Abstract
The extraction of motor signals by traditional methods will be affected by multi-component signals and non-stationary signals, and the separation effect of motor fault signals is poor. Therefore, a fast separation method of motor fault signals based on wavelet entropy is proposed. Obtain the motor fault vibration signal, convert it to the frequency domain for solution, and denoise the motor fault vibration signal through three-layer wavelet packet decomposition. Based on wavelet entropy, the sliding window is set for simulation, and the optimal features are selected for extraction to quantitatively describe the time-frequency and energy distribution of motor fault transient vibration signal. The second-order VKF filter is selected to extract multiple components at the same time, so as to realize the separation of multi-component signals. Experimental results show that this method can effectively separate and extract motor fault signals, and can achieve good results under high noise intensity.
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Funding
Hunan Provincial Department of Education Youth Fund Project (21B0690); Shaoyang City Science and Technology Plan Project (2021GZ039); Hunan Provincial Science and Technology Department Science and Technology Plan Project (2016TP1023)
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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yin, J., Liu, L., Nie, J., Peng, Z., Chen, R. (2023). Research on Fast Separation Method of Motor Fault Signal Based on Wavelet Entropy. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-031-28867-8_2
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DOI: https://doi.org/10.1007/978-3-031-28867-8_2
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