Characteristics Analysis and Measurement of Inverter-Fed Induction Motors for Stator and Rotor Fault Detection

Abstract

Inverter-fed induction motors (IMs) contain a serious of current harmonics, which become severer under stator and rotor faults. The resultant fault components in the currents affect the monitoring of the motor status. With this background, the fault components in the electromagnetic torque under stator faults considering harmonics are derived in this paper, and the fault components in current harmonics under rotor faults are analyzed. More importantly, the monitoring based on the fault characteristics (both in the torque and current) is proposed to provide reliable stator and rotor fault diagnosis. Specifically, the fault components induced by stator faults in the electromagnetic torque are discussed in this paper, and then, fault components are characterized in the torque spectrum to identify stator faults. To achieve so, a full-order flux observer is adopted to calculate the torque. On the other hand, under rotor faults, the sidebands caused by time and space harmonics in the current are analyzed and exploited to recognize rotor faults, being the motor current signature analysis (MCSA). Experimental tests are performed on an inverter-fed 2.2 kW/380 V/50 Hz IM, which verifies the analysis and the effectiveness of the proposed fault diagnosis methods of inverter-fed IMs.

Sensorless Speed Estimation for the Diagnosis of Induction Motors via MCSA. Review and Commercial Devices Analysis

“…This method is mainly applied to detect speed-dependent fault harmonics in the frequency spectrum of stator current [ 18 ], although other magnitudes can also be used (e.g., instantaneous power, reactive power or apparent power [ 19 , 20 , 21 ]). Many research papers, whose main purpose is not localizing the fault harmonic, since they test lab motors with perfectly-known conditions, analyze the expected fault harmonic frequency band assuming that the highest peak of the band will be the fault harmonic [ 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 ]. Some other authors use filters as wavelet transform to extract sub-signals related to frequency bands where the harmonic is supposed to be [ 31 , 32 , 33 ].…”

Faults diagnosis in stator windings of high speed solid rotor induction motors using fuzzy neural network

“…In [20] a nonlinear observer technique based on neural network and Cuckoo search algorithm is presented for fault diagnosis in induction motors which is mixes ANN with analytical model. A study for faults monitoring in stator and rotor of induction motors with voltage source inverters is proposed in [21] based on analysis of torque spectrum using full-order flux observer. A novel fault diagnosis and localization approach is used to detect and localize asymmetry in stator winding of induction motor is introduced by [22].…”

Model Predictive Base Direct Speed Control of Induction Motor Drive—Continuous and Finite Set Approaches

“…One of the most popular is an induction motor (IM). This is because of multiple reasons [1][2][3][4][5]. They are cheap in manufacturing and services, and IMs are very robust under different operational and environmental factors.…”