Implications of the findings for prevention and intervention parenting programs are considered. PMID:20090863

Prediction of Human Intestinal Absorption of Compounds Using Artificial Intelligence Techniques.

PubMed

Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

2017-01-01

Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of intestinal absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds. Prediction accuracy of Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis for prediction of intestinal absorption of compounds was found to be 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A novel semi-transductive learning framework for efficient atypicality detection in chest radiographs

NASA Astrophysics Data System (ADS)

Alzubaidi, Mohammad; Balasubramanian, Vineeth; Patel, Ameet; Panchanathan, Sethuraman; Black, John A., Jr.

2012-03-01

Inductive learning refers to machine learning algorithms that learn a model from a set of training data instances. Any test instance is then classified by comparing it to the learned model. When the set of training instances lend themselves well to modeling, the use of a model substantially reduces the computation cost of classification. However, some training data sets are complex, and do not lend themselves well to modeling. Transductive learning refers to machine learning algorithms that classify test instances by comparing them to all of the training instances, without creating an explicit model. This can produce better classification performance, but at a much higher computational cost. Medical images vary greatly across human populations, constituting a data set that does not lend itself well to modeling. Our previous work showed that the wide variations seen across training sets of "normal" chest radiographs make it difficult to successfully classify test radiographs with an inductive (modeling) approach, and that a transductive approach leads to much better performance in detecting atypical regions. The problem with the transductive approach is its high computational cost. This paper develops and demonstrates a novel semi-transductive framework that can address the unique challenges of atypicality detection in chest radiographs. The proposed framework combines the superior performance of transductive methods with the reduced computational cost of inductive methods. Our results show that the proposed semitransductive approach provides both effective and efficient detection of atypical regions within a set of chest radiographs previously labeled by Mayo Clinic expert thoracic radiologists.

A linearly controlled direct-current power source for high-current inductive loads in a magnetic suspension wind tunnel

NASA Technical Reports Server (NTRS)

Tripp, John S.; Daniels, Taumi S.

1990-01-01

The NASA Langley 6 inch magnetic suspension and balance system (MSBS) requires an independently controlled bidirectional DC power source for each of six positioning electromagnets. These electromagnets provide five-degree-of-freedom control over a suspended aerodynamic test model. Existing power equipment, which employs resistance coupled thyratron controlled rectifiers as well as AC to DC motor generator converters, is obsolete, inefficient, and unreliable. A replacement six phase bidirectional controlled bridge rectifier is proposed, which employs power MOSFET switches sequenced by hybrid analog/digital circuits. Full load efficiency is 80 percent compared to 25 percent for the resistance coupled thyratron system. Current feedback provides high control linearity, adjustable current limiting, and current overload protection. A quenching circuit suppresses inductive voltage impulses. It is shown that 20 kHz interference from positioning magnet power into MSBS electromagnetic model position sensors results predominantly from capacitively coupled electric fields. Hence, proper shielding and grounding techniques are necessary. Inductively coupled magnetic interference is negligible.

Spin dynamics in storage rings and linear accelerators

DOE Office of Scientific and Technical Information (OSTI.GOV)

Irwin, J.

1994-12-01

The purpose of these lectures is to survey the subject of spin dynamics in accelerators: to give a sense of the underlying physics, the typical analytic and numeric methods used, and an overview of results achieved. Consideration will be limited to electrons and protons. Examples of experimental and theoretical results in both linear and circular machines are included.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Powering the programmed nanostructure and function of gold nanoparticles with catenated DNA machines

NASA Astrophysics Data System (ADS)

Elbaz, Johann; Cecconello, Alessandro; Fan, Zhiyuan; Govorov, Alexander O.; Willner, Itamar

2013-06-01

DNA nanotechnology is a rapidly developing research area in nanoscience. It includes the development of DNA machines, tailoring of DNA nanostructures, application of DNA nanostructures for computing, and more. Different DNA machines were reported in the past and DNA-guided assembly of nanoparticles represents an active research effort in DNA nanotechnology. Several DNA-dictated nanoparticle structures were reported, including a tetrahedron, a triangle or linear nanoengineered nanoparticle structures; however, the programmed, dynamic reversible switching of nanoparticle structures and, particularly, the dictated switchable functions emerging from the nanostructures, are missing elements in DNA nanotechnology. Here we introduce DNA catenane systems (interlocked DNA rings) as molecular DNA machines for the programmed, reversible and switchable arrangement of different-sized gold nanoparticles. We further demonstrate that the machine-powered gold nanoparticle structures reveal unique emerging switchable spectroscopic features, such as plasmonic coupling or surface-enhanced fluorescence.

A Real-Time Tool Positioning Sensor for Machine-Tools

PubMed Central

Ruiz, Antonio Ramon Jimenez; Rosas, Jorge Guevara; Granja, Fernando Seco; Honorato, Jose Carlos Prieto; Taboada, Jose Juan Esteve; Serrano, Vicente Mico; Jimenez, Teresa Molina

2009-01-01

In machining, natural oscillations, and elastic, gravitational or temperature deformations, are still a problem to guarantee the quality of fabricated parts. In this paper we present an optical measurement system designed to track and localize in 3D a reference retro-reflector close to the machine-tool's drill. The complete system and its components are described in detail. Several tests, some static (including impacts and rotations) and others dynamic (by executing linear and circular trajectories), were performed on two different machine tools. It has been integrated, for the first time, a laser tracking system into the position control loop of a machine-tool. Results indicate that oscillations and deformations close to the tool can be estimated with micrometric resolution and a bandwidth from 0 to more than 100 Hz. Therefore this sensor opens the possibility for on-line compensation of oscillations and deformations. PMID:22408472

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Gray, A.

2014-04-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors. This is likely of particular interest to the radio astronomy community given, for example, that survey projects contain groups dedicated to this topic. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

Scalable Machine Learning for Massive Astronomical Datasets

NASA Astrophysics Data System (ADS)

Ball, Nicholas M.; Astronomy Data Centre, Canadian

2014-01-01

We present the ability to perform data mining and machine learning operations on a catalog of half a billion astronomical objects. This is the result of the combination of robust, highly accurate machine learning algorithms with linear scalability that renders the applications of these algorithms to massive astronomical data tractable. We demonstrate the core algorithms kernel density estimation, K-means clustering, linear regression, nearest neighbors, random forest and gradient-boosted decision tree, singular value decomposition, support vector machine, and two-point correlation function. Each of these is relevant for astronomical applications such as finding novel astrophysical objects, characterizing artifacts in data, object classification (including for rare objects), object distances, finding the important features describing objects, density estimation of distributions, probabilistic quantities, and exploring the unknown structure of new data. The software, Skytree Server, runs on any UNIX-based machine, a virtual machine, or cloud-based and distributed systems including Hadoop. We have integrated it on the cloud computing system of the Canadian Astronomical Data Centre, the Canadian Advanced Network for Astronomical Research (CANFAR), creating the world's first cloud computing data mining system for astronomy. We demonstrate results showing the scaling of each of our major algorithms on large astronomical datasets, including the full 470,992,970 objects of the 2 Micron All-Sky Survey (2MASS) Point Source Catalog. We demonstrate the ability to find outliers in the full 2MASS dataset utilizing multiple methods, e.g., nearest neighbors, and the local outlier factor. 2MASS is used as a proof-of-concept dataset due to its convenience and availability. These results are of interest to any astronomical project with large and/or complex datasets that wishes to extract the full scientific value from its data.

An Application of the Vandermonde Determinant

ERIC Educational Resources Information Center

Xu, Junqin; Zhao, Likuan

2006-01-01

Eigenvalue is an important concept in Linear Algebra. It is well known that the eigenvectors corresponding to different eigenvalues of a square matrix are linear independent. In most of the existing textbooks, this result is proven using mathematical induction. In this note, a new proof using Vandermonde determinant is given. It is shown that this…

Double Arm Linkage precision Linear motion (DALL) Carriage, a simplified, rugged, high performance linear motion stage for the moving mirror of an Fourier Transform Spectrometer or other system requiring precision linear motion

NASA Astrophysics Data System (ADS)

Johnson, Kendall B.; Hopkins, Greg

2017-08-01

The Double Arm Linkage precision Linear motion (DALL) carriage has been developed as a simplified, rugged, high performance linear motion stage. Initially conceived as a moving mirror stage for the moving mirror of a Fourier Transform Spectrometer (FTS), it is applicable to any system requiring high performance linear motion. It is based on rigid double arm linkages connecting a base to a moving carriage through flexures. It is a monolithic design. The system is fabricated from one piece of material including the flexural elements, using high precision machining. The monolithic design has many advantages. There are no joints to slip or creep and there are no CTE (coefficient of thermal expansion) issues. This provides a stable, robust design, both mechanically and thermally and is expected to provide a wide operating temperature range, including cryogenic temperatures, and high tolerance to vibration and shock. Furthermore, it provides simplicity and ease of implementation, as there is no assembly or alignment of the mechanism. It comes out of the machining operation aligned and there are no adjustments. A prototype has been fabricated and tested, showing superb shear performance and very promising tilt performance. This makes it applicable to both corner cube and flat mirror FTS systems respectively.

A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis

NASA Astrophysics Data System (ADS)

Khawaja, Taimoor Saleem

A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. An efficient yet powerful Least Squares Support Vector Machine (LS-SVM) algorithm, set within a Bayesian Inference framework, not only allows for the development of real-time algorithms for diagnosis and prognosis but also provides a solid theoretical framework to address key concepts related to classification for diagnosis and regression modeling for prognosis. SVM machines are founded on the principle of Structural Risk Minimization (SRM) which tends to find a good trade-off between low empirical risk and small capacity. The key features in SVM are the use of non-linear kernels, the absence of local minima, the sparseness of the solution and the capacity control obtained by optimizing the margin. The Bayesian Inference framework linked with LS-SVMs allows a probabilistic interpretation of the results for diagnosis and prognosis. Additional levels of inference provide the much coveted features of adaptability and tunability of the modeling parameters. The two main modules considered in this research are fault diagnosis and failure prognosis. With the goal of designing an efficient and reliable fault diagnosis scheme, a novel Anomaly Detector is suggested based on the LS-SVM machines. The proposed scheme uses only baseline data to construct a 1-class LS-SVM machine which, when presented with online data is able to distinguish between normal behavior and any abnormal or novel data during real-time operation. The results of the scheme are interpreted as a posterior probability of health (1 - probability of fault). As shown through two case studies in Chapter 3, the scheme is well suited for diagnosing imminent faults in dynamical non-linear systems. Finally, the failure prognosis scheme is based on an incremental weighted Bayesian LS-SVR machine. It is particularly suited for online deployment given the incremental nature of the algorithm and the quick optimization problem solved in the LS-SVR algorithm. By way of kernelization and a Gaussian Mixture Modeling (GMM) scheme, the algorithm can estimate "possibly" non-Gaussian posterior distributions for complex non-linear systems. An efficient regression scheme associated with the more rigorous core algorithm allows for long-term predictions, fault growth estimation with confidence bounds and remaining useful life (RUL) estimation after a fault is detected. The leading contributions of this thesis are (a) the development of a novel Bayesian Anomaly Detector for efficient and reliable Fault Detection and Identification (FDI) based on Least Squares Support Vector Machines, (b) the development of a data-driven real-time architecture for long-term Failure Prognosis using Least Squares Support Vector Machines, (c) Uncertainty representation and management using Bayesian Inference for posterior distribution estimation and hyper-parameter tuning, and finally (d) the statistical characterization of the performance of diagnosis and prognosis algorithms in order to relate the efficiency and reliability of the proposed schemes.

Effective switching frequency multiplier inverter

DOEpatents

Su, Gui-Jia [Oak Ridge, TN; Peng, Fang Z [Okemos, MI

2007-08-07

A switching frequency multiplier inverter for low inductance machines that uses parallel connection of switches and each switch is independently controlled according to a pulse width modulation scheme. The effective switching frequency is multiplied by the number of switches connected in parallel while each individual switch operates within its limit of switching frequency. This technique can also be used for other power converters such as DC/DC, AC/DC converters.

Proceedings: USACERL/ASCE First Joint Conference on Expert Systems, 29-30 June 1988

DTIC Science & Technology

1989-01-01

Wong KOWLEDGE -BASED GRAPHIC DIALOGUES . o ...................... .... 80 D. L Mw 4 CONTENTS (Cont’d) ABSTRACTS ACCEPTED FOR PUBLICATION MAD, AN EXPERT...methodology of inductive shallow modeling was developed. Inductive systems may become powerful shallow modeling tools applicable to a large class of...analysis was conducted using a statistical package, Trajectories. Four different types of relationships were analyzed: linear, logarithmic, power , and

Analysis, design, and testing of a low cost, direct force command linear proof mass actuator for structural control

NASA Technical Reports Server (NTRS)

Slater, G. L.; Shelley, Stuart; Jacobson, Mark

1993-01-01

In this paper, the design, analysis, and test of a low cost, linear proof mass actuator for vibration control is presented. The actuator is based on a linear induction coil from a large computer disk drive. Such disk drives are readily available and provide the linear actuator, current feedback amplifier, and power supply for a highly effective, yet inexpensive, experimental laboratory actuator. The device is implemented as a force command input system, and the performance is virtually the same as other, more sophisticated, linear proof mass systems.

Energy harvesting using AC machines with high effective pole count

NASA Astrophysics Data System (ADS)

Geiger, Richard Theodore

In this thesis, ways to improve the power conversion of rotating generators at low rotor speeds in energy harvesting applications were investigated. One method is to increase the pole count, which increases the generator back-emf without also increasing the I2R losses, thereby increasing both torque density and conversion efficiency. One machine topology that has a high effective pole count is a hybrid "stepper" machine. However, the large self inductance of these machines decreases their power factor and hence the maximum power that can be delivered to a load. This effect can be cancelled by the addition of capacitors in series with the stepper windings. A circuit was designed and implemented to automatically vary the series capacitance over the entire speed range investigated. The addition of the series capacitors improved the power output of the stepper machine by up to 700%. At low rotor speeds, with the addition of series capacitance, the power output of the hybrid "stepper" was more than 200% that of a similarly sized PMDC brushed motor. Finally, in this thesis a hybrid lumped parameter / finite element model was used to investigate the impact of number, shape and size of the rotor and stator teeth on machine performance. A typical off-the-shelf hybrid stepper machine has significant cogging torque by design. This cogging torque is a major problem in most small energy harvesting applications. In this thesis it was shown that the cogging and ripple torque can be dramatically reduced. These findings confirm that high-pole-count topologies, and specifically the hybrid stepper configuration, are an attractive choice for energy harvesting applications.

Grumman WS33 wind system: prototype construction and testing, Phase II technical report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adler, F.M.; Henton, P.; King, P.W.

1980-11-01

The prototype fabrication and testing of the 8 kW small wind energy conversion system are reported. The turbine is a three-bladed, down-wind machine designed to interface directly with an electrical utility network. The machine as finally fabricated is rated at 15 kW at 24 mpH and peak power of 18 kW at 35 mph. Utility compatible electrical power is generated in winds between a cut-in speed of 9 mph and a cut-out speed of 35 mph by using the torque characteristics of the unit's induction generator combined with the rotor aerodynamics to maintain essentially constant speed. Inspection procedures, pre-delivery testing,more » and a cost analysis are included.« less

Review of the energy check of an electron-only linear accelerator over a 6 year period: sensitivity of the technique to energy shift.

PubMed

Biggs, Peter J

2003-04-01

The calibration and monthly QA of an electron-only linear accelerator dedicated to intra-operative radiation therapy has been reviewed. Since this machine is calibrated prior to every procedure, there was no necessity to adjust the output calibration at any time except, perhaps, when the magnetron is changed, provided the machine output is reasonably stable. This gives a unique opportunity to study the dose output of the machine per monitor unit, variation in the timer error, flatness and symmetry of the beam and the energy check as a function of time. The results show that, although the dose per monitor unit varied within +/- 2%, the timer error within +/- 0.005 MU and the asymmetry within 1-2%, none of these parameters showed any systematic change with time. On the other hand, the energy check showed a linear drift with time for 6, 9, and 12 MeV (2.1, 3.5, and 2.5%, respectively, over 5 years), while at 15 and 18 MeV, the energy check was relatively constant. It is further shown that based on annual calibrations and RPC TLD checks, the energy of each beam is constant and that therefore the energy check is an exquisitely sensitive one. The consistency of the independent checks is demonstrated.

Wear resistance of machine tools' bionic linear rolling guides by laser cladding

NASA Astrophysics Data System (ADS)

Wang, Yiqiang; Liu, Botao; Guo, Zhengcai

2017-06-01

In order to improve the rolling wear resistance (RWR) of linear rolling guides (LRG) as well as prolong the life of machine tools, various shape samples with different units spaces ranged from 1 to 5 mm are designed through the observation of animals in the desert and manufactured by laser cladding. Wear resistance tests reproducing closely the real operational condition are conducted by using a homemade linear reciprocating wear test machine, and wear resistance is evaluated by means of weight loss measurement. Results indicate that the samples with bionic units have better RWR than the untreated one, of which the reticulate treated sample with unit space 3 mm present the best RWR. More specifically, among the punctuate treated samples, the mass loss increases with the increase of unit space; among the striate treated samples, the mass loss changes slightly with the increase of unit space, attaining a minimum at the unit space of 4 mm; among the reticulate treated samples, with the increase of unit space, the mass loss initially decreases, but turns to increase after reaching a minimum at the unit space of 3 mm. Additionally, the samples with striate shape perform better wear resistance than the other shape groups on the whole. From the ratio value of laser treated area to contacted area perspective, that the samples with ratio value between 0.15 and 0.3 possess better wear resistance is concluded.

Comparison of Classifiers for Decoding Sensory and Cognitive Information from Prefrontal Neuronal Populations

PubMed Central

Astrand, Elaine; Enel, Pierre; Ibos, Guilhem; Dominey, Peter Ford; Baraduc, Pierre; Ben Hamed, Suliann

2014-01-01

Decoding neuronal information is important in neuroscience, both as a basic means to understand how neuronal activity is related to cerebral function and as a processing stage in driving neuroprosthetic effectors. Here, we compare the readout performance of six commonly used classifiers at decoding two different variables encoded by the spiking activity of the non-human primate frontal eye fields (FEF): the spatial position of a visual cue, and the instructed orientation of the animal's attention. While the first variable is exogenously driven by the environment, the second variable corresponds to the interpretation of the instruction conveyed by the cue; it is endogenously driven and corresponds to the output of internal cognitive operations performed on the visual attributes of the cue. These two variables were decoded using either a regularized optimal linear estimator in its explicit formulation, an optimal linear artificial neural network estimator, a non-linear artificial neural network estimator, a non-linear naïve Bayesian estimator, a non-linear Reservoir recurrent network classifier or a non-linear Support Vector Machine classifier. Our results suggest that endogenous information such as the orientation of attention can be decoded from the FEF with the same accuracy as exogenous visual information. All classifiers did not behave equally in the face of population size and heterogeneity, the available training and testing trials, the subject's behavior and the temporal structure of the variable of interest. In most situations, the regularized optimal linear estimator and the non-linear Support Vector Machine classifiers outperformed the other tested decoders. PMID:24466019

Design and performance tests of a distributed power-driven wheel loader

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2010-03-01

An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.

Design and performance tests of a distributed power-driven wheel loader

NASA Astrophysics Data System (ADS)

Jin, Xiaolin; Shi, Laide; Bian, Yongming

2009-12-01

An improved ZLM15B distributed power-driven wheel loader was designed, whose travel and brake system was accomplished by two permanent magnet synchronous motorized-wheels instead of traditional mechanical components, and whose hydraulic systems such as the working device system and steering system were both actuated by an induction motor. All above systems were flexibly coupled with 3-phase 380VAC electric power with which the diesel engine power is replaced. On the level cement road, traveling, braking, traction and steering tests were carried out separately under non-load and heavy-load conditions. Data show that machine speed is 5 km/h around and travel efficiency of motorized-wheels is above 95%; that machine braking deceleration is between 0.5 and 0.64 m/s2 but efficiency of motorized-wheels is less than 10%; that maximum machine traction is above 2t while efficiency of motorized-wheels is more than 90% and that adaptive differential steering can be smoothly achieved by motorized-wheels.

Generalized SMO algorithm for SVM-based multitask learning.

PubMed

Cai, Feng; Cherkassky, Vladimir

2012-06-01

Exploiting additional information to improve traditional inductive learning is an active research area in machine learning. In many supervised-learning applications, training data can be naturally separated into several groups, and incorporating this group information into learning may improve generalization. Recently, Vapnik proposed a general approach to formalizing such problems, known as "learning with structured data" and its support vector machine (SVM) based optimization formulation called SVM+. Liang and Cherkassky showed the connection between SVM+ and multitask learning (MTL) approaches in machine learning, and proposed an SVM-based formulation for MTL called SVM+MTL for classification. Training the SVM+MTL classifier requires the solution of a large quadratic programming optimization problem which scales as O(n(3)) with sample size n. So there is a need to develop computationally efficient algorithms for implementing SVM+MTL. This brief generalizes Platt's sequential minimal optimization (SMO) algorithm to the SVM+MTL setting. Empirical results show that, for typical SVM+MTL problems, the proposed generalized SMO achieves over 100 times speed-up, in comparison with general-purpose optimization routines.

Objective Assessment of an Ionic Footbath (IonCleanse): Testing Its Ability to Remove Potentially Toxic Elements from the Body

PubMed Central

Kennedy, Deborah A.; Cooley, Kieran; Einarson, Thomas R.; Seely, Dugald

2012-01-01

Ionic footbaths are often used in holistic health centres and spas to aid in detoxification; however, claims that these machines eliminate toxins from the body have not been rigorously evaluated. In this proof-of-principle study, we sought to measure the release of potentially toxic elements from ionic footbaths into distilled and tap water with and without feet. Water samples were collected and analyzed following 30-minute ionic footbath sessions without feet using both distilled (n = 1) and tap water (n = 6) and following four ionic footbaths using tap water (once/week for 4 weeks) in six healthy participants. Urine collection samples were analyzed at four points during the study. Hair samples were analyzed for element concentrations at baseline and study conclusion. Contrary to claims made for the machine, there does not appear to be any specific induction of toxic element release through the feet when running the machine according to specifications. PMID:22174728

An Analysis of the Multiple Objective Capital Budgeting Problem via Fuzzy Linear Integer (0-1) Programming.

DTIC Science & Technology

1980-05-31

34 International Journal of Man- Machine Studies , Vol. 9, No. 1, 1977, pp. 1-68. [16] Zimmermann, H. J., Theory and Applications of Fuzzy Sets, Institut...Boston, Inc., Hingham, MA, 1978. [18] Yager, R. R., "Multiple Objective Decision-Making Using Fuzzy Sets," International Journal of Man- Machine Studies ...Professor of Industria Engineering ... iv t TABLE OF CONTENTS page ABSTRACT .. .. . ...... . .... ...... ........ iii LIST OF TABLES

A new measuring machine in Paris

NASA Technical Reports Server (NTRS)

Guibert, J.; Charvin, P.

1984-01-01

A new photographic measuring machine is under construction at the Paris Observatory. The amount of transmitted light is measured by a linear array of 1024 photodiodes. Carriage control, data acquisition and on line processing are performed by microprocessors, a S.E.L. 32/27 computer, and an AP 120-B Array Processor. It is expected that a Schmidt telescope plate of size 360 mm square will be scanned in one hour with pixel size of ten microns.

Monocoil reciprocating permanent magnet electric machine with self-centering force

NASA Technical Reports Server (NTRS)

Bhate, Suresh K. (Inventor); Vitale, Nicholas G. (Inventor)

1989-01-01

A linear reciprocating machine has a tubular outer stator housing a coil, a plunger and an inner stator. The plunger has four axially spaced rings of radially magnetized permanent magnets which cooperate two at a time with the stator to complete first or second opposite magnetic paths. The four rings of magnets and the stators are arranged so that the stroke of the plunger is independent of the axial length of the coil.

Productive High Performance Parallel Programming with Auto-tuned Domain-Specific Embedded Languages

DTIC Science & Technology

2013-01-02

Compilation JVM Java Virtual Machine KB Kilobyte KDT Knowledge Discovery Toolbox LAPACK Linear Algebra Package LLVM Low-Level Virtual Machine LOC Lines...different starting points. Leo Meyerovich also helped solidify some of the ideas here in discussions during Par Lab retreats. I would also like to thank...multi-timestep computations by blocking in both time and space. 88 Implementation Output Approx DSL Type Language Language Parallelism LoC Graphite

Asymptotic Representations of Quantum Affine Superalgebras

NASA Astrophysics Data System (ADS)

Zhang, Huafeng

2017-08-01

We study representations of the quantum affine superalgebra associated with a general linear Lie superalgebra. In the spirit of Hernandez-Jimbo, we construct inductive systems of Kirillov-Reshetikhin modules based on a cyclicity result that we established previously on tensor products of these modules, and realize their inductive limits as modules over its Borel subalgebra, the so-called q-Yangian. A new generic asymptotic limit of the same inductive systems is proposed, resulting in modules over the full quantum affine superalgebra. We derive generalized Baxter's relations in the sense of Frenkel-Hernandez for representations of the full quantum group.

High-voltage, low-inductance gas switch

DOEpatents

Gruner, Frederick R.; Stygar, William A.

2016-03-22

A low-inductance, air-insulated gas switch uses a de-enhanced annular trigger ring disposed between two opposing high voltage electrodes. The switch is DC chargeable to 200 kilovolts or more, triggerable, has low jitter (5 ns or less), has pre-fire and no-fire rates of no more than one in 10,000 shots, and has a lifetime of greater than 100,000 shots. Importantly, the switch also has a low inductance (less than 60 nH) and the ability to conduct currents with less than 100 ns rise times. The switch can be used with linear transformer drives or other pulsed-power systems.

Influence of magnet eddy current on magnetization characteristics of variable flux memory machine

NASA Astrophysics Data System (ADS)

Yang, Hui; Lin, Heyun; Zhu, Z. Q.; Lyu, Shukang

2018-05-01

In this paper, the magnet eddy current characteristics of a newly developed variable flux memory machine (VFMM) is investigated. Firstly, the machine structure, non-linear hysteresis characteristics and eddy current modeling of low coercive force magnet are described, respectively. Besides, the PM eddy current behaviors when applying the demagnetizing current pulses are unveiled and investigated. The mismatch of the required demagnetization currents between the cases with or without considering the magnet eddy current is identified. In addition, the influences of the magnet eddy current on the demagnetization effect of VFMM are analyzed. Finally, a prototype is manufactured and tested to verify the theoretical analyses.

Energy-free machine learning force field for aluminum.

PubMed

Kruglov, Ivan; Sergeev, Oleg; Yanilkin, Alexey; Oganov, Artem R

2017-08-17

We used the machine learning technique of Li et al. (PRL 114, 2015) for molecular dynamics simulations. Atomic configurations were described by feature matrix based on internal vectors, and linear regression was used as a learning technique. We implemented this approach in the LAMMPS code. The method was applied to crystalline and liquid aluminum and uranium at different temperatures and densities, and showed the highest accuracy among different published potentials. Phonon density of states, entropy and melting temperature of aluminum were calculated using this machine learning potential. The results are in excellent agreement with experimental data and results of full ab initio calculations.

Electricity and Magnetism

NASA Astrophysics Data System (ADS)

Glazebrook, R. T.

2016-10-01

1. Electrostatics: fundamental facts; 2. Electricity as a measurable quantity; 3. Measurement of electric force and potential; 4. Condensers; 5. Electrical machines; 6. Measurement of potential and electric force; 7. Magnetic attraction and repulsion; 8. Laws of magnetic force; 9. Experiments with magnets; 10. Magnetic calculations; 11. Magnetic measurements; 12. Terrestrial magnetism; 13. The electric current; 14. Relation between electromagnetic force and current; 15. Measurement of current; 16. Measurement of resistance and electromotive force; 17. Measurement of quantity of electricity, condensers; 18. Thermal activity of a current; 19. The voltaic cell (theory); 20. Electromagnetism; 21. Magnetisation of iron; 22. Electromagnetic instruments; 23. Electromagnetic induction; 24. Applications of electromagnetic induction; 25. Telegraphy and telephony; 26. Electric waves; 27. Transference of electricity through gases: corpuscles and electrons; Answers to examples; Index.

The operation of a single-sided linear induction motor with squirrel-cage and solid-steel reaction rails

NASA Astrophysics Data System (ADS)

Eastham, A. R.; Katz, R. M.

1980-09-01

Two test programs have been conducted to evaluate the performance of a single-sided linear induction motor with a squirrel-cage reaction rail and with a solid steel reaction rail. A 1.73-m-long six-pole stator interacted with the rails mounted on the rim of a 7.6-m-diam wheel. A 64-channel data acquisition system allowed tests to be performed over a wide range of operating conditions at speeds up to 20 m/sec. Typical test results which compare and contrast the mechanical, electrical and magnetic behavior of the SLIMs are presented. The test data are being used to assess the SLIM as an integrated suspension/propulsion system and for other transportation applications.

Center for Parallel Optimization.

DTIC Science & Technology

1996-03-19

A NEW OPTIMIZATION BASED APPROACH TO IMPROVING GENERALIZATION IN MACHINE LEARNING HAS BEEN PROPOSED AND COMPUTATIONALLY VALIDATED ON SIMPLE LINEAR MODELS AS WELL AS ON HIGHLY NONLINEAR SYSTEMS SUCH AS NEURAL NETWORKS.

Building "e-rater"® Scoring Models Using Machine Learning Methods. Research Report. ETS RR-16-04

ERIC Educational Resources Information Center

Chen, Jing; Fife, James H.; Bejar, Isaac I.; Rupp, André A.

2016-01-01

The "e-rater"® automated scoring engine used at Educational Testing Service (ETS) scores the writing quality of essays. In the current practice, e-rater scores are generated via a multiple linear regression (MLR) model as a linear combination of various features evaluated for each essay and human scores as the outcome variable. This…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tsai, C. -Y.; Douglas, D.; Li, R.

Microbunching instability (MBI) has been one of the most challenging issues in designs of magnetic chicanes for short-wavelength free-electron lasers or linear colliders, as well as those of transport lines for recirculating or energy-recovery-linac machines. To quantify MBI for a recirculating machine and for more systematic analyses, we have recently developed a linear Vlasov solver and incorporated relevant collective effects into the code, including the longitudinal space charge, coherent synchrotron radiation, and linac geometric impedances, with extension of the existing formulation to include beam acceleration. In our code, we semianalytically solve the linearized Vlasov equation for microbunching amplification factor formore » an arbitrary linear lattice. In this study we apply our code to beam line lattices of two comparative isochronous recirculation arcs and one arc lattice preceded by a linac section. The resultant microbunching gain functions and spectral responses are presented, with some results compared to particle tracking simulation by elegant (M. Borland, APS Light Source Note No. LS-287, 2002). These results demonstrate clearly the impact of arc lattice design on the microbunching development. Lastly, the underlying physics with inclusion of those collective effects is elucidated and the limitation of the existing formulation is also discussed.« less

Koopman Operator Framework for Time Series Modeling and Analysis

NASA Astrophysics Data System (ADS)

Surana, Amit

2018-01-01

We propose an interdisciplinary framework for time series classification, forecasting, and anomaly detection by combining concepts from Koopman operator theory, machine learning, and linear systems and control theory. At the core of this framework is nonlinear dynamic generative modeling of time series using the Koopman operator which is an infinite-dimensional but linear operator. Rather than working with the underlying nonlinear model, we propose two simpler linear representations or model forms based on Koopman spectral properties. We show that these model forms are invariants of the generative model and can be readily identified directly from data using techniques for computing Koopman spectral properties without requiring the explicit knowledge of the generative model. We also introduce different notions of distances on the space of such model forms which is essential for model comparison/clustering. We employ the space of Koopman model forms equipped with distance in conjunction with classical machine learning techniques to develop a framework for automatic feature generation for time series classification. The forecasting/anomaly detection framework is based on using Koopman model forms along with classical linear systems and control approaches. We demonstrate the proposed framework for human activity classification, and for time series forecasting/anomaly detection in power grid application.

BLAS- BASIC LINEAR ALGEBRA SUBPROGRAMS

NASA Technical Reports Server (NTRS)

Krogh, F. T.

1994-01-01

The Basic Linear Algebra Subprogram (BLAS) library is a collection of FORTRAN callable routines for employing standard techniques in performing the basic operations of numerical linear algebra. The BLAS library was developed to provide a portable and efficient source of basic operations for designers of programs involving linear algebraic computations. The subprograms available in the library cover the operations of dot product, multiplication of a scalar and a vector, vector plus a scalar times a vector, Givens transformation, modified Givens transformation, copy, swap, Euclidean norm, sum of magnitudes, and location of the largest magnitude element. Since these subprograms are to be used in an ANSI FORTRAN context, the cases of single precision, double precision, and complex data are provided for. All of the subprograms have been thoroughly tested and produce consistent results even when transported from machine to machine. BLAS contains Assembler versions and FORTRAN test code for any of the following compilers: Lahey F77L, Microsoft FORTRAN, or IBM Professional FORTRAN. It requires the Microsoft Macro Assembler and a math co-processor. The PC implementation allows individual arrays of over 64K. The BLAS library was developed in 1979. The PC version was made available in 1986 and updated in 1988.

Integrating image quality in 2nu-SVM biometric match score fusion.

PubMed

Vatsa, Mayank; Singh, Richa; Noore, Afzel

2007-10-01

This paper proposes an intelligent 2nu-support vector machine based match score fusion algorithm to improve the performance of face and iris recognition by integrating the quality of images. The proposed algorithm applies redundant discrete wavelet transform to evaluate the underlying linear and non-linear features present in the image. A composite quality score is computed to determine the extent of smoothness, sharpness, noise, and other pertinent features present in each subband of the image. The match score and the corresponding quality score of an image are fused using 2nu-support vector machine to improve the verification performance. The proposed algorithm is experimentally validated using the FERET face database and the CASIA iris database. The verification performance and statistical evaluation show that the proposed algorithm outperforms existing fusion algorithms.

Phase and speed synchronization control of four eccentric rotors driven by induction motors in a linear vibratory feeder with unknown time-varying load torques using adaptive sliding mode control algorithm

NASA Astrophysics Data System (ADS)

Kong, Xiangxi; Zhang, Xueliang; Chen, Xiaozhe; Wen, Bangchun; Wang, Bo

2016-05-01

In this paper, phase and speed synchronization control of four eccentric rotors (ERs) driven by induction motors in a linear vibratory feeder with unknown time-varying load torques is studied. Firstly, the electromechanical coupling model of the linear vibratory feeder is established by associating induction motor's model with the dynamic model of the system, which is a typical under actuated model. According to the characteristics of the linear vibratory feeder, the complex control problem of the under actuated electromechanical coupling model converts to phase and speed synchronization control of four ERs. In order to keep the four ERs operating synchronously with zero phase differences, phase and speed synchronization controllers are designed by employing adaptive sliding mode control (ASMC) algorithm via a modified master-slave structure. The stability of the controllers is proved by Lyapunov stability theorem. The proposed controllers are verified by simulation via Matlab/Simulink program and compared with the conventional sliding mode control (SMC) algorithm. The results show the proposed controllers can reject the time-varying load torques effectively and four ERs can operate synchronously with zero phase differences. Moreover, the control performance is better than the conventional SMC algorithm and the chattering phenomenon is attenuated. Furthermore, the effects of reference speed and parametric perturbations are discussed to show the strong robustness of the proposed controllers. Finally, experiments on a simple vibratory test bench are operated by using the proposed controllers and without control, respectively, to validate the effectiveness of the proposed controllers further.

Inductive sensor performance in partial discharges and noise separation by means of spectral power ratios.

PubMed

Ardila-Rey, Jorge Alfredo; Rojas-Moreno, Mónica Victoria; Martínez-Tarifa, Juan Manuel; Robles, Guillermo

2014-02-19

Partial discharge (PD) detection is a standardized technique to qualify electrical insulation in machines and power cables. Several techniques that analyze the waveform of the pulses have been proposed to discriminate noise from PD activity. Among them, spectral power ratio representation shows great flexibility in the separation of the sources of PD. Mapping spectral power ratios in two-dimensional plots leads to clusters of points which group pulses with similar characteristics. The position in the map depends on the nature of the partial discharge, the setup and the frequency response of the sensors. If these clusters are clearly separated, the subsequent task of identifying the source of the discharge is straightforward so the distance between clusters can be a figure of merit to suggest the best option for PD recognition. In this paper, two inductive sensors with different frequency responses to pulsed signals, a high frequency current transformer and an inductive loop sensor, are analyzed to test their performance in detecting and separating the sources of partial discharges.

Simulation of three-phase induction motor drives using indirect field oriented control in PSIM environment

NASA Astrophysics Data System (ADS)

Aziri, Hasif; Patakor, Fizatul Aini; Sulaiman, Marizan; Salleh, Zulhisyam

2017-09-01

This paper presents the simulation of three-phase induction motor drives using Indirect Field Oriented Control (IFOC) in PSIM environment. The asynchronous machine is well known about natural limitations fact of highly nonlinearity and complexity of motor model. In order to resolve these problems, the IFOC is applied to control the instantaneous electrical quantities such as torque and flux component. As FOC is controlling the stator current that represented by a vector, the torque component is aligned with d coordinate while the flux component is aligned with q coordinate. There are five levels of the incremental system are gradually built up to verify and testing the software module in the system. Indeed, all of system build levels are verified and successfully tested in PSIM environment. Moreover, the corresponding system of five build levels are simulated in PSIM environment which is user-friendly for simulation studies in order to explore the performance of speed responses based on IFOC algorithm for three-phase induction motor drives.

Determining the effect of grain size and maximum induction upon coercive field of electrical steels

NASA Astrophysics Data System (ADS)

Landgraf, Fernando José Gomes; da Silveira, João Ricardo Filipini; Rodrigues-Jr., Daniel

2011-10-01

Although theoretical models have already been proposed, experimental data is still lacking to quantify the influence of grain size upon coercivity of electrical steels. Some authors consider a linear inverse proportionality, while others suggest a square root inverse proportionality. Results also differ with regard to the slope of the reciprocal of grain size-coercive field relation for a given material. This paper discusses two aspects of the problem: the maximum induction used for determining coercive force and the possible effect of lurking variables such as the grain size distribution breadth and crystallographic texture. Electrical steel sheets containing 0.7% Si, 0.3% Al and 24 ppm C were cold-rolled and annealed in order to produce different grain sizes (ranging from 20 to 150 μm). Coercive field was measured along the rolling direction and found to depend linearly on reciprocal of grain size with a slope of approximately 0.9 (A/m)mm at 1.0 T induction. A general relation for coercive field as a function of grain size and maximum induction was established, yielding an average absolute error below 4%. Through measurement of B50 and image analysis of micrographs, the effects of crystallographic texture and grain size distribution breadth were qualitatively discussed.

A Novel Local Learning based Approach With Application to Breast Cancer Diagnosis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Songhua; Tourassi, Georgia

2012-01-01

The purpose of this study is to develop and evaluate a novel local learning-based approach for computer-assisted diagnosis of breast cancer. Our new local learning based algorithm using the linear logistic regression method as its base learner is described. Overall, our algorithm will perform its stochastic searching process until the total allowed computing time is used up by our random walk process in identifying the most suitable population subdivision scheme and their corresponding individual base learners. The proposed local learning-based approach was applied for the prediction of breast cancer given 11 mammographic and clinical findings reported by physicians using themore » BI-RADS lexicon. Our database consisted of 850 patients with biopsy confirmed diagnosis (290 malignant and 560 benign). We also compared the performance of our method with a collection of publicly available state-of-the-art machine learning methods. Predictive performance for all classifiers was evaluated using 10-fold cross validation and Receiver Operating Characteristics (ROC) analysis. Figure 1 reports the performance of 54 machine learning methods implemented in the machine learning toolkit Weka (version 3.0). We introduced a novel local learning-based classifier and compared it with an extensive list of other classifiers for the problem of breast cancer diagnosis. Our experiments show that the algorithm superior prediction performance outperforming a wide range of other well established machine learning techniques. Our conclusion complements the existing understanding in the machine learning field that local learning may capture complicated, non-linear relationships exhibited by real-world datasets.« less

Welding of Aluminum Alloys to Steels: An Overview

DTIC Science & Technology

2013-08-01

and deformations are a few examples of the unwanted consequences which somehow would lead to brittle fracture, fatigue fracture, shape instability...was made under the copper tips of the spot welding machine. The fatigue results showed higher fatigue strength of the joints with transition layer...kHz ultrasonic butt welding system with a vibration source applying eight bolt-clamped Langevin type PZT transducers and a 50 kW static induction

System diagnostic builder: a rule-generation tool for expert systems that do intelligent data evaluation

NASA Astrophysics Data System (ADS)

Nieten, Joseph L.; Burke, Roger

1993-03-01

The system diagnostic builder (SDB) is an automated knowledge acquisition tool using state- of-the-art artificial intelligence (AI) technologies. The SDB uses an inductive machine learning technique to generate rules from data sets that are classified by a subject matter expert (SME). Thus, data is captured from the subject system, classified by an expert, and used to drive the rule generation process. These rule-bases are used to represent the observable behavior of the subject system, and to represent knowledge about this system. The rule-bases can be used in any knowledge based system which monitors or controls a physical system or simulation. The SDB has demonstrated the utility of using inductive machine learning technology to generate reliable knowledge bases. In fact, we have discovered that the knowledge captured by the SDB can be used in any number of applications. For example, the knowledge bases captured from the SMS can be used as black box simulations by intelligent computer aided training devices. We can also use the SDB to construct knowledge bases for the process control industry, such as chemical production, or oil and gas production. These knowledge bases can be used in automated advisory systems to ensure safety, productivity, and consistency.

Novel permanent magnet linear motor with isolated movers: analytical, numerical and experimental study.

PubMed

Yan, Liang; Peng, Juanjuan; Jiao, Zongxia; Chen, Chin-Yin; Chen, I-Ming

2014-10-01

This paper proposes a novel permanent magnet linear motor possessing two movers and one stator. The two movers are isolated and can interact with the stator poles to generate independent forces and motions. Compared with conventional multiple motor driving system, it helps to increase the system compactness, and thus improve the power density and working efficiency. The magnetic field distribution is obtained by using equivalent magnetic circuit method. Following that, the formulation of force output considering armature reaction is carried out. Then inductances are analyzed with finite element method to investigate the relationships of the two movers. It is found that the mutual-inductances are nearly equal to zero, and thus the interaction between the two movers is negligible. A research prototype of the linear motor and a measurement apparatus on thrust force have been developed. Both numerical computation and experiment measurement are conducted to validate the analytical model of thrust force. Comparison shows that the analytical model matches the numerical and experimental results well.

Modeling Dengue vector population using remotely sensed data and machine learning.

PubMed

Scavuzzo, Juan M; Trucco, Francisco; Espinosa, Manuel; Tauro, Carolina B; Abril, Marcelo; Scavuzzo, Carlos M; Frery, Alejandro C

2018-05-16

Mosquitoes are vectors of many human diseases. In particular, Aedes ægypti (Linnaeus) is the main vector for Chikungunya, Dengue, and Zika viruses in Latin America and it represents a global threat. Public health policies that aim at combating this vector require dependable and timely information, which is usually expensive to obtain with field campaigns. For this reason, several efforts have been done to use remote sensing due to its reduced cost. The present work includes the temporal modeling of the oviposition activity (measured weekly on 50 ovitraps in a north Argentinean city) of Aedes ægypti (Linnaeus), based on time series of data extracted from operational earth observation satellite images. We use are NDVI, NDWI, LST night, LST day and TRMM-GPM rain from 2012 to 2016 as predictive variables. In contrast to previous works which use linear models, we employ Machine Learning techniques using completely accessible open source toolkits. These models have the advantages of being non-parametric and capable of describing nonlinear relationships between variables. Specifically, in addition to two linear approaches, we assess a support vector machine, an artificial neural networks, a K-nearest neighbors and a decision tree regressor. Considerations are made on parameter tuning and the validation and training approach. The results are compared to linear models used in previous works with similar data sets for generating temporal predictive models. These new tools perform better than linear approaches, in particular nearest neighbor regression (KNNR) performs the best. These results provide better alternatives to be implemented operatively on the Argentine geospatial risk system that is running since 2012. Copyright © 2018 Elsevier B.V. All rights reserved.

Improving linear accelerator service response with a real- time electronic event reporting system.

PubMed

Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

2014-09-08

To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations.

Inductive voltage adder (IVA) for submillimeter radius electron beam

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mazarakis, M.G.; Poukey, J.W.; Maenchen, J.E.

The authors have already demonstrated the utility of inductive voltage adder accelerators for production of small-size electron beams. In this approach, the inductive voltage adder drives a magnetically immersed foilless diode to produce high-energy (10--20 MeV), high-brightness pencil electron beams. This concept was first demonstrated with the successful experiments which converted the linear induction accelerator RADLAC II into an IVA fitted with a small 1-cm radius cathode magnetically immersed foilless diode (RADLAC II/SMILE). They present here first validations of extending this idea to mm-scale electron beams using the SABRE and HERMES-III inductive voltage adders as test beds. The SABRE experimentsmore » are already completed and have produced 30-kA, 9-MeV electron beams with envelope diameter of 1.5-mm FWHM. The HERMES-III experiments are currently underway.« less

Inductance position sensor for pneumatic cylinder

NASA Astrophysics Data System (ADS)

Ripka, Pavel; Chirtsov, Andrey; Mirzaei, Mehran; Vyhnanek, Jan

2018-04-01

The position of the piston in pneumatic cylinder with aluminum wall can be measured by external inductance sensor without modifications of the aluminum piston and massive iron piston rod. For frequencies below 20 Hz the inductance is increasing with inserting rod due to the rod permeability. This mode has disadvantage of slow response to piston movement and also high temperature sensitivity. At the frequency of 45 Hz the inductance is position independent, as the permeability effect is compensated by the eddy current effect. At higher frequencies eddy current effects in the rod prevail, the inductance is decreasing with inserting rod. In this mode the sensitivity is smaller but the sensor response is fast and temperature stability is better. We show that FEM simulation of this sensor using measured material properties gives accurate results, which is important for the sensor optimization such as designing the winding geometry for the best linearity.

Survey of beam instrumentation used in SLC

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ecklund, S.D.

A survey of beam instruments used at SLAC in the SLC machine is presented. The basic utility and operation of each device is briefly described. The various beam instruments used at the Stanford Linear Collider (SLC), can be classified by the function they perform. Beam intensity, position and size are typical of the parameters of beam which are measured. Each type of parameter is important for adjusting or tuning the machine in order to achieve optimum performance. 39 refs.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE PAGES

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

2017-04-26

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Figure of merit for macrouniformity based on image quality ruler evaluation and machine learning framework

NASA Astrophysics Data System (ADS)

Wang, Weibao; Overall, Gary; Riggs, Travis; Silveston-Keith, Rebecca; Whitney, Julie; Chiu, George; Allebach, Jan P.

2013-01-01

Assessment of macro-uniformity is a capability that is important for the development and manufacture of printer products. Our goal is to develop a metric that will predict macro-uniformity, as judged by human subjects, by scanning and analyzing printed pages. We consider two different machine learning frameworks for the metric: linear regression and the support vector machine. We have implemented the image quality ruler, based on the recommendations of the INCITS W1.1 macro-uniformity team. Using 12 subjects at Purdue University and 20 subjects at Lexmark, evenly balanced with respect to gender, we conducted subjective evaluations with a set of 35 uniform b/w prints from seven different printers with five levels of tint coverage. Our results suggest that the image quality ruler method provides a reliable means to assess macro-uniformity. We then defined and implemented separate features to measure graininess, mottle, large area variation, jitter, and large-scale non-uniformity. The algorithms that we used are largely based on ISO image quality standards. Finally, we used these features computed for a set of test pages and the subjects' image quality ruler assessments of these pages to train the two different predictors - one based on linear regression and the other based on the support vector machine (SVM). Using five-fold cross-validation, we confirmed the efficacy of our predictor.

Discovering charge density functionals and structure-property relationships with PROPhet: A general framework for coupling machine learning and first-principles methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kolb, Brian; Lentz, Levi C.; Kolpak, Alexie M.

Modern ab initio methods have rapidly increased our understanding of solid state materials properties, chemical reactions, and the quantum interactions between atoms. However, poor scaling often renders direct ab initio calculations intractable for large or complex systems. There are two obvious avenues through which to remedy this problem: (i) develop new, less expensive methods to calculate system properties, or (ii) make existing methods faster. This paper describes an open source framework designed to pursue both of these avenues. PROPhet (short for PROPerty Prophet) utilizes machine learning techniques to find complex, non-linear mappings between sets of material or system properties. Themore » result is a single code capable of learning analytical potentials, non-linear density functionals, and other structure-property or property-property relationships. These capabilities enable highly accurate mesoscopic simulations, facilitate computation of expensive properties, and enable the development of predictive models for systematic materials design and optimization. Here, this work explores the coupling of machine learning to ab initio methods through means both familiar (e.g., the creation of various potentials and energy functionals) and less familiar (e.g., the creation of density functionals for arbitrary properties), serving both to demonstrate PROPhet’s ability to create exciting post-processing analysis tools and to open the door to improving ab initio methods themselves with these powerful machine learning techniques.« less

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

Synchronous machines have traditionally acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, with the increased integration of distributed renewable resources and energy-storage technologies, there is a need to systematically acknowledge the dynamics of power-electronics inverters - the primary energy-conversion interface in such systems - in all aspects of modeling, analysis, and control of the bulk power network. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator, three-phase inverter, and a load. The inverter model is formulatedmore » such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less

Comparison of Machine Learning Methods for the Arterial Hypertension Diagnostics

PubMed Central

Belo, David; Gamboa, Hugo

2017-01-01

The paper presents results of machine learning approach accuracy applied analysis of cardiac activity. The study evaluates the diagnostics possibilities of the arterial hypertension by means of the short-term heart rate variability signals. Two groups were studied: 30 relatively healthy volunteers and 40 patients suffering from the arterial hypertension of II-III degree. The following machine learning approaches were studied: linear and quadratic discriminant analysis, k-nearest neighbors, support vector machine with radial basis, decision trees, and naive Bayes classifier. Moreover, in the study, different methods of feature extraction are analyzed: statistical, spectral, wavelet, and multifractal. All in all, 53 features were investigated. Investigation results show that discriminant analysis achieves the highest classification accuracy. The suggested approach of noncorrelated feature set search achieved higher results than data set based on the principal components. PMID:28831239

An implementation of support vector machine on sentiment classification of movie reviews

NASA Astrophysics Data System (ADS)

Yulietha, I. M.; Faraby, S. A.; Adiwijaya; Widyaningtyas, W. C.

2018-03-01

With technological advances, all information about movie is available on the internet. If the information is processed properly, it will get the quality of the information. This research proposes to the classify sentiments on movie review documents. This research uses Support Vector Machine (SVM) method because it can classify high dimensional data in accordance with the data used in this research in the form of text. Support Vector Machine is a popular machine learning technique for text classification because it can classify by learning from a collection of documents that have been classified previously and can provide good result. Based on number of datasets, the 90-10 composition has the best result that is 85.6%. Based on SVM kernel, kernel linear with constant 1 has the best result that is 84.9%

Remote sensing of thermal radiation from an aircraft - An analysis and evaluation of crop-freeze protection methods

NASA Technical Reports Server (NTRS)

Sutherland, R. A.; Hannah, H. E.; Cook, A. F.; Martsolf, J. D.

1981-01-01

Thermal images from an aircraft-mounted scanner are used to evaluate the effectiveness of crop-freeze protection devices. Data from flights made while using fuel oil heaters, a wind machine and an undercanopy irrigation system are compared. Results show that the overall protection provided by irrigation (at approximately 2 C) is comparable to the less energy-efficient heater-wind machine combination. Protection provided by the wind machine alone (at approximately 1 C) was found to decrease linearly with distance from the machine by approximately 1 C/100 m. The flights were made over a 1.5 hectare citrus grove at an altitude of 450 m with an 8-14 micron detector. General meteorological conditions during the experiments, conducted during the nighttime, were cold (at approximately -6 C) and calm with clear skies.

Machine learning in the string landscape

NASA Astrophysics Data System (ADS)

Carifio, Jonathan; Halverson, James; Krioukov, Dmitri; Nelson, Brent D.

2017-09-01

We utilize machine learning to study the string landscape. Deep data dives and conjecture generation are proposed as useful frameworks for utilizing machine learning in the landscape, and examples of each are presented. A decision tree accurately predicts the number of weak Fano toric threefolds arising from reflexive polytopes, each of which determines a smooth F-theory compactification, and linear regression generates a previously proven conjecture for the gauge group rank in an ensemble of 4/3× 2.96× {10}^{755} F-theory compactifications. Logistic regression generates a new conjecture for when E 6 arises in the large ensemble of F-theory compactifications, which is then rigorously proven. This result may be relevant for the appearance of visible sectors in the ensemble. Through conjecture generation, machine learning is useful not only for numerics, but also for rigorous results.

Analysis and comparison of end effects in linear switched reluctance and hybrid motors

NASA Astrophysics Data System (ADS)

Barhoumi, El Manaa; Abo-Khalil, Ahmed Galal; Berrouche, Youcef; Wurtz, Frederic

2017-03-01

This paper presents and discusses the longitudinal and transversal end effects which affects the propulsive force of linear motors. Generally, the modeling of linear machine considers the forces distortion due to the specific geometry of linear actuators. The insertion of permanent magnets on the stator allows improving the propulsive force produced by switched reluctance linear motors. Also, the inserted permanent magnets in the hybrid structure allow reducing considerably the ends effects observed in linear motors. The analysis was conducted using 2D and 3D finite elements method. The permanent magnet reinforces the flux produced by the winding and reorients it which allows modifying the impact of end effects. Presented simulations and discussions show the importance of this study to characterize the end effects in two different linear motors.

Steady induction effects in geomagnetism. Part 1B: Geomagnetic estimation of steady surficial core motions: A non-linear inverse problem

NASA Technical Reports Server (NTRS)

Voorhies, Coerte V.

1993-01-01

The problem of estimating a steady fluid velocity field near the top of Earth's core which induces the secular variation (SV) indicated by models of the observed geomagnetic field is examined in the source-free mantle/frozen-flux core (SFI/VFFC) approximation. This inverse problem is non-linear because solutions of the forward problem are deterministically chaotic. The SFM/FFC approximation is inexact, and neither the models nor the observations they represent are either complete or perfect. A method is developed for solving the non-linear inverse motional induction problem posed by the hypothesis of (piecewise, statistically) steady core surface flow and the supposition of a complete initial geomagnetic condition. The method features iterative solution of the weighted, linearized least-squares problem and admits optional biases favoring surficially geostrophic flow and/or spatially simple flow. Two types of weights are advanced radial field weights for fitting the evolution of the broad-scale portion of the radial field component near Earth's surface implied by the models, and generalized weights for fitting the evolution of the broad-scale portion of the scalar potential specified by the models.

Non Invasive Sensors for Monitoring the Efficiency of AC Electrical Rotating Machines

PubMed Central

Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric

2010-01-01

This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer. PMID:22163631

Development of High Temperature Electro-Magnetic Actuators (HTEMA) for Aircraft Propulsion Systems (Preprint)

DTIC Science & Technology

2013-05-01

an 18 inch gap diameter has roughly a 2 foot outer diameter                                                              2 “ Brushless  Permanent...require PMs include wound rotor DC (brush and brushless ), Variable or Switched reluctance (VR or SR) machines and squirrel cage induction motors...Trades have identified Brushless DC PM and SR machines are of primary interest. Both motors can use sensorless commutation methods. A VR resolver can

Non invasive sensors for monitoring the efficiency of AC electrical rotating machines.

PubMed

Zidat, Farid; Lecointe, Jean-Philippe; Morganti, Fabrice; Brudny, Jean-François; Jacq, Thierry; Streiff, Frédéric

2010-01-01

This paper presents a non invasive method for estimating the energy efficiency of induction motors used in industrial applications. This method is innovative because it is only based on the measurement of the external field emitted by the motor. The paper describes the sensors used, how they should be placed around the machine in order to decouple the external field components generated by both the air gap flux and the winding end-windings. The study emphasizes the influence of the eddy currents flowing in the yoke frame on the sensor position. A method to estimate the torque from the external field use is proposed. The measurements are transmitted by a wireless module (Zig-Bee) and they are centralized and stored on a PC computer.

Note: A pulsed laser ion source for linear induction accelerators

NASA Astrophysics Data System (ADS)

Zhang, H.; Zhang, K.; Shen, Y.; Jiang, X.; Dong, P.; Liu, Y.; Wang, Y.; Chen, D.; Pan, H.; Wang, W.; Jiang, W.; Long, J.; Xia, L.; Shi, J.; Zhang, L.; Deng, J.

2015-01-01

We have developed a high-current laser ion source for induction accelerators. A copper target was irradiated by a frequency-quadrupled Nd:YAG laser (266 nm) with relatively low intensities of 108 W/cm2. The laser-produced plasma supplied a large number of Cu+ ions (˜1012 ions/pulse) during several microseconds. Emission spectra of the plasma were observed and the calculated electron temperature was about 1 eV. An induction voltage adder extracted high-current ion beams over 0.5 A/cm2 from a plasma-prefilled gap. The normalized beam emittance measured by a pepper-pot method was smaller than 1 π mm mrad.

Radiation effects in Caenorhabditis elegans - Mutagenesis by high and low LET ionizing radiation

NASA Technical Reports Server (NTRS)

Nelson, Gregory A.; Schubert, Wayne W.; Marshall, Tamara M.; Benton, Eric R.; Benton, Eugene V.

1989-01-01

The nematode C. elegans was used to measure the effectiveness of high-energy ionized particles in the induction of three types of genetic lesions. Recessive lethal mutations in a 40-map unit autosomal region, sterility, and X-chromosome nondisjunction or damage were investigated. Induction rates were measured as a function of linear energy transfer, LET(infinity), for nine ions of atomic nunmber 1-57 accelerated at the BEVALAC accelerator. Linear kinetics were observed for all three types of lesions within the dose/fluence ranges tested and were found to vary strongly as a function of particle LET(infinity). Relative biological effectiveness (RBE) values of up to 4.2 were measured, and action cross sections were calculated and compared to mutagenic responses in other systems.

Pencil-like mm-size electron beams produced with linear inductive voltage adders

NASA Astrophysics Data System (ADS)

Mazarakis, M. G.; Poukey, J. W.; Rovang, D. C.; Maenchen, J. E.; Cordova, S. R.; Menge, P. R.; Pepping, R.; Bennett, L.; Mikkelson, K.; Smith, D. L.; Halbleib, J.; Stygar, W. A.; Welch, D. R.

1997-02-01

We present the design, analysis, and results of the high brightness electron beam experiments currently under investigation at Sandia National Laboratories. The anticipated beam parameters are the following: energy 12 MeV, current 35-40 kA, rms radius 0.5 mm, and pulse duration 40 ns full width at half-maximum. The accelerator is SABRE, a pulsed linear inductive voltage adder modified to higher impedance, and the electron source is a magnetically immersed foilless electron diode. 20-30 T solenoidal magnets are required to insulate the diode and contain the beam to its extremely small-sized (1 mm) envelope. These experiments are designed to push the technology to produce the highest possible electron current in a submillimeter radius beam. Design, numerical simulations, and experimental results are presented.

Electromagnetic Performance Calculation of HTS Linear Induction Motor for Rail Systems

NASA Astrophysics Data System (ADS)

Liu, Bin; Fang, Jin; Cao, Junci; Chen, Jie; Shu, Hang; Sheng, Long

2017-07-01

According to a high temperature superconducting (HTS) linear induction motor (LIM) designed for rail systems, the influence of electromagnetic parameters and mechanical structure parameters on the electromagnetic horizontal thrust, vertical force of HTS LIM and the maximum vertical magnetic field of HTS windings are analyzed. Through the research on the vertical field of HTS windings, the development regularity of the HTS LIM maximum input current with different stator frequency and different thickness value of the secondary conductive plate is obtained. The theoretical results are of great significance to analyze the stability of HTS LIM. Finally, based on theory analysis, HTS LIM test platform was built and the experiment was carried out with load. The experimental results show that the theoretical analysis is correct and reasonable.

Controlling Continuous-Variable Quantum Key Distribution with Entanglement in the Middle Using Tunable Linear Optics Cloning Machines

NASA Astrophysics Data System (ADS)

Wu, Xiao Dong; Chen, Feng; Wu, Xiang Hua; Guo, Ying

2017-02-01

Continuous-variable quantum key distribution (CVQKD) can provide detection efficiency, as compared to discrete-variable quantum key distribution (DVQKD). In this paper, we demonstrate a controllable CVQKD with the entangled source in the middle, contrast to the traditional point-to-point CVQKD where the entanglement source is usually created by one honest party and the Gaussian noise added on the reference partner of the reconciliation is uncontrollable. In order to harmonize the additive noise that originates in the middle to resist the effect of malicious eavesdropper, we propose a controllable CVQKD protocol by performing a tunable linear optics cloning machine (LOCM) at one participant's side, say Alice. Simulation results show that we can achieve the optimal secret key rates by selecting the parameters of the tuned LOCM in the derived regions.

A Prototype SSVEP Based Real Time BCI Gaming System

PubMed Central

Martišius, Ignas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel. PMID:27051414

Balancing Vibrations at Harmonic Frequencies by Injecting Harmonic Balancing Signals into the Armature of a Linear Motor/Alternator Coupled to a Stirling Machine

NASA Technical Reports Server (NTRS)

Holliday, Ezekiel S. (Inventor)

2014-01-01

Vibrations at harmonic frequencies are reduced by injecting harmonic balancing signals into the armature of a linear motor/alternator coupled to a Stirling machine. The vibrations are sensed to provide a signal representing the mechanical vibrations. A harmonic balancing signal is generated for selected harmonics of the operating frequency by processing the sensed vibration signal with adaptive filter algorithms of adaptive filters for each harmonic. Reference inputs for each harmonic are applied to the adaptive filter algorithms at the frequency of the selected harmonic. The harmonic balancing signals for all of the harmonics are summed with a principal control signal. The harmonic balancing signals modify the principal electrical drive voltage and drive the motor/alternator with a drive voltage component in opposition to the vibration at each harmonic.

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

A Prototype SSVEP Based Real Time BCI Gaming System.

PubMed

Martišius, Ignas; Damaševičius, Robertas

2016-01-01

Although brain-computer interface technology is mainly designed with disabled people in mind, it can also be beneficial to healthy subjects, for example, in gaming or virtual reality systems. In this paper we discuss the typical architecture, paradigms, requirements, and limitations of electroencephalogram-based gaming systems. We have developed a prototype three-class brain-computer interface system, based on the steady state visually evoked potentials paradigm and the Emotiv EPOC headset. An online target shooting game, implemented in the OpenViBE environment, has been used for user feedback. The system utilizes wave atom transform for feature extraction, achieving an average accuracy of 78.2% using linear discriminant analysis classifier, 79.3% using support vector machine classifier with a linear kernel, and 80.5% using a support vector machine classifier with a radial basis function kernel.

Comparison of rule induction, decision trees and formal concept analysis approaches for classification

NASA Astrophysics Data System (ADS)

Kotelnikov, E. V.; Milov, V. R.

2018-05-01

Rule-based learning algorithms have higher transparency and easiness to interpret in comparison with neural networks and deep learning algorithms. These properties make it possible to effectively use such algorithms to solve descriptive tasks of data mining. The choice of an algorithm depends also on its ability to solve predictive tasks. The article compares the quality of the solution of the problems with binary and multiclass classification based on the experiments with six datasets from the UCI Machine Learning Repository. The authors investigate three algorithms: Ripper (rule induction), C4.5 (decision trees), In-Close (formal concept analysis). The results of the experiments show that In-Close demonstrates the best quality of classification in comparison with Ripper and C4.5, however the latter two generate more compact rule sets.

NASA Tech Briefs, December 2013

NASA Technical Reports Server (NTRS)

2013-01-01

Topics include: Microwave Kinetic Inductance Detector With; Selective Polarization Coupling; Flexible Microstrip Circuits for; Superconducting Electronics; CFD Extraction Tool for TecPlot From DPLR Solutions; RECOVIR Software for Identifying Viruses; Enhanced Contact Graph Routing (ECGR) MACHETE Simulation Model; Orbital Debris Engineering Model (ORDEM) v.3; Scatter-Reducing Sounding Filtration Using a Genetic Algorithm and Mean Monthly Standard Deviation; Thermo-Mechanical Methodology for Stabilizing Shape Memory Alloy Response; Hermetic Seal Designs for Sample Return Sample Tubes; Silicon Alignment Pins: An Easy Way To Realize a Wafer-to-Wafer Alignment; Positive-Buoyancy Rover for Under Ice Mobility; Electric Machine With Boosted Inductance to Stabilize Current Control; International Space Station-Based Electromagnetic Launcher for Space Science Payloads; Advanced Hybrid Spacesuit Concept Featuring Integrated Open Loop and Closed Loop Ventilation Systems; Data Quality Screening Service.

Inductive System Health Monitoring

NASA Technical Reports Server (NTRS)

Iverson, David L.

2004-01-01

The Inductive Monitoring System (IMS) software was developed to provide a technique to automatically produce health monitoring knowledge bases for systems that are either difficult to model (simulate) with a computer or which require computer models that are too complex to use for real time monitoring. IMS uses nominal data sets collected either directly from the system or from simulations to build a knowledge base that can be used to detect anomalous behavior in the system. Machine learning and data mining techniques are used to characterize typical system behavior by extracting general classes of nominal data from archived data sets. IMS is able to monitor the system by comparing real time operational data with these classes. We present a description of learning and monitoring method used by IMS and summarize some recent IMS results.

High Strength P/M Gears for Vehicle Transmissions - Phase 2

DTIC Science & Technology

2008-08-15

and while it was considered amenable to standard work material transfer ("blue steel" chutes for example) from other P/M processing equipment, no...depend of the machine design but should be kept to a minimum in order to minimize part transfer times. Position control of the linear axis is...Establish design of ausform gear finishing machine for P/M gears: The "Focus" part identified in phase I (New Process Planet gear P/N 17864, component

Linear-hall sensor based force detecting unit for lower limb exoskeleton

NASA Astrophysics Data System (ADS)

Li, Hongwu; Zhu, Yanhe; Zhao, Jie; Wang, Tianshuo; Zhang, Zongwei

2018-04-01

This paper describes a knee-joint human-machine interaction force sensor for lower-limb force-assistance exoskeleton. The structure is designed based on hall sensor and series elastic actuator (SEA) structure. The work we have done includes the structure design, the parameter determination and dynamic simulation. By converting the force signal into macro displacement and output voltage, we completed the measurement of man-machine interaction force. And it is proved by experiments that the design is simple, stable and low-cost.

Developing Test Apparatus and Measurements of AC Loss of High Temperature Superconductors

DTIC Science & Technology

2012-11-01

temperature of the coil is not raised significantly. The second system, a larger machine, designed with a long term prospective to serve a test bed for...four sample chambers inside the vacuum gap, LN2 – cooled sample holder (currently only one is in use), the laminated back iron, and the outer shell...machine. accommodate a variety of different small coils and linear tapes. This assembly is surrounded by the laminated back iron and the outer shell

Anytime query-tuned kernel machine classifiers via Cholesky factorization

NASA Technical Reports Server (NTRS)

DeCoste, D.

2002-01-01

We recently demonstrated 2 to 64-fold query-time speedups of Support Vector Machine and Kernel Fisher classifiers via a new computational geometry method for anytime output bounds (DeCoste,2002). This new paper refines our approach in two key ways. First, we introduce a simple linear algebra formulation based on Cholesky factorization, yielding simpler equations and lower computational overhead. Second, this new formulation suggests new methods for achieving additional speedups, including tuning on query samples. We demonstrate effectiveness on benchmark datasets.

Error compensation for thermally induced errors on a machine tool

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krulewich, D.A.

1996-11-08

Heat flow from internal and external sources and the environment create machine deformations, resulting in positioning errors between the tool and workpiece. There is no industrially accepted method for thermal error compensation. A simple model has been selected that linearly relates discrete temperature measurements to the deflection. The biggest problem is how to locate the temperature sensors and to determine the number of required temperature sensors. This research develops a method to determine the number and location of temperature measurements.

The study on the nanomachining property and cutting model of single-crystal sapphire by atomic force microscopy.

PubMed

Huang, Jen-Ching; Weng, Yung-Jin

2014-01-01

This study focused on the nanomachining property and cutting model of single-crystal sapphire during nanomachining. The coated diamond probe is used to as a tool, and the atomic force microscopy (AFM) is as an experimental platform for nanomachining. To understand the effect of normal force on single-crystal sapphire machining, this study tested nano-line machining and nano-rectangular pattern machining at different normal force. In nano-line machining test, the experimental results showed that the normal force increased, the groove depth from nano-line machining also increased. And the trend is logarithmic type. In nano-rectangular pattern machining test, it is found when the normal force increases, the groove depth also increased, but rather the accumulation of small chips. This paper combined the blew by air blower, the cleaning by ultrasonic cleaning machine and using contact mode probe to scan the surface topology after nanomaching, and proposed the "criterion of nanomachining cutting model," in order to determine the cutting model of single-crystal sapphire in the nanomachining is ductile regime cutting model or brittle regime cutting model. After analysis, the single-crystal sapphire substrate is processed in small normal force during nano-linear machining; its cutting modes are ductile regime cutting model. In the nano-rectangular pattern machining, due to the impact of machined zones overlap, the cutting mode is converted into a brittle regime cutting model. © 2014 Wiley Periodicals, Inc.

Detection of Buried Targets via Active Selection of Labeled Data: Application to Sensing Subsurface UXO

DTIC Science & Technology

2007-06-01

images,” IEEE Trans. Pattern Analysis Machine Intelligence, vol. 13, no. 2, pp. 99–113, 1991. [15] C. Bouman and M. Shapiro, “A multiscale random...including the time for reviewing instructions, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing...this project was on developing new statistical algorithms for analysis of electromagnetic induction (EMI) and magnetometer data measured at actual

New concept for in-line OLED manufacturing

NASA Astrophysics Data System (ADS)

Hoffmann, U.; Landgraf, H.; Campo, M.; Keller, S.; Koening, M.

2011-03-01

A new concept of a vertical In-Line deposition machine for large area white OLED production has been developed. The concept targets manufacturing on large substrates (>= Gen 4, 750 x 920 mm2) using linear deposition source achieving a total material utilization of >= 50 % and tact time down to 80 seconds. The continuously improved linear evaporation sources for the organic material achieve thickness uniformity on Gen 4 substrate of better than +/- 3 % and stable deposition rates down to less than 0.1 nm m/min and up to more than 100 nm m/min. For Lithium-Fluoride but also for other high evaporation temperature materials like Magnesium or Silver a linear source with uniformity better than +/- 3 % has been developed. For Aluminum we integrated a vertical oriented point source using wire feed to achieve high (> 150 nm m/min) and stable deposition rates. The machine concept includes a new vertical vacuum handling and alignment system for Gen 4 shadow masks. A complete alignment cycle for the mask can be done in less than one minute achieving alignment accuracy in the range of several 10 μm.

Four-point bend apparatus for in situ micro-Raman stress measurements

NASA Astrophysics Data System (ADS)

Ward, Shawn H.; Mann, Adrian B.

2018-06-01

A device for in situ use with a micro-Raman microscope to determine stress from the Raman peak position was designed and validated. The device is a four-point bend machine with a micro-stepping motor and load cell, allowing for fine movement and accurate readings of the applied force. The machine has a small footprint and easily fits on most optical microscope stages. The results obtained from silicon are in good agreement with published literature values for the linear relationship between stress and peak position for the 520.8 cm‑1 Raman peak. The device was used to examine 4H–SiC and a good linear relationship was found between the 798 cm‑1 Raman peak position and stress, with the proportionality coefficient being close to the theoretical value of 0.0025. The 777 cm‑1 Raman peak also showed a linear dependence on stress, but the dependence was not as strong. The device examines both the tensile and compressive sides of the beam in bending, granting the potential for many materials and crystal orientations to be examined.

Alternate approaches to future electron-positron linear colliders

DOE Office of Scientific and Technical Information (OSTI.GOV)

Loew, G.A.

1998-07-01

The purpose of this article is two-fold: to review the current international status of various design approaches to the next generation of e{sup +}e{sup {minus}} linear colliders, and on the occasion of his 80th birthday, to celebrate Richard B. Neal`s many contributions to the field of linear accelerators. As it turns out, combining these two tasks is a rather natural enterprise because of Neal`s long professional involvement and insight into many of the problems and options which the international e{sup +}e{sup {minus}} linear collider community is currently studying to achieve a practical design for a future machine.

Mamdani-Fuzzy Modeling Approach for Quality Prediction of Non-Linear Laser Lathing Process

NASA Astrophysics Data System (ADS)

Sivaraos; Khalim, A. Z.; Salleh, M. S.; Sivakumar, D.; Kadirgama, K.

2018-03-01

Lathing is a process to fashioning stock materials into desired cylindrical shapes which usually performed by traditional lathe machine. But, the recent rapid advancements in engineering materials and precision demand gives a great challenge to the traditional method. The main drawback of conventional lathe is its mechanical contact which brings to the undesirable tool wear, heat affected zone, finishing, and dimensional accuracy especially taper quality in machining of stock with high length to diameter ratio. Therefore, a novel approach has been devised to investigate in transforming a 2D flatbed CO2 laser cutting machine into 3D laser lathing capability as an alternative solution. Three significant design parameters were selected for this experiment, namely cutting speed, spinning speed, and depth of cut. Total of 24 experiments were performed with eight (8) sequential runs where they were then replicated three (3) times. The experimental results were then used to establish Mamdani - Fuzzy predictive model where it yields the accuracy of more than 95%. Thus, the proposed Mamdani - Fuzzy modelling approach is found very much suitable and practical for quality prediction of non-linear laser lathing process for cylindrical stocks of 10mm diameter.

Full-motion video analysis for improved gender classification

NASA Astrophysics Data System (ADS)

Flora, Jeffrey B.; Lochtefeld, Darrell F.; Iftekharuddin, Khan M.

2014-06-01

The ability of computer systems to perform gender classification using the dynamic motion of the human subject has important applications in medicine, human factors, and human-computer interface systems. Previous works in motion analysis have used data from sensors (including gyroscopes, accelerometers, and force plates), radar signatures, and video. However, full-motion video, motion capture, range data provides a higher resolution time and spatial dataset for the analysis of dynamic motion. Works using motion capture data have been limited by small datasets in a controlled environment. In this paper, we explore machine learning techniques to a new dataset that has a larger number of subjects. Additionally, these subjects move unrestricted through a capture volume, representing a more realistic, less controlled environment. We conclude that existing linear classification methods are insufficient for the gender classification for larger dataset captured in relatively uncontrolled environment. A method based on a nonlinear support vector machine classifier is proposed to obtain gender classification for the larger dataset. In experimental testing with a dataset consisting of 98 trials (49 subjects, 2 trials per subject), classification rates using leave-one-out cross-validation are improved from 73% using linear discriminant analysis to 88% using the nonlinear support vector machine classifier.

The employment of Support Vector Machine to classify high and low performance archers based on bio-physiological variables

NASA Astrophysics Data System (ADS)

Taha, Zahari; Muazu Musa, Rabiu; Majeed, Anwar P. P. Abdul; Razali Abdullah, Mohamad; Amirul Abdullah, Muhammad; Hasnun Arif Hassan, Mohd; Khalil, Zubair

2018-04-01

The present study employs a machine learning algorithm namely support vector machine (SVM) to classify high and low potential archers from a collection of bio-physiological variables trained on different SVMs. 50 youth archers with the average age and standard deviation of (17.0 ±.056) gathered from various archery programmes completed a one end shooting score test. The bio-physiological variables namely resting heart rate, resting respiratory rate, resting diastolic blood pressure, resting systolic blood pressure, as well as calories intake, were measured prior to their shooting tests. k-means cluster analysis was applied to cluster the archers based on their scores on variables assessed. SVM models i.e. linear, quadratic and cubic kernel functions, were trained on the aforementioned variables. The k-means clustered the archers into high (HPA) and low potential archers (LPA), respectively. It was demonstrated that the linear SVM exhibited good accuracy with a classification accuracy of 94% in comparison the other tested models. The findings of this investigation can be valuable to coaches and sports managers to recognise high potential athletes from the selected bio-physiological variables examined.

Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast.

PubMed

Poos, Alexandra M; Maicher, André; Dieckmann, Anna K; Oswald, Marcus; Eils, Roland; Kupiec, Martin; Luke, Brian; König, Rainer

2016-06-02

Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Development and Implementation of a Simplified Tool Measuring System

NASA Astrophysics Data System (ADS)

Chen, Jenn-Yih; Lee, Bean-Yin; Lee, Kuang-Chyi; Chen, Zhao-Kai

2010-01-01

This paper presents a simplified system for measuring geometric profiles of end mills. Firstly, a CCD camera was used to capture images of cutting tools. Then, an image acquisition card with the encoding function was adopted to convert the source of image into an USB port of a PC, and the image could be shown on a monitor. In addition, two linear scales were mounted on the X-Y table for positioning and measuring purposes. The signals of the linear scales were transmitted into a 4-axis quadrature encoder with 4-channel counter card for position monitoring. The C++ Builder was utilized for designing the user friendly human machine interface of the measuring system of tools. There is a cross line on the image of the interface to show a coordinate for the position measurement. Finally, a well-known tool measuring and inspection machine was employed for the measuring standard. This study compares the difference of the measuring results by using the machine and the proposed system. Experimental results show that the percentage of measuring error is acceptable for some geometric parameters of the square or ball nose end mills. Therefore, the results demonstrate the effectiveness of the presented approach.

Dynamics of the process boom machine working equipment under the real law of the hydraulic distributor electric spool control

NASA Astrophysics Data System (ADS)

Tarasov, V. N.; Boyarkina, I. V.

2017-06-01

Analytical calculation methods of dynamic processes of the self-propelled boom hydraulic machines working equipment are more preferable in comparison with numerical methods. The analytical research method of dynamic processes of the boom hydraulic machines working equipment by means of differential equations of acceleration and braking of the working equipment is proposed. The real control law of a hydraulic distributor electric spool is considered containing the linear law of the electric spool activation and stepped law of the electric spool deactivation. Dependences of dynamic processes of the working equipment on reduced mass, stiffness of hydraulic power cylinder, viscous drag coefficient, piston acceleration, pressure in hydraulic cylinders, inertia force are obtained. Definite recommendations relative to the reduction of dynamic loads, appearing during the working equipment control are considered as the research result. The nature and rate of parameter variations of the speed and piston acceleration dynamic process depend on the law of the ports opening and closure of the hydraulic distributor electric spool. Dynamic loads in the working equipment are decreased during a smooth linear activation of the hydraulic distributor electric spool.

DOE Office of Scientific and Technical Information (OSTI.GOV)

DiCostanzo, D; Ayan, A; Woollard, J

Purpose: To predict potential failures of hardware within the Varian TrueBeam linear accelerator in order to proactively replace parts and decrease machine downtime. Methods: Machine downtime is a problem for all radiation oncology departments and vendors. Most often it is the result of unexpected equipment failure, and increased due to lack of in-house clinical engineering support. Preventative maintenance attempts to assuage downtime, but often is ineffective at preemptively preventing many failure modes such as MLC motor failures, the need to tighten a gantry chain, or the replacement of a jaw motor, among other things. To attempt to alleviate downtime, softwaremore » was developed in house that determines the maximum value of each axis enumerated in the Truebeam trajectory log files. After patient treatments, this data is stored in a SQL database. Microsoft Power BI is used to plot the average maximum error of each day of each machine as a function of time. The results are then correlated with actual faults that occurred at the machine with the help of Varian service engineers. Results: Over the course of six months, 76,312 trajectory logs have been written into the database and plotted in Power BI. Throughout the course of analysis MLC motors have been replaced on three machines due to the early warning of the trajectory log analysis. The service engineers have also been alerted to possible gantry issues on one occasion due to the aforementioned analysis. Conclusion: Analyzing the trajectory log data is a viable and effective early warning system for potential failures of the TrueBeam linear accelerator. With further analysis and tightening of the tolerance values used to determine a possible imminent failure, it should be possible to pinpoint future issues more thoroughly and for more axes of motion.« less

Coupling machine learning with mechanistic models to study runoff production and river flow at the hillslope scale

NASA Astrophysics Data System (ADS)

Marçais, J.; Gupta, H. V.; De Dreuzy, J. R.; Troch, P. A. A.

2016-12-01

Geomorphological structure and geological heterogeneity of hillslopes are major controls on runoff responses. The diversity of hillslopes (morphological shapes and geological structures) on one hand, and the highly non linear runoff mechanism response on the other hand, make it difficult to transpose what has been learnt at one specific hillslope to another. Therefore, making reliable predictions on runoff appearance or river flow for a given hillslope is a challenge. Applying a classic model calibration (based on inverse problems technique) requires doing it for each specific hillslope and having some data available for calibration. When applied to thousands of cases it cannot always be promoted. Here we propose a novel modeling framework based on coupling process based models with data based approach. First we develop a mechanistic model, based on hillslope storage Boussinesq equations (Troch et al. 2003), able to model non linear runoff responses to rainfall at the hillslope scale. Second we set up a model database, representing thousands of non calibrated simulations. These simulations investigate different hillslope shapes (real ones obtained by analyzing 5m digital elevation model of Brittany and synthetic ones), different hillslope geological structures (i.e. different parametrizations) and different hydrologic forcing terms (i.e. different infiltration chronicles). Then, we use this model library to train a machine learning model on this physically based database. Machine learning model performance is then assessed by a classic validating phase (testing it on new hillslopes and comparing machine learning with mechanistic outputs). Finally we use this machine learning model to learn what are the hillslope properties controlling runoffs. This methodology will be further tested combining synthetic datasets with real ones.

Optimization of classification and regression analysis of four monoclonal antibodies from Raman spectra using collaborative machine learning approach.

PubMed

Le, Laetitia Minh Maï; Kégl, Balázs; Gramfort, Alexandre; Marini, Camille; Nguyen, David; Cherti, Mehdi; Tfaili, Sana; Tfayli, Ali; Baillet-Guffroy, Arlette; Prognon, Patrice; Chaminade, Pierre; Caudron, Eric

2018-07-01

The use of monoclonal antibodies (mAbs) constitutes one of the most important strategies to treat patients suffering from cancers such as hematological malignancies and solid tumors. These antibodies are prescribed by the physician and prepared by hospital pharmacists. An analytical control enables the quality of the preparations to be ensured. The aim of this study was to explore the development of a rapid analytical method for quality control. The method used four mAbs (Infliximab, Bevacizumab, Rituximab and Ramucirumab) at various concentrations and was based on recording Raman data and coupling them to a traditional chemometric and machine learning approach for data analysis. Compared to conventional linear approach, prediction errors are reduced with a data-driven approach using statistical machine learning methods. In the latter, preprocessing and predictive models are jointly optimized. An additional original aspect of the work involved on submitting the problem to a collaborative data challenge platform called Rapid Analytics and Model Prototyping (RAMP). This allowed using solutions from about 300 data scientists in collaborative work. Using machine learning, the prediction of the four mAbs samples was considerably improved. The best predictive model showed a combined error of 2.4% versus 14.6% using linear approach. The concentration and classification errors were 5.8% and 0.7%, only three spectra were misclassified over the 429 spectra of the test set. This large improvement obtained with machine learning techniques was uniform for all molecules but maximal for Bevacizumab with an 88.3% reduction on combined errors (2.1% versus 17.9%). Copyright © 2018 Elsevier B.V. All rights reserved.

Cobalt-60 Machines and Medical Linear Accelerators: Competing Technologies for External Beam Radiotherapy.

PubMed

Healy, B J; van der Merwe, D; Christaki, K E; Meghzifene, A

2017-02-01

Medical linear accelerators (linacs) and cobalt-60 machines are both mature technologies for external beam radiotherapy. A comparison is made between these two technologies in terms of infrastructure and maintenance, dosimetry, shielding requirements, staffing, costs, security, patient throughput and clinical use. Infrastructure and maintenance are more demanding for linacs due to the complex electric componentry. In dosimetry, a higher beam energy, modulated dose rate and smaller focal spot size mean that it is easier to create an optimised treatment with a linac for conformal dose coverage of the tumour while sparing healthy organs at risk. In shielding, the requirements for a concrete bunker are similar for cobalt-60 machines and linacs but extra shielding and protection from neutrons are required for linacs. Staffing levels can be higher for linacs and more staff training is required for linacs. Life cycle costs are higher for linacs, especially multi-energy linacs. Security is more complex for cobalt-60 machines because of the high activity radioactive source. Patient throughput can be affected by source decay for cobalt-60 machines but poor maintenance and breakdowns can severely affect patient throughput for linacs. In clinical use, more complex treatment techniques are easier to achieve with linacs, and the availability of electron beams on high-energy linacs can be useful for certain treatments. In summary, there is no simple answer to the question of the choice of either cobalt-60 machines or linacs for radiotherapy in low- and middle-income countries. In fact a radiotherapy department with a combination of technologies, including orthovoltage X-ray units, may be an option. Local needs, conditions and resources will have to be factored into any decision on technology taking into account the characteristics of both forms of teletherapy, with the primary goal being the sustainability of the radiotherapy service over the useful lifetime of the equipment. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Machine Learning to Improve Energy Expenditure Estimation in Children With Disabilities: A Pilot Study in Duchenne Muscular Dystrophy.

PubMed

Pande, Amit; Mohapatra, Prasant; Nicorici, Alina; Han, Jay J

2016-07-19

Children with physical impairments are at a greater risk for obesity and decreased physical activity. A better understanding of physical activity pattern and energy expenditure (EE) would lead to a more targeted approach to intervention. This study focuses on studying the use of machine-learning algorithms for EE estimation in children with disabilities. A pilot study was conducted on children with Duchenne muscular dystrophy (DMD) to identify important factors for determining EE and develop a novel algorithm to accurately estimate EE from wearable sensor-collected data. There were 7 boys with DMD, 6 healthy control boys, and 22 control adults recruited. Data were collected using smartphone accelerometer and chest-worn heart rate sensors. The gold standard EE values were obtained from the COSMED K4b2 portable cardiopulmonary metabolic unit worn by boys (aged 6-10 years) with DMD and controls. Data from this sensor setup were collected simultaneously during a series of concurrent activities. Linear regression and nonlinear machine-learning-based approaches were used to analyze the relationship between accelerometer and heart rate readings and COSMED values. Existing calorimetry equations using linear regression and nonlinear machine-learning-based models, developed for healthy adults and young children, give low correlation to actual EE values in children with disabilities (14%-40%). The proposed model for boys with DMD uses ensemble machine learning techniques and gives a 91% correlation with actual measured EE values (root mean square error of 0.017). Our results confirm that the methods developed to determine EE using accelerometer and heart rate sensor values in normal adults are not appropriate for children with disabilities and should not be used. A much more accurate model is obtained using machine-learning-based nonlinear regression specifically developed for this target population. ©Amit Pande, Prasant Mohapatra, Alina Nicorici, Jay J Han. Originally published in JMIR Rehabilitation and Assistive Technology (http://rehab.jmir.org), 19.07.2016.

On recovering distributed IP information from inductive source time domain electromagnetic data

NASA Astrophysics Data System (ADS)

Kang, Seogi; Oldenburg, Douglas W.

2016-10-01

We develop a procedure to invert time domain induced polarization (IP) data for inductive sources. Our approach is based upon the inversion methodology in conventional electrical IP (EIP), which uses a sensitivity function that is independent of time. However, significant modifications are required for inductive source IP (ISIP) because electric fields in the ground do not achieve a steady state. The time-history for these fields needs to be evaluated and then used to define approximate IP currents. The resultant data, either a magnetic field or its derivative, are evaluated through the Biot-Savart law. This forms the desired linear relationship between data and pseudo-chargeability. Our inversion procedure has three steps: (1) Obtain a 3-D background conductivity model. We advocate, where possible, that this be obtained by inverting early-time data that do not suffer significantly from IP effects. (2) Decouple IP responses embedded in the observations by forward modelling the TEM data due to a background conductivity and subtracting these from the observations. (3) Use the linearized sensitivity function to invert data at each time channel and recover pseudo-chargeability. Post-interpretation of the recovered pseudo-chargeabilities at multiple times allows recovery of intrinsic Cole-Cole parameters such as time constant and chargeability. The procedure is applicable to all inductive source survey geometries but we focus upon airborne time domain EM (ATEM) data with a coincident-loop configuration because of the distinctive negative IP signal that is observed over a chargeable body. Several assumptions are adopted to generate our linearized modelling but we systematically test the capability and accuracy of the linearization for ISIP responses arising from different conductivity structures. On test examples we show: (1) our decoupling procedure enhances the ability to extract information about existence and location of chargeable targets directly from the data maps; (2) the horizontal location of a target body can be well recovered through inversion; (3) the overall geometry of a target body might be recovered but for ATEM data a depth weighting is required in the inversion; (4) we can recover estimates of intrinsic τ and η that may be useful for distinguishing between two chargeable targets.

Linear Optimization and Image Reconstruction

DTIC Science & Technology

1994-06-01

final example is again a novel one. We formulate the problem of computer assisted tomographic ( CAT ) image reconstruction as a linear optimization...possibility that a patient, Fred, suffers from a brain tumor. Further, the physician opts to make use of the CAT (Computer Aided Tomography) scan device...and examine the inside of Fred’s head without exploratory surgery. The CAT scan machine works by projecting a finite number of X-rays of known

Physics Notes.

ERIC Educational Resources Information Center

School Science Review, 1982

1982-01-01

Outlines methodology, demonstrations, and materials including: an inexpensive wave machine; speed of sound in carbon dioxide; diffraction grating method for measuring spectral line wavelength; linear electronic thermometer; analogy for bromine diffusion; direct reading refractice index meter; inexpensive integrated circuit spectrophotometer; and…

Induction and repair of DNA double-strand breaks in rat cerebellar cortex exposed to 60Co γ-rays

NASA Astrophysics Data System (ADS)

Bulanova, T. S.; Zadneprianetc, M. G.; Ježková, L.; Kruglyakova, E. A.; Smirnova, E. V.; Boreyko, A. V.

2018-01-01

The induction and repair of DNA double-strand breaks are studied using the immunohistochemical staining procedure of paraffin-embedded rat cerebellum tissues after exposure to γ-rays of 60Co. The dose dependence of radiation-induced colocalized γH2AX/53BP1 foci is studied and its linear character is established. It is shown that these foci are efficiently eliminated 24 h after irradiation.

Applying machine learning classification techniques to automate sky object cataloguing

NASA Astrophysics Data System (ADS)

Fayyad, Usama M.; Doyle, Richard J.; Weir, W. Nick; Djorgovski, Stanislav

1993-08-01

We describe the application of an Artificial Intelligence machine learning techniques to the development of an automated tool for the reduction of a large scientific data set. The 2nd Mt. Palomar Northern Sky Survey is nearly completed. This survey provides comprehensive coverage of the northern celestial hemisphere in the form of photographic plates. The plates are being transformed into digitized images whose quality will probably not be surpassed in the next ten to twenty years. The images are expected to contain on the order of 107 galaxies and 108 stars. Astronomers wish to determine which of these sky objects belong to various classes of galaxies and stars. Unfortunately, the size of this data set precludes analysis in an exclusively manual fashion. Our approach is to develop a software system which integrates the functions of independently developed techniques for image processing and data classification. Digitized sky images are passed through image processing routines to identify sky objects and to extract a set of features for each object. These routines are used to help select a useful set of attributes for classifying sky objects. Then GID3 (Generalized ID3) and O-B Tree, two inductive learning techniques, learns classification decision trees from examples. These classifiers will then be applied to new data. These developmnent process is highly interactive, with astronomer input playing a vital role. Astronomers refine the feature set used to construct sky object descriptions, and evaluate the performance of the automated classification technique on new data. This paper gives an overview of the machine learning techniques with an emphasis on their general applicability, describes the details of our specific application, and reports the initial encouraging results. The results indicate that our machine learning approach is well-suited to the problem. The primary benefit of the approach is increased data reduction throughput. Another benefit is consistency of classification. The classification rules which are the product of the inductive learning techniques will form an objective, examinable basis for classifying sky objects. A final, not to be underestimated benefit is that astronomers will be freed from the tedium of an intensely visual task to pursue more challenging analysis and interpretation problems based on automatically catalogued data.

Quantum annealing versus classical machine learning applied to a simplified computational biology problem

PubMed Central

Li, Richard Y.; Di Felice, Rosa; Rohs, Remo; Lidar, Daniel A.

2018-01-01

Transcription factors regulate gene expression, but how these proteins recognize and specifically bind to their DNA targets is still debated. Machine learning models are effective means to reveal interaction mechanisms. Here we studied the ability of a quantum machine learning approach to predict binding specificity. Using simplified datasets of a small number of DNA sequences derived from actual binding affinity experiments, we trained a commercially available quantum annealer to classify and rank transcription factor binding. The results were compared to state-of-the-art classical approaches for the same simplified datasets, including simulated annealing, simulated quantum annealing, multiple linear regression, LASSO, and extreme gradient boosting. Despite technological limitations, we find a slight advantage in classification performance and nearly equal ranking performance using the quantum annealer for these fairly small training data sets. Thus, we propose that quantum annealing might be an effective method to implement machine learning for certain computational biology problems. PMID:29652405

Nonlinear programming for classification problems in machine learning

NASA Astrophysics Data System (ADS)

Astorino, Annabella; Fuduli, Antonio; Gaudioso, Manlio

2016-10-01

We survey some nonlinear models for classification problems arising in machine learning. In the last years this field has become more and more relevant due to a lot of practical applications, such as text and web classification, object recognition in machine vision, gene expression profile analysis, DNA and protein analysis, medical diagnosis, customer profiling etc. Classification deals with separation of sets by means of appropriate separation surfaces, which is generally obtained by solving a numerical optimization model. While linear separability is the basis of the most popular approach to classification, the Support Vector Machine (SVM), in the recent years using nonlinear separating surfaces has received some attention. The objective of this work is to recall some of such proposals, mainly in terms of the numerical optimization models. In particular we tackle the polyhedral, ellipsoidal, spherical and conical separation approaches and, for some of them, we also consider the semisupervised versions.

Strike action electromagnetic machine for immersion of rod elements into ground

NASA Astrophysics Data System (ADS)

Usanov, K. M.; Volgin, A. V.; Chetverikov, E. A.; Kargin, V. A.; Moiseev, A. P.; Ivanova, Z. I.

2017-10-01

During construction, survey work, and drilling shallow wells by striking, operations associated with dipping and removing the rod elements are the most common. At the same time relatively long, with small diameter, elements, in which the ratio of length to diameter l/d is 100 or more, constitute a significant proportion. At present, the application of power pulse linear electromagnetic motors to drive drum machines is recognized to be highly effective. However, the mechanical method of transmission of shocks does not allow dipping long longitudinally unstable core elements. In this case, mechanical energy must be transferred from the motor to the rod through its side surface. The design of the strike action electromagnetic machine with a through axial channel for non-mechanical end striking of the pile of long, longitudinally unstable metal rods is proposed. Electromagnetic striking machine for non-mechanical end striking rod elements provides operations characterized by ecological compatibility, safety and high quality.

Stirling cryocooler test results and design model verification

NASA Astrophysics Data System (ADS)

Shimko, Martin A.; Stacy, W. D.; McCormick, John A.

A long-life Stirling cycle cryocooler being developed for spaceborne applications is described. The results from tests on a preliminary breadboard version of the cryocooler used to demonstrate the feasibility of the technology and to validate the generator design code used in its development are presented. This machine achieved a cold-end temperature of 65 K while carrying a 1/2-W cooling load. The basic machine is a double-acting, flexure-bearing, split Stirling design with linear electromagnetic drives for the expander and compressors. Flat metal diaphragms replace pistons for sweeping and sealing the machine working volumes. The double-acting expander couples to a laminar-channel counterflow recuperative heat exchanger for regeneration. The PC-compatible design code developed for this design approach calculates regenerator loss, including heat transfer irreversibilities, pressure drop, and axial conduction in the regenerator walls. The code accurately predicted cooler performance and assisted in diagnosing breadboard machine flaws during shakedown and development testing.

Thermocouple and infrared sensor-based measurement of temperature distribution in metal cutting.

PubMed

Kus, Abdil; Isik, Yahya; Cakir, M Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-12

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining.

Thermocouple and Infrared Sensor-Based Measurement of Temperature Distribution in Metal Cutting

PubMed Central

Kus, Abdil; Isik, Yahya; Cakir, M. Cemal; Coşkun, Salih; Özdemir, Kadir

2015-01-01

In metal cutting, the magnitude of the temperature at the tool-chip interface is a function of the cutting parameters. This temperature directly affects production; therefore, increased research on the role of cutting temperatures can lead to improved machining operations. In this study, tool temperature was estimated by simultaneous temperature measurement employing both a K-type thermocouple and an infrared radiation (IR) pyrometer to measure the tool-chip interface temperature. Due to the complexity of the machining processes, the integration of different measuring techniques was necessary in order to obtain consistent temperature data. The thermal analysis results were compared via the ANSYS finite element method. Experiments were carried out in dry machining using workpiece material of AISI 4140 alloy steel that was heat treated by an induction process to a hardness of 50 HRC. A PVD TiAlN-TiN-coated WNVG 080404-IC907 carbide insert was used during the turning process. The results showed that with increasing cutting speed, feed rate and depth of cut, the tool temperature increased; the cutting speed was found to be the most effective parameter in assessing the temperature rise. The heat distribution of the cutting tool, tool-chip interface and workpiece provided effective and useful data for the optimization of selected cutting parameters during orthogonal machining. PMID:25587976

Design and analysis of linear cascade DNA hybridization chain reactions using DNA hairpins

NASA Astrophysics Data System (ADS)

Bui, Hieu; Garg, Sudhanshu; Miao, Vincent; Song, Tianqi; Mokhtar, Reem; Reif, John

2017-01-01

DNA self-assembly has been employed non-conventionally to construct nanoscale structures and dynamic nanoscale machines. The technique of hybridization chain reactions by triggered self-assembly has been shown to form various interesting nanoscale structures ranging from simple linear DNA oligomers to dendritic DNA structures. Inspired by earlier triggered self-assembly works, we present a system for controlled self-assembly of linear cascade DNA hybridization chain reactions using nine distinct DNA hairpins. NUPACK is employed to assist in designing DNA sequences and Matlab has been used to simulate DNA hairpin interactions. Gel electrophoresis and ensemble fluorescence reaction kinetics data indicate strong evidence of linear cascade DNA hybridization chain reactions. The half-time completion of the proposed linear cascade reactions indicates a linear dependency on the number of hairpins.

Maternal exposure to ambient PM10 during pregnancy increases the risk of congenital heart defects: Evidence from machine learning models.

PubMed

Ren, Zhoupeng; Zhu, Jun; Gao, Yanfang; Yin, Qian; Hu, Maogui; Dai, Li; Deng, Changfei; Yi, Lin; Deng, Kui; Wang, Yanping; Li, Xiaohong; Wang, Jinfeng

2018-07-15

Previous research suggested an association between maternal exposure to ambient air pollutants and risk of congenital heart defects (CHDs), though the effects of particulate matter ≤10μm in aerodynamic diameter (PM 10 ) on CHDs are inconsistent. We used two machine learning models (i.e., random forest (RF) and gradient boosting (GB)) to investigate the non-linear effects of PM 10 exposure during the critical time window, weeks 3-8 in pregnancy, on risk of CHDs. From 2009 through 2012, we carried out a population-based birth cohort study on 39,053 live-born infants in Beijing. RF and GB models were used to calculate odds ratios for CHDs associated with increase in PM 10 exposure, adjusting for maternal and perinatal characteristics. Maternal exposure to PM 10 was identified as the primary risk factor for CHDs in all machine learning models. We observed a clear non-linear effect of maternal exposure to PM 10 on CHDs risk. Compared to 40μgm -3 , the following odds ratios resulted: 1) 92μgm -3 [RF: 1.16 (95% CI: 1.06, 1.28); GB: 1.26 (95% CI: 1.17, 1.35)]; 2) 111μgm -3 [RF: 1.04 (95% CI: 0.96, 1.14); GB: 1.04 (95% CI: 0.99, 1.08)]; 3) 124μgm -3 [RF: 1.01 (95% CI: 0.94, 1.10); GB: 0.98 (95% CI: 0.93, 1.02)]; 4) 190μgm -3 [RF: 1.29 (95% CI: 1.14, 1.44); GB: 1.71 (95% CI: 1.04, 2.17)]. Overall, both machine models showed an association between maternal exposure to ambient PM 10 and CHDs in Beijing, highlighting the need for non-linear methods to investigate dose-response relationships. Copyright © 2018 Elsevier B.V. All rights reserved.

Comparative analysis of expert and machine-learning methods for classification of body cavity effusions in companion animals.

PubMed

Hotz, Christine S; Templeton, Steven J; Christopher, Mary M

2005-03-01

A rule-based expert system using CLIPS programming language was created to classify body cavity effusions as transudates, modified transudates, exudates, chylous, and hemorrhagic effusions. The diagnostic accuracy of the rule-based system was compared with that produced by 2 machine-learning methods: Rosetta, a rough sets algorithm and RIPPER, a rule-induction method. Results of 508 body cavity fluid analyses (canine, feline, equine) obtained from the University of California-Davis Veterinary Medical Teaching Hospital computerized patient database were used to test CLIPS and to test and train RIPPER and Rosetta. The CLIPS system, using 17 rules, achieved an accuracy of 93.5% compared with pathologist consensus diagnoses. Rosetta accurately classified 91% of effusions by using 5,479 rules. RIPPER achieved the greatest accuracy (95.5%) using only 10 rules. When the original rules of the CLIPS application were replaced with those of RIPPER, the accuracy rates were identical. These results suggest that both rule-based expert systems and machine-learning methods hold promise for the preliminary classification of body fluids in the clinical laboratory.

A Life Study of Ausforged, Standard Forged and Standard Machined AISI M-50 Spur Gears

NASA Technical Reports Server (NTRS)

Townsend, D. P.; Bamberger, E. N.; Zaretsky, E. V.

1975-01-01

Tests were conducted at 350 K (170 F) with three groups of 8.9 cm (3.5 in.) pitch diameter spur gears made of vacuum induction melted (VIM) consumable-electrode vacuum-arc melted (VAR), AISI M-50 steel and one group of vacuum-arc remelted (VAR) AISI 9310 steel. The pitting fatigue life of the standard forged and ausforged gears was approximately five times that of the VAR AISI 9310 gears and ten times that of the bending fatigue life of the standard machined VIM-VAR AISI M-50 gears run under identical conditions. There was a slight decrease in the 10-percent life of the ausforged gears from that for the standard forged gears, but the difference is not statistically significant. The standard machined gears failed primarily by gear tooth fracture while the forged and ausforged VIM-VAR AISI M-50 and the VAR AISI 9310 gears failed primarily by surface pitting fatigue. The ausforged gears had a slightly greater tendency to fail by tooth fracture than the standard forged gears.

A high sensitivity wear debris sensor using ferrite cores for online oil condition monitoring

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Zhong, Chong; Zhe, Jiang

2017-07-01

Detecting wear debris and measuring the increasing number of wear debris in lubrication oil can indicate abnormal machine wear well ahead of machine failure, and thus are indispensable for online machine health monitoring. A portable wear debris sensor with ferrite cores for online monitoring is presented. The sensor detects wear debris by measuring the inductance change of two planar coils wound around a pair of ferrite cores that make the magnetic flux denser and more uniform in the sensing channel, thereby improving the sensitivity of the sensor. Static testing results showed this wear debris sensor is capable of detecting 11 µm and 50 µm ferrous debris in 1 mm and 7 mm diameter fluidic pipes, respectively; such a high sensitivity has not been achieved before. Furthermore, a synchronized sampling method was also applied to reduce the data size and realize real-time data processing. Dynamic testing results demonstrated that the sensor is capable of detecting wear debris in real time with a high throughput of 750 ml min-1 the measured debris concentration is in good agreement with the actual concentration.

Design and analysis of a 3D-flux flux-switching permanent magnet machine with SMC cores and ferrite magnets

NASA Astrophysics Data System (ADS)

Liu, Chengcheng; Wang, Youhua; Lei, Gang; Guo, Youguang; Zhu, Jianguo

2017-05-01

Since permanent magnets (PM) are stacked between the adjacent stator teeth and there are no windings or PMs on the rotor, flux-switching permanent magnet machine (FSPMM) owns the merits of good flux concentrating and robust rotor structure. Compared with the traditional PM machines, FSPMM can provide higher torque density and better thermal dissipation ability. Combined with the soft magnetic composite (SMC) material and ferrite magnets, this paper proposes a new 3D-flux FSPMM (3DFFSPMM). The topology and operation principle are introduced. It can be found that the designed new 3DFFSPMM has many merits over than the traditional FSPMM for it can utilize the advantages of SMC material. Moreover, the PM flux of this new motor can be regulated by using the mechanical method. 3D finite element method (FEM) is used to calculate the magnetic field and parameters of the motor, such as flux density, inductance, PM flux linkage and efficiency map. The demagnetization analysis of the ferrite magnet is also addressed to ensure the safety operation of the proposed motor.

Numerical Technology for Large-Scale Computational Electromagnetics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharpe, R; Champagne, N; White, D

The key bottleneck of implicit computational electromagnetics tools for large complex geometries is the solution of the resulting linear system of equations. The goal of this effort was to research and develop critical numerical technology that alleviates this bottleneck for large-scale computational electromagnetics (CEM). The mathematical operators and numerical formulations used in this arena of CEM yield linear equations that are complex valued, unstructured, and indefinite. Also, simultaneously applying multiple mathematical modeling formulations to different portions of a complex problem (hybrid formulations) results in a mixed structure linear system, further increasing the computational difficulty. Typically, these hybrid linear systems aremore » solved using a direct solution method, which was acceptable for Cray-class machines but does not scale adequately for ASCI-class machines. Additionally, LLNL's previously existing linear solvers were not well suited for the linear systems that are created by hybrid implicit CEM codes. Hence, a new approach was required to make effective use of ASCI-class computing platforms and to enable the next generation design capabilities. Multiple approaches were investigated, including the latest sparse-direct methods developed by our ASCI collaborators. In addition, approaches that combine domain decomposition (or matrix partitioning) with general-purpose iterative methods and special purpose pre-conditioners were investigated. Special-purpose pre-conditioners that take advantage of the structure of the matrix were adapted and developed based on intimate knowledge of the matrix properties. Finally, new operator formulations were developed that radically improve the conditioning of the resulting linear systems thus greatly reducing solution time. The goal was to enable the solution of CEM problems that are 10 to 100 times larger than our previous capability.« less

Comparison of linear and non-linear models for predicting energy expenditure from raw accelerometer data.

PubMed

Montoye, Alexander H K; Begum, Munni; Henning, Zachary; Pfeiffer, Karin A

2017-02-01

This study had three purposes, all related to evaluating energy expenditure (EE) prediction accuracy from body-worn accelerometers: (1) compare linear regression to linear mixed models, (2) compare linear models to artificial neural network models, and (3) compare accuracy of accelerometers placed on the hip, thigh, and wrists. Forty individuals performed 13 activities in a 90 min semi-structured, laboratory-based protocol. Participants wore accelerometers on the right hip, right thigh, and both wrists and a portable metabolic analyzer (EE criterion). Four EE prediction models were developed for each accelerometer: linear regression, linear mixed, and two ANN models. EE prediction accuracy was assessed using correlations, root mean square error (RMSE), and bias and was compared across models and accelerometers using repeated-measures analysis of variance. For all accelerometer placements, there were no significant differences for correlations or RMSE between linear regression and linear mixed models (correlations: r  =  0.71-0.88, RMSE: 1.11-1.61 METs; p  >  0.05). For the thigh-worn accelerometer, there were no differences in correlations or RMSE between linear and ANN models (ANN-correlations: r  =  0.89, RMSE: 1.07-1.08 METs. Linear models-correlations: r  =  0.88, RMSE: 1.10-1.11 METs; p  >  0.05). Conversely, one ANN had higher correlations and lower RMSE than both linear models for the hip (ANN-correlation: r  =  0.88, RMSE: 1.12 METs. Linear models-correlations: r  =  0.86, RMSE: 1.18-1.19 METs; p  <  0.05), and both ANNs had higher correlations and lower RMSE than both linear models for the wrist-worn accelerometers (ANN-correlations: r  =  0.82-0.84, RMSE: 1.26-1.32 METs. Linear models-correlations: r  =  0.71-0.73, RMSE: 1.55-1.61 METs; p  <  0.01). For studies using wrist-worn accelerometers, machine learning models offer a significant improvement in EE prediction accuracy over linear models. Conversely, linear models showed similar EE prediction accuracy to machine learning models for hip- and thigh-worn accelerometers and may be viable alternative modeling techniques for EE prediction for hip- or thigh-worn accelerometers.

Monitoring Temperature and Fan Speed Using Ganglia and Winbond Chips

DOE Office of Scientific and Technical Information (OSTI.GOV)

McCaffrey, Cattie; /SLAC

2006-09-27

Effective monitoring is essential to keep a large group of machines, like the ones at Stanford Linear Accelerator Center (SLAC), up and running. SLAC currently uses Ganglia Monitoring System to observe about 2000 machines, analyzing metrics like CPU usage and I/O rate. However, metrics essential to machine hardware health, such as temperature and fan speed, are not being monitored. Many machines have a Winbond w83782d chip which monitors three temperatures, two of which come from dual CPUs, and returns the information when the sensor command is invoked. Ganglia also provides a feature, gmetric, that allows the users to monitor theirmore » own metrics and incorporate them into the monitoring system. The programming language Perl is chosen to implement a script that invokes the sensors command, extracts the temperature and fan speed information, and calls gmetric with the appropriate arguments. Two machines were used to test the script; the two CPUs on each machine run at about 65 Celsius, which is well within the operating temperature range (The maximum safe temperature range is 77-82 Celsius for the Pentium III processors being used). Installing the script on all machines with a Winbond w83782d chip allows the SLAC Scientific Computing and Computing Services group (SCCS) to better evaluate current cooling methods.« less

Stability Assessment of a System Comprising a Single Machine and Inverter with Scalable Ratings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Brian B; Lin, Yashen; Gevorgian, Vahan

From the inception of power systems, synchronous machines have acted as the foundation of large-scale electrical infrastructures and their physical properties have formed the cornerstone of system operations. However, power electronics interfaces are playing a growing role as they are the primary interface for several types of renewable energy sources and storage technologies. As the role of power electronics in systems continues to grow, it is crucial to investigate the properties of bulk power systems in low inertia settings. In this paper, we assess the properties of coupled machine-inverter systems by studying an elementary system comprised of a synchronous generator,more » three-phase inverter, and a load. Furthermore, the inverter model is formulated such that its power rating can be scaled continuously across power levels while preserving its closed-loop response. Accordingly, the properties of the machine-inverter system can be assessed for varying ratios of machine-to-inverter power ratings and, hence, differing levels of inertia. After linearizing the model and assessing its eigenvalues, we show that system stability is highly dependent on the interaction between the inverter current controller and machine exciter, thus uncovering a key concern with mixed machine-inverter systems and motivating the need for next-generation grid-stabilizing inverter controls.« less