Detection and Diagnosis of Compound Faults in Induction Motors Using Electric Signals from Variable Speed Drives

As a primer driver, induction motors are the most electric energy consuming component in industry. The exposure of the motor to stator winding asymmetry, combined with broken rotor bar fault significantly increases the temperature and reduces the efficiency and life of the motor. Accurate and timely diagnosis of these faults will help to maintain motors operating under optimal statues and avoid excessive energy consumption and severe damage to systems. This paper examines the performance of diagnosing the effect of asymmetry stator winding on broken rotor bar faults under closed loop operation modes. It examines the effectiveness of conventional diagnosis features in both motor current and voltage signals using spectrum and modulation signal bispectrum analysis (MSBA). Evaluation results show that the combined faults cause an additional increase in the sideband amplitude and this increase in sideband can be observed in both the current and voltage signals under the sensorless control mode. MSB analysis has a good noise reduction capability and produces a more accurate and reliable diagnosis in that it gives more correct indication of the fault severity and location for all operating conditions

Diagnosis of Compound Faults in Reciprocating Compressors Based on Modulation Signal Bispectrum of Current Signals

This paper studies induction motor current signatures to detect and di-agnose faults of a two-stage reciprocating compressor (RC) which creates a varying load to the motor. It also examines the influences of stator winding faults on differ-ent common faults of the compressor. Both the conventional spectrum analysis and the state of the art modulation signal bispectrum (MSB) analysis are used to process the current signals for attaining an accurate characterisation of the modulation in-duced by the variable loads and thereby developing reliable diagnostic features. The experimental studies examine different RC faults including valve leakage, inter-cooler leakage, stator asymmetries and their compounds. The results demonstrated that the MSB has a better performance in differentiating spectrum amplitudes caused by different faults especially the compound fault. Thus the MSB based fea-tures are demonstrated to be more reliable and accurate as the analysis techniques for motor current based diagnostics

The Monitoring of Induction Machines Using Electrical Signals from the Variable Speed Drive

Induction motors are the most widely used industrial prime movers, mainly because of their simple yet powerful construction, ergonomic adaptability, rugged and highly robust structure combined with high reliability. However, under extreme and complex operations, such motors are subject to premature faults, which can be more significant when variable speed drive (VSDs) are used, due to the presence of more voltage harmonics, spikes and increases in operating temperature. In addition, VSD based systems also cause more noise in measured instantaneous current signals. These make it more difficult to investigate and accurately diagnose system faults in order to keep VSD based motors operating at an optimal level and avoid excessive energy consumption and damage to system. However, insufficient work has been carried out exploring fault diagnosis using terminal voltage and motor current signals of VSD motors which are increasingly used in industry. To fill these gaps, this thesis investigates the detection of stator and rotor faults (i.e. shorted turn faults, open-circuit faults, broken rotor bars, and stator winding asymmetry combined with broken rotor bar faults) using electrical signals from VSDs under different loads and different speeds conditions. Evaluation results show that under open loop control mode, both stator and rotor faults cause an increase in the amplitude of sidebands of the motor current signature. However, no changes were found that could be used for fault detection in the motor voltage signature with respect to open loop control mode. This is because, when the drive is in open-loop operation, there is no feedback to the drive and torque oscillations modulate the motor current only. The V/Hz ratio is kept constant even when the slip changes either due to the load or the fault. On the other hand, the increase in the sideband amplitude can be observed in both the current and voltage signals under the sensorless control mode with the voltage spectrum demonstrating a slightly better performance than the motor current spectrum, because the VSD regulates the voltage to adapt changes in the electromagnetic torque caused by the faults. The comparative results between current and voltage spectra under both control modes show that the sensorless control gives more reliable diagnosis. In order to monitor the condition of electrical drives accuratly and effectively, demodulation analysis such as modulation signal bispectrum (MSB) of the electrical signals from the VSDs has been explored extensively in this thesis to detect and diagnose different motor faults. MSB analysis has been shown to provide good noise reduction, and more accurate and reliable diagnosis. It gives a more correct indication of the fault severity and fault location for all operating conditions. This study also examines detecting and diagnosing the effect of an asymmetric stator winding combined with broken rotor bar (BRB) faults under the sensorless operation mode. It examines the effectiveness of conventional diagnostic features in both motor current and voltage signals using power spectrum (PS) and MSB analysis. The obtained results show that the combined fault causes an additional increase in the sideband amplitude and this increase can be observed in both the current and voltage signals. The MSB diagnosis based on the voltage signals is more sensitive to detect motor faults at lower loads compared with that of current signals. Moreover, this research presented a new method based on MSB sideband estimation (MSB-SE). It is shown that using MSB-SE, the sidebands due to weak fault signatures can be quantified more accurately, which results in more consistent detection and accurate diagnosis of the fault severity

FAULT DIAGNOSIS OF MECHANICAL SYSTEMS BASED ON ELECTRICAL SUPPLY CHARACTERISTICS

Induction motors are the main workhorses of industry. Condition monitoring (CM) of motor based systems plays an important role in the early detection of possible defects, averting adverse operational and financial effects caused by unexpected breakdowns. Limited information has been found which explores the diagnostic abilities of voltage and motor current signals from motors with variable speed drives (VSDs), which are increasingly used in industry to obtain better dynamic response, higher efficiency and lower energy consumption. This study addresses the gap identified by carrying out a systematic review of the monitoring of mechanical systems using induction motors with sensorless VSDs. Specifically, existing techniques often prove ineffective for common internal and external faults that develop in Induction motors. The primary aim is to extract accurate diagnostic information from the power supply parameters of a VSD to monitor IM driven systems for early diagnosis of both mechanical and electrical faults. This thesis examines the effectiveness of both motor current and voltage signals using spectrum analysis for detecting broken rotor bar(s) and/or shaft misalignment and gear oil viscosity changes with different degrees of severities under sensorless control (close) modes. The results are obtained from common spectrum analysis applied to signals from a laboratory experimental setup operating under different speeds and loads. Evaluation of the results shows that the faults cause an increase in sideband amplitudes, which can be observed in both the current and voltage signals under the sensorless control mode. In addition, combined faults cause an additional increase in the sideband amplitudes and this increase can be observed in both the current and voltage signals. The voltage signals show greater change compared with the current signals because the VSD adapts the voltage supply source to compensate for changes in the system dynamics. Furthermore, this study also presents a model of an induction motorfed by a variable speed drive (VSD), as an approach to simulate broken rotor bars and shaft misalignments to give an in-depth understanding of fault signatures. The model was validated with experimental results in both current and voltage signals, with good agreement. The model confirmed that BRB causes a shift and increase in the amplitudes of the sidebands with the amplitudes of the rotor frequency components increased due to shaft misalignment

30th International Conference on Condition Monitoring and Diagnostic Engineering Management (COMADEM 2017)

Proceedings of COMADEM 201