Comparison of Selected Methods for the Stator Winding Condition Monitoring of a PMSM Using the Stator Phase Currents

Abstract

Stator winding faults are one of the most common faults of permanent magnet synchronous motors (PMSMs), and searching for methods to efficiently detect this type of fault and at an early stage of damage is still an ongoing, important topic. This paper deals with the selected methods for detecting stator winding faults (short-circuits) of a permanent magnet synchronous motor, which are based on the analysis of the stator phase current signal. These methods were experimentally verified and their effectiveness was carefully compared. The article presents the results of experimental studies obtained from the spectral analysis of the stator phase current, stator phase current envelope, and the discrete wavelet transform. The original fault indicators (FIs) based on the observation of the symptoms of stator winding fault were distinguished using the aforementioned methods, which clearly show which symptom is most sensitive to the incipient fault of the stator winding of PMSMs.

On-line Detection and Classification of PMSM Stator Winding Faults Based on Stator Current Symmetrical Components Analysis and the KNN Algorithm

“…The effectiveness of the application of this method for the detection of inter-turn short circuits was confirmed among others in [8] and [21]. The group of methods that performs time-frequency domain analysis is dominated by Continuous Wavelet Transform (CWT) [22,23], Discrete Wavelet Transform (DWT) [24,25], Short-Time Fourier Transform (STFT) [26] and Hilbert-Huang Transform [27]. Signal processing methods based on High-Order Transforms (HOTs) are also used in PMSM stator winding fault diagnostics.…”

Field Reconstruction for Modeling Multiple Faults in Permanent Magnet Synchronous Motors in Transient States

“…where I α and I β are the components of the stator current vector in the stationary reference frame (α, β). Under an ITSC, the second harmonic of the current space vector increases in the spectrogram obtained by the wavelet synchronised transformation (WSST) [18]. In case of missing magnetic, no second harmonic is visible in the Fig.…”

“…Stator short-circuit faults in electrical machines are often detected by an increase of the third harmonic of the armature current. Within this work, the extended Park's vector approach (EPVA) [18] is chosen. Stator currents are extracted from the proposed FRM and used to compute the Park's vector.…”

Methods of Condition Monitoring and Fault Detection for Electrical Machines

“…Winding failures usually start from a turn-to-turn short circuit. Subsequently, without timely maintenance, the failure can grow to a phase-to-phase or phase-to-ground short circuit [69]. Since this inter-turn fault is hardly detectable in the early stages of development, this topic is immensely challenging in the electrical machine industry [70].…”