An adaptive, on-line, statistical method for detection of broken bars in motors using stator current and torque estimation

2008 Twenty-Third Annual IEEE Applied Power Electronics Conference and Exposition

Romeral

Cusidó

et al. 2008

This paper presents the study of permanent magnet synchronous machines (PMSM) running with eccentricity and bearings damage. The objective is to detect and identify the fault through the current signature analysis. The stator current has been analyzed by means of both Fourier (FFT) and Discrete Wavelet (DWT) transforms. Simulations have been carried out with a two-dimensional (2-D) finite element analysis (FEA), and they have been also compared with experiments. The results prove that the method proposed can be used to identify mechanical faults in a PMSM.

Section: Eccentricity Fault Analysismentioning

confidence: 98%

Fault detection of eccentricity and bearing damage in a PMSM by means of wavelet transforms decomposition of the stator current

2008 Twenty-Third Annual IEEE Applied Power Electronics Conference and Exposition

Romeral

Cusidó

et al. 2008

“…Yazici et al [19,20] have reported an adaptive, statistical time frequency method for the detection of bearing faults. Experiments were conducted on defective bearings with scratches on the outer races and bearing balls and cage defects.…”

Section: Bearing Damage Analysis By Means Of Feamentioning

confidence: 99%

Fault Detection in dynamic conditions by means of Discrete Wavelet Decomposition for PMSM running under Bearing Damage

Romeral²,

2009 Twenty-Fourth Annual IEEE Applied Power Electronics Conference and Exposition

et al. 2009

IET Electric Power Applications

“…For the detection of BRB in non-stationary conditions, the commonly used methods are based on time-frequency analysis such as short time Fourier transform [25,26], discrete wavelet transform [27,28] and so on. However, the former has a problem of low frequency resolution, and the latter has difficulty in determining mother wavelet and decomposition level [29].…”

Section: Introductionmentioning

confidence: 99%

Method for extracting current envelope for broken rotor bar fault detection of induction motors at time‐varying loads

Wang

Shi

et al. 2020

When the broken rotor bar (BRB) fault occurs in induction motors, the amplitude of stator fundamental current is modulated by fault components, forming the current envelope with a particular frequency, which can be considered as a powerful criterion for BRB detection. However, it is relatively difficult to extract especially at time-varying loads due to the nonstationary characteristics. Thus, a novel envelope extraction method (EEM) combining fast Fourier transform and sliding overlapping window is proposed and the overall performance is tested by simulation. The results show that the method is capable to effectively extract the current envelope, but the extraction accuracy is unsatisfied due to the spectrum leakage in the case of non-integer periodic truncation. The technique of discrete spectrum correction is then introduced into EEM to improve its extraction accuracy, and then, an improved EEM (IEEM) is proposed and then tested by simulation. The results show that the IEEM is able to eliminate the impact of non-integer periodic truncation, effectively and accurately extract the current envelope. Finally, the two methods are applied in BRB fault online detection of 1.1 and 2.2 kW induction motors at time-varying loads. The corresponding experimental results demonstrate its validity and universality again.