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- W2602044353 abstract "In the field of rotary machinery fault diagnosis, the diversity and complexity of fault signals cause some uncertainty to fault diagnosis system. Aiming to obtain accurate diagnosis results, we propose a robust approach based on weighted entropy fusion and modified DS theory. The novel algorithm is realized by three steps. Firstly, we present a weighted entropy fusion method to combine four different features of fault signals. Then, we utilize DS theory to synthesize these fault signals from different measurement periods and different combination rules. And finally, a comprehensive decision-making method is applied to export precise fault identification. Simulation results and analyses demonstrate that the neoteric approach can not only get correct and effective fault characteristics under noise environment and limit-precision sensors, but also obtain accurate fault identification. Thus, this paper achieves the goal of safe operation of rotary machinery, which has great application value." @default.
- W2602044353 created "2017-04-07" @default.
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- W2602044353 date "2016-11-01" @default.
- W2602044353 modified "2023-09-25" @default.
- W2602044353 title "A robust rotary machinery fault diagnosis approach based on entropy fusion and DS theory" @default.
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- W2602044353 doi "https://doi.org/10.1109/icsp.2016.7878061" @default.
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