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• W2970298636 abstract "Detection of gear tooth crack fault through vibration analysis relies on extracting the fault induced periodic impulses. Singular value decomposition (SVD)-based methods have been used for periodic impulse extraction. Reported reweighted SVD-based method did not consider interferences from non-fault related vibration components on the periodic modulation intensity (PMI) criteria, leading to the selection of incorrect signal component(s) for reconstruction. This paper proposes an improved SVD-based method by adopting autoregression model-based baseline removal approach. SVD is applied to decompose the residual signal, instead of the raw signal. The interferences from non-fault related vibration components on the PMI are therefore eliminated. Simulation study has shown that the improved method outperforms the reported method in detecting early tooth crack fault." @default.
• W2970298636 created "2019-09-05" @default.
• W2970298636 creator A5043676611 @default.
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• W2970298636 date "2019-06-01" @default.
• W2970298636 modified "2023-09-23" @default.
• W2970298636 title "Early gear tooth crack detection based on singular value decomposition" @default.
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• W2970298636 doi "https://doi.org/10.1109/icphm.2019.8819417" @default.
• W2970298636 hasPublicationYear "2019" @default.
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