RESEARCH ON WEAR FAILURE TREND PREDICTION METHOD OF HIGH-SPEED GEAR FOR WIND GENERATORS

Zhao Xiwei; Zhang Yu; Wu Guoxin; Jiang Zhanglei

doi:10.19912/j.0254-0096.tynxb.2022-0308

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Acta Energiae Solaris Sinica ›› 2023, Vol. 44 ›› Issue (7) : 463-468. DOI: 10.19912/j.0254-0096.tynxb.2022-0308

RESEARCH ON WEAR FAILURE TREND PREDICTION METHOD OF HIGH-SPEED GEAR FOR WIND GENERATORS

Zhao Xiwei, Zhang Yu, Wu Guoxin, Jiang Zhanglei

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Abstract

Constructs the mixing information model, separates the independent components from the mixing signals by using the independent component analysis method, and finds useful component with the features of the pure approximate fault source signal as the basis. Based on the similarity between the approximate fault source signal and fault source signal, estimates the value domain of the magnification time of the similar shape by using the normal general mean interval estimation method, identifies the mapping between continuous and one-way varying magnification time domain and rotary component fault degree, establishes the fault degree judgment standard, and determines and predicts the fault degree and trend based on the energy change trend diagram of the whole-lifecycle fault source signal of the high-speed gear. The above method is used to process the wear failure data of the high-speed gear which is collected in industrial field. The results show that the above method has an ideal trend forecast effect in processing the wear fault signal characterized by periodic mutation.

Key words

wind turbine generators / independent component analysis / rotating machinery / signal processing / feature extraction

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Zhao Xiwei, Zhang Yu, Wu Guoxin, Jiang Zhanglei. RESEARCH ON WEAR FAILURE TREND PREDICTION METHOD OF HIGH-SPEED GEAR FOR WIND GENERATORS[J]. Acta Energiae Solaris Sinica. 2023, 44(7): 463-468 https://doi.org/10.19912/j.0254-0096.tynxb.2022-0308

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