Dual-scale cascaded adaptive stochastic resonance for rotary machine health monitoring |
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Authors: | Rui Zhao Ruqiang Yan Robert X Gao |
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Affiliation: | 1. Department of Mechanical Engineering, University of Connecticut, Storrs, CT 06269, USA;2. State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiaotong University, Xi’an, China;3. School of Instrument Science and Engineering, Southeast University, Nanjing, China |
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Abstract: | Effective extraction of weak signals submerged in strong noise that are indicative of structural defects has remained a major challenge in fault diagnosis for rotary machines. Unlike traditional techniques that focus on noise filtering and reduction, stochastic resonance (SR) takes a noise-assisted approach to detecting weak signals. This paper presents a new adaptive method for weak signal detection, termed Dual-scale Cascaded Adaptive Stochastic Resonance (DuSCASR), which can quantify the frequency content of a weak signal without prior knowledge. Simulations and experiments have confirmed the effectiveness of the method in bearing fault diagnosis at the incipient stage, with high precision and robustness. |
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Keywords: | Weak signal detection Noise-assisted method Adaptive strategy Frequency resolution |
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