基于LabVIEW的异步电机转子断条检测

针对三相异步电动转子断条的故障检测中故障信号很小,其与基波频率很接近,可能被基波分量泄漏或噪声所淹没,不能准确的判断。提出了一种LabVIEW平台下基于数字滤波、频谱细化分析和定子电流齿槽谐波分量的转差率在线检测方法。先对提取到的定子电流进行频谱细化分析,提高频谱分辨率,然后设计一个数字滤波器滤除定子电流基频信号,避免基波分量造成干扰。详细介绍了定子电流齿槽谐波分量的转差率估计的原理,通过该方法找出故障信号,并有效的区分出段子断条故障和负载波动。仿真和实验结果表明,该方法能够准确的找到故障信号,解决基波分量泄漏等引起的干扰,提高故障检测的可靠性和准确性。     

A comparison of external and internal methods of signal spectral analysis for broken rotor bars detection in induction motors

Like all mechanical devices, motors are subject to failures, which can sometimes lead to the shutting down of an entire industrial process. This paper looks at failure predictions in three-phase line-operated induction machines through spectral analysis or electric and electromagnetic signals. Fault characteristics frequencies generated in the estimated and the measured signal spectrum, as a result of mechanical abnormalities such as broken rotor bars, are analyzed. Spectral analyses of simple stator current, of the current's Park vector modulus, and or total and partial instantaneous electric powers are considered as external diagnosis. Internal methods of diagnosis are usually based on a mathematical model of the motor. This requires knowledge of the motor's electrical parameters, which are affected by a number of physical phenomena such as temperature variations, skin effects, core losses, and saturation. As internal diagnosis, we examine different approaches to the spectral analysis of electromagnetic torque computed by stator and rotor flux estimation. To this end, the open loop method, the Luenberger observer and the Kalman filter are employed. Finally, experimental results enable us to draw up a table of comparison of internal and external methods in the detection of rotor imperfections, using two criteria under different load levels.     

Matrix approach to steady-state analysis of invertor-fed induction motors

The output voltage of a static invertor is frequently a piecewise-constant periodic waveform. For such cases, and using the properties of the transition matrix, a method is presented for determining the steady-state current waveform.     

A self-commissioning algorithm for VSI-fed induction motors

In the paper, a self-commissioning algorithm is presented, which allows the determination of the parameters of an induction motor fed by a VSI, without any additional hardware, with respect to the one required by a vectorial control strategy. It is based upon the comparison between the measured and the predicted current response of the motor to an adequate feeding voltage waveform. The algorithm can be easily implemented as a start-up routine of the control software. In this way, a precise and quick evaluation of the motor parameters can be achieved. The validity and feasibility of the proposed algorithm are proved by experimental implementation.     

Different indexes for eccentricity faults diagnosis in three-phase squirrel-cage induction motors: A review

In this paper, a short introduction about different types of eccentricity faults in three-phase squirrel-cage induction motors is presented and their effects and consequences on the health and behavior of the motor are reviewed. Two fault diagnosis techniques are discussed, namely: invasive and non-invasive techniques. The relative advantages of the non-invasive techniques are also discussed. Various indices used in the non-invasive techniques are then briefly introduced and some outlines for continuing the research on every index are given. The advantages and disadvantages of the indices under different operating conditions and for any type and eccentricity degree are then discussed together with some effective parameters of the motor. The results of this review are useful for manufacturers of fault diagnosis systems in selecting proper indices for existing conditions and also for researchers in determining further research areas.     

A three-phase multilevel converter for high-power induction motors

A new converter topology for drives is presented in this paper: a three-phase multilevel converter with separately regulated DC power supplies. The DC voltages are provided by medium-frequency DC-DC converters. The applications for the converter are especially high-power traction systems, where the voltage applied to the induction motor is bigger than 1 kV. The motor current is of a very high quality, compared to a classical three-phase converter. This allows keeping the switching frequency low by using phase-shifted pulsewidth modulation (PWM) carriers. Different modulation methods have been developed and simulated. Experimental tests have been made on a 12 kW prototype     

A discrete model of induction motors for real-time controlapplications

The real-time digital control of induction motors and AC servomotor drives often involves estimation, identification, and adaptive control algorithms. An efficient and numerically stable discrete model of the induction motor is required to implement these algorithms in real time. A predictor-corrector discrete model of induction motors is developed here for real-time model is analyzed by a discrete root locus technique. The digital simulation of the model is presented and compared with a rigorous solution, and satisfactory results are obtained     

Multiple error detection and identification via signature analysis

Signature analysis has been used widely for fault detection as a part of Built-In Self Test (BIST). In this paper we show how signature analysis can be used not only for fault detection but also for identification of multiple errors produced by faults in the circuits under test. We construct Signature Analysis Registers (SARs) to detect and identify any specified number of errors in the input polynomials by choosing proper characteristic polynomials. To detect and identifyr errors in an input bit stream ofm bits, we use a polynomialg _r (x)=1cm (f ₁ (x), f ₃ (x), ..., f _2r?1 (x)) as the characteristic polynomial for the SAR for any polynomialf ₁ (x), where lcm represents the least common multiple of polynomials al $$fi(x) = Res_t (f_1 (t),x - t^i ), i = 3,...,2r - 1,$$ Res _t denotes thet-Resultant, andm is less than the order off ₁ (x). Given a faulty signature produced by an SAR constructed as described, we present an algorithm for the identification of the actual error bits in the input polynomial to the SAR. We also extend the use of BCH codes for error detection and correction to include nonprimitive polynomials.     

Passivity-based control of saturated induction motors

A passivity-based controller, which takes into account saturation of the magnetic material in the main flux path of the induction motor, is developed to provide close tracking of time-varying speed and flux trajectories in the high magnetic saturation regions. The proposed passivity based controller is experimentally verified. Also, a comparison between the controllers based on the saturated and nonsaturated magnetics is presented to demonstrate the benefit of the controller based on the saturated magnetics     

Sensorless sliding-mode control of induction motors

This paper develops the ideas of speed- and flux-sensorless sliding-mode control for an induction motor illustrated in previous work by one of the authors. A sliding-mode observer/controller is proposed in this paper. The convergence of the nonlinear time-varying observer along with the asymptotic stability of the controller is analyzed. Pulsewidth modulation implementation using sliding-mode concepts is also discussed. Major attention is paid to torque control, and then the developed approach is utilized for speed control. Computer simulations and experiments have been carried out to test the proposed estimation and control algorithm. The experimental results demonstrated high efficiency of the proposed estimation and control method.     

Sensorless fault diagnosis of induction motors

Early detection and diagnosis of incipient faults is desirable for online condition assessment, product quality assurance, and improved operational efficiency of induction motors. In this paper, a speed-sensorless fault diagnosis system is developed for induction motors, using recurrent dynamic neural networks and multiresolution or Fourier-based signal processing for transient or quasi-steady-state operation, respectively. In addition to nameplate information required for the initial system setup, the proposed fault diagnosis system uses only motor terminal voltages and currents. The effectiveness of the proposed diagnosis system in detecting the most widely encountered motor electrical and mechanical faults is demonstrated through extensive staged faults. The developed system is scalable to different power ratings and it has been successfully demonstrated with data from 2.2, 373 and 597 kW induction motors.     

A vector control scheme for EV induction motors with a series ironloss model

Electric vehicle (EV) motors are characterized by their low inductance and high current density, so that they run at high speed and produce a high starting torque. Due to the low inductance coil design, the current ripple caused by pulsewidth modulation (PWM) switching makes a significant amount of eddy-current loss and hysteresis loss, especially in high-speed operation. If one simply neglects the iron loss, the overall vector controller is detuned, resulting in an error in the torque control. The iron loss is modeled, in general, by a parallel resistor R_M to the magnetizing inductor L_M. The authors propose a series R-L model that accounts for the effects of the iron loss. A major advantage of the series model is that it does not increase the number of state variables in developing a vector control. In this paper, they derive a rotor-flux-oriented flux error, orientation angle error, and torque error caused by iron loss. Finally, they demonstrate the effectiveness of the proposed control method through computer simulation and experimental results     

Calculating the efficiency of three-phase induction motors

A method for computing the efficiency of a three-phase induction motor using the input phassor currents for blocked motor, no load, and running with load, is presented.     

The history of induction motors in America

This paper briefly reviews the history of the induction motor from its invention by Nicola Tesla in 1888 through the various stages of its development-the invention of the cast aluminum squirrelcage winding, improvements in magnetic steel and insulation, and the progressive reduction of the dimensions for a given horsepower rating, so that today a 100-hp motor has the same mounting dimensions as the 7.5-hp motor of 1897.     

Analysis of phase-controlled converters for induction motors

A phase-controlled converter for induction motors is analyzed, using a representation of semiconductor switching devices as two-state resistances. The steady state of symmetrically controlled converters (when the states of the semiconductor switching devices change periodically) is considered, and symmetrical components of the motor phase currents are used. This allows classical equivalent circuits of the induction motor to be used. As a result of the analysis the Fourier spectrum of the motor phase currents and electromagnetic torque is determined. An example that shows the application of the relations presented here is given     

Field-oriented control of induction motors using neural-networkdecouplers

This paper presents a novel approach to the field-oriented control (FOC) of induction motor drives. It discusses the introduction of artificial neural networks (ANNs) for decoupling control of induction motors using FOC principles. Two ANNs are presented for direct and indirect FOC applications. The first performs an estimation of the stator flux for direct field orientation, and the second is trained to map the nonlinear behavior of a rotor-flux decoupling controller. A decoupling controller and flux estimator were implemented upon these ANNs using the MATLAB/SIMULINK neural-network toolbox. The data for training are obtained from a computer simulation of the system and experimental measurements. The methodology used to train the networks with the backpropagation learning process is presented. Simulation results reveal some very interesting features and show that the networks have good potential for use as an alternative to the conventional field-oriented decoupling control of induction motors     

Current signature analysis of induction motor mechanical faults by wavelet packet decomposition

This paper presents a novel approach to induction motor current signature analysis based on wavelet packet decomposition (WPD) of the stator current. The novelty of the proposed method lies in the fact that by using WPD method the inherent nonstationary nature of stator current can be accurately considered. The key characteristics of the proposed method are its ability to provide feature representations of multiple frequency resolutions for faulty modes, ability to clearly differentiate between healthy and faulty conditions, and its applicability to nonstationary signals. Successful implementation of the system for two types of faults, i.e., rotor bar breakage and air-gap eccentricity is demonstrated here. The results are validated based on both simulation and experiments of a 5-hp induction motor.     

A generic neurofuzzy model-based approach for detecting faults in induction motors

Many fault detection and diagnosis schemes are based on the concept of comparing the plant output with a model in order to generate residues. A fault is deemed to have occurred if the residue exceeds a predetermined threshold. Unfortunately, the practical usefulness of model-based fault detection schemes is limited because of the difficulty in acquiring sufficiently rich experimental data to identify an accurate model of the system characteristics. This paper aims at developing a generic neurofuzzy model-based strategy for detecting broken rotor bars, which is one of the most common type of faults that may occur in a squirrel-cage induction motor. A neurofuzzy model that captures the generic characteristics of a class of asynchronous motor is the key component of the proposed approach. It is identified using data generated by a simulation model that is constructed using information on the name plate of the motor. Customization for individual motors is then carried out by selecting the threshold for fault detection via an empirical steady-state torque-speed curve. Since data obtained from a practical motor are used to select the threshold and not to build a complete model, the objective of reducing the amount of experimental input-output data required to design a model-based fault detector may be realized. Experimental results are presented to demonstrate the viability of the proposed fault detection scheme.     

Sensorless control of induction motors by artificial neuralnetworks

In this letter, we propose a voltage-source inverter control working in the open loop of an induction motor measuring the stator current and using an artificial neural network. This technique has the mission to estimate the speed and torque of the rotor without using sensors. With this, a simple and cheap method of control is obtained, with as much precision and robustness as other more complex ones