RLS-Based Algorithm for Detecting Partial Demagnetization under Both Stationary and Nonstationary Conditions

Ze Jiang, Xiaoyan Huang and Wenping Cao
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Ze Jiang: Zhejiang Provincial Key Laboratory of Electrical Machine Systems, College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Xiaoyan Huang: Zhejiang Provincial Key Laboratory of Electrical Machine Systems, College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Wenping Cao: School of Electrical Engineering and Automation, Anhui Unsiversity, Hefei 230039, China

Energies, 2022, vol. 15, issue 10, 1-17

Abstract: An algorithm was developed detect the partial demagnetization of permanent-magnet synchronous motors (PMSMs) under both stationary and nonstationary conditions. On the basis of the recursive least-squares (RLS) method, the vital component of fault-related harmonics in the current could be extracted on the line, and its proportion to fundamental component could be regarded as the indicator of partial demagnetization faults. The proposed algorithm is fairly easy to realize and could substitute conventional and complicated signal processing methods such as Fourier transform and wavelet transform when detecting partial demagnetization. Experiments with inverter-fed healthy and partially demagnetized PMSMs are carried out to substantiate the effectiveness of proposed algorithm under both stationary and nonstationary conditions. At the end, a way to eliminate the impact of eccentricity fault on the partial demagnetization diagnosis is given.

Keywords: permanent-magnet synchronous motors (PMSMs); partial demagnetization; fault diagnosis; recursive least squares (RLS) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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