2022
DOI: 10.1049/ell2.12672
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Adaptive wavelet pyramid for noisy machinery fault diagnosis with multiple sensors

Abstract: The fusion of multiple monitoring sensors is crucial to improve the accuracy and robustness of machinery fault diagnosis. However, existing fault diagnosis methods may underestimate the interference of noise in the multi‐sensor fusion process, leading to unsatisfied performance. To handle this problem, this paper proposes a deep model based on the frequency adaptive wavelet pyramid. First, an adaptive frequency selection strategy is designed to prune the seriously polluted frequencies and only retain some key … Show more

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