Rotor fault condition monitoring techniques for squirrel-cage induction machine—A review

Nowadays, manufacturing companies are making great efforts to implement an effective machinery maintenance program, which provides incipient fault detection. The machine problem and its irregularity can be detected at an early stage by employing a suitable condition monitoring accompanied with powerful signal processing technique. Among various defects occurred in machines, rotor faults are of significant importance as they cause secondary failures that lead to a serious motor malfunction. Diagnosis of rotor failures has long been an important but complicated task in the area of motor faults detection. This paper intends to review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection. The aim of this article is to provide a broad outlook on rotor fault monitoring techniques for the researchers and engineers.     

电机电流分析法在机床类设备诊断中的应用研究

机床类设备传动链复杂,结构紧凑且封闭,对传动系统状态监测一直没有有效的分析办法,即使在噪声增大等恶劣情况下,常规的振动诊断方法也难以奏效.本文尝试用电流信号分析法,简称MCSA(Motor Current Signal Analysis),对机床状态进行测试和分析.通过电机电流信号的传动链齿轮谱特征分析,对其做出了正确评估,表明定子电流能很好地反映机床传动系统部件的运行状况.同时进行了多种运行工况的测试与试验,研究结论对机床类设备的生产制造和现场运行状态的分析提供了有效依据.     

基于MIRPSA的感应电动机转子断条数目诊断判据

在感应电动机转子断条数目诊断方面,电机定子电流信号分析(MCSA)类方法已经建立明确的解析判据,而电机瞬时无功功率信号分析(MIRPSA)类方法缺乏理论支撑。为此,针对转子断条故障推导了感应电动机瞬时无功功率特征分量的幅值与转子断条数目间的数值对应关系,由此建立了具有解析意义的基于MIRPSA的转子断条数目诊断判据。感应电动机转子断条故障仿真与实验证明了所提判据的有效性。     

鼠笼式异步电机转子故障程度诊断方法

针对异步电机启动阶段转子断条故障检测问题,提出了一种基于同步压缩小波变换SWT的瞬态电流特征分析方法,通过时频分布图来判断转子是否存在故障。在此基础上,通过曲线拟合的方法给出了导条电阻与SWT系数能量谱之间的关系,进一步给出了确定故障预警值和报警值的方法。最后提出了一种判断故障程度的指标。采用Ansoft Maxwell软件建立笼型异步电机故障仿真模型,仿真实验结果表明,该方法能有效地诊断转子不对称故障并评估出故障程度。     

基于MCSA的笼型异步电动机转子断条诊断

研究笼型异步电动机在转子断条时的运行情况,提出有效的检测方法,以便在电机转子只出现轻微故障时及时检测出故障,采取有效措施。MCSA技术采用时域加窗和傅里叶变换的方法,对电机电流信号进行频谱分析,并对故障频率段局部细化,提取定子电流中故障特征频率分量来诊断电动机是否存在转子断条故障。仿真结果表明本方法可以有效消除频率泄漏和栅栏现象,准确检测出故障分量。     

Bispectrum of stator phase current for fault detection of induction motor

A number of research studies has shown that faults in a stator or rotor generally show sideband frequencies around the mains frequency (50 Hz) and at higher harmonics in the spectrum of the Motor Current Signature Analysis (MCSA). However in the present experimental studies such observations have not been seen, but any fault either in the stator or the rotor may distort the sinusoidal response of the motor RPM and the mains frequency so the MCSA response may contain a number of harmonics of the motor RPM and the mains frequency. Hence the use of a higher order spectrum (HOS), namely the bispectrum of the MCSA has been proposed here because it relates both amplitude and phase of number of the harmonics in a signal. It has been observed that it not only detects early faults but also indicates the severity of the fault to some extent.     

Winding distribution effects on induction motor rotor fault diagnosis

The sidebands around stator currents harmonics as a potential tool for supporting the diagnosis of rotor faults in induction motors are analyzed in this paper. The presence of broken bars introduces high frequency components in the machine currents spectrum in addition to the characteristic sidebands around the fundamental component. These additional components are due to the interaction between, rotor asymmetry and either the voltage harmonics, or winding distribution, or rotor slots. In particular, the components at frequencies near to fifth and seventh harmonics, produced by the interaction between the rotor faults and the harmonics of the spatial distribution of stator windings, are analyzed in this work. A multiple coupled circuit model of the induction motor is used to evaluate the sensitivity of these components for different stator winding configurations, load level, supply voltage conditions, and different number of broken bars. Simulation results showed that a particular analyzed component near to fifth harmonic depends mainly on fifth harmonic of winding distribution, which remains almost constant for most common distributions. Therefore, it is expected that this component should be found in most motors with broken bars. Finally, experimental laboratory results and two industrial cases that validate the analysis are presented.     

Motor square current signature analysis for induction motor rotor diagnosis

Induction machines play an important role in today’s industry. Thus, preventive maintenance combined with fault diagnosis techniques have become an essential issue. One of the most used techniques for the diagnosis of faults in the induction machine is motor current signature analysis (MCSA). This approach presents some limitations for induction motor rotor diagnosis, particularly for small faults. In this paper, a new motor square current signature analysis (MSCSA) fault diagnosis methodology is presented. The proposed technique is based on three main steps: first, the induction motor current is measured; secondly, the square of the current is computed; and finally a frequency analysis of the square current is performed. This technique allows more information to be obtained from a motor with a rotor fault than the classical MCSA approach. Simulation and experimental results are presented in order to confirm the theoretical assumptions. This methodology has also been tested for the identification of two distinct faults (broken bars and rotor eccentricity).     

Hybrid algorithmic approach oriented to incipient rotor fault diagnosis on induction motors

This paper investigates the current monitoring for effective fault diagnosis in induction motor (IM) by using random forest (RF) algorithms. A rotor bar breakage of IM does not derive in a catastrophic fault but its timely detection can avoid catastrophic consequences in the stator or prevent malfunctioning of those applications in which this sort of fault is the primary concern. Current-based fault signatures depend enormously on the IM power source and in the load connected to the motor. Hence, homogeneous sets of current signals were acquired through multiple experiments at particular loading torques and IM feedings from an experimental test bench in which incipient rotor severities were considered. Understanding the importance of each fault signature in relation to its diagnosis performance is an interesting matter. To this end, we propose a hybrid approach based on Simulated Annealing algorithm to conduct a global search over the computed feature set for feature selection purposes, which reduce the computational requirements of the diagnosis tool. Then, a novel Oblique RF classifier is used to build multivariate trees, which explicitly learn optimal split directions at internal nodes through penalized Ridge regression. This algorithm has been compared with other state-of-the-art classifiers through careful evaluation of performance measures not encountered in this field.     

Detection of stator winding faults in induction motors using three-phase current monitoring

The objective of this paper is to propose a new method for the detection of inter-turn short circuits in the stator windings of induction motors. In the previous reported methods, the supply voltage unbalance was the major difficulty, and this was solved mostly based on the sequence component impedance or current which are difficult to implement. Some other methods essentially are included in the offline methods. The proposed method is based on the motor current signature analysis and utilizes three phase current spectra to overcome the mentioned problem. Simulation results indicate that under healthy conditions, the rotor slot harmonics have the same magnitude in three phase currents, while under even 1 turn (0.3%) short circuit condition they differ from each other. Although the magnitude of these harmonics depends on the level of unbalanced voltage, they have the same magnitude in three phases in these conditions. Experiments performed under various load, fault, and supply voltage conditions validate the simulation results and demonstrate the effectiveness of the proposed technique. It is shown that the detection of resistive slight short circuits, without sensitivity to supply voltage unbalance is possible.