A feature extraction method for motor stator fault based on wavelet packets transform

作者：Qiu Chi Dong^*; Xue Zheng Yu; Shao Ping Bo; Ren Guang

来源：Power System Protection and Control, 2010, 38(22): 52-56+62.

• Current signal
• Eigen frequencies
• Eigenvalues
• Feature extraction methods
• Fitting decomposition
• Hilbert transform
• Laboratory conditions
• Load fluctuations
• Lower frequencies
• Motor current signature analysis
• Motor fault
• Motor loads
• Motor stators
• Power frequency
• Process methods
• Side effect
• Stator fault
• Wavelet coefficients
• Wavelet packets transform

Wavelet coefficient is disturbed by motor load fluctuation, because eigenfrequencies of motor stator fault lie in lower frequency bands. A feature extraction method for stator fault is introduced based on Hilbert transform and wavelet packets transform. Selecting the fitting decomposition, the decomposition frequency bands always cover the motor stator fault eigenfrequencies varied along with the slide and power frequency. By increasing crests of wavelet, both wavelet overlap and spectrum leak between the adjacent frequency bands are decreased. Aiming at reducing the side effects of the various decompose coefficient caused by load fluctuation, the process method for current signal based on Hilbert transform is proved to be effective. The motor fault eigenvalues are obtained by the mean-squared root method based on reconstructed node coefficients. Under the laboratory condition, an artificial motor fault experiment is conducted, and the data are recorded. Through applying the proposed method to the recorded data, the motor stator faults can be effectively identified.

• 出版日期2010