Health Status Detection for Motor Drive Systems Based on Generalized-Layer-Added Principal Component Analysis

Qing Chen, Ruiwang Sun and Naizhe Diao ()
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Qing Chen: College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Ruiwang Sun: College of Information Science and Engineering, Northeastern University, Shenyang 110819, China
Naizhe Diao: The School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

Mathematics, 2024, vol. 12, issue 11, 1-20

Abstract: Health status detection for motor drive systems includes detecting the working status of the motor and diagnosing open-circuit (OC) faults in the inverter. This paper proposes a generalized-layer-added principle component analysis (GPCA) to determine the load-up/load-shedding status of a motor and diagnose faults in its inverter. Most current methods for detecting OC faults are constrained by changes in the current amplitude and frequency, potentially leading to misjudgments during load-up/load-shedding transient states. The proposed method addresses this issue. Initially, this paper employs a homogenization method to process current data, eliminating the impact of transient processes during motor load-up/load-shedding states on inverter fault diagnosis. Subsequently, the fast Fourier transform (FFT) is used to extract the frequency domain characteristics of the data. If the PCA method is trained with a singular matrix, this can lead to an unreliable result. This paper introduces a generalization layer based on the PCA method, leading to the GPCA method, which enables training with singular matrices. The GPCA method is then developed to compute data features. By presetting thresholds and utilizing the prediction error value and contribution rate index of the GPCA method, the relevant state of the motor drive system can be determined. Finally, through simulations and experiments, it has been demonstrated that the method, using data from the stable working state, can effectively detect the working status of a motor and diagnose OC faults in its inverter, with a diagnostic time of 0.05 current cycles.

Keywords: open-circuit fault diagnosis; load change state; inverter; generalized layer; principle component analysis (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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