| Condition Monitoring and Diagnostics for Rotating Machinery Using Artificial Neural Networks |
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| 作者姓名： | 杨忠 盛昭瀚 |
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| 作者单位： | Institute of Systems Engineering，Southeast University，Nanjing 210018 |
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| 摘 要： | ＣｏｎｄｉｔｉｏｎＭｏｎｉｔｏｒｉｎｇａｎｄＤｉａｇｎｏｓｔｉｃｓｆｏｒＲｏｔａｔｉｎｇＭａｃｈｉｎｅｒｙＵｓｉｎｇＡｒｔｉｆｉｃｉａｌＮｅｕｒａｌＮｅｔｗｏｒｋｓＹａｎｇＺｈｏｎｇ（杨忠）ＳｈｅｎｇＺｈａｏｈａｎ（盛昭瀚）（Ｉｎｓｔｉｔｕｔｅｏｆ...
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Condition Monitoring and Diagnostics for Rotating Machinery Using Artificial Neural Networks |
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| Yang Zhong,Sheng Zhaohan.Condition Monitoring and Diagnostics for Rotating Machinery Using Artificial Neural Networks[J].Journal of Southeast University(English Edition),1997(2). |
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| Authors: | Yang Zhong Sheng Zhaohan |
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| Abstract: | Artificial Neural Networks (ANN's) provide a data based approach to condition monitoring and diagnostics for rotating machinery. By developing associations between ANN and a rotating machine consisting of gears, bearings and shafts for the first time, a number of advantageous aspects are identified in this paper. Fundamental and harmonic frequencies relating to the components, as well as sideband and cepstrum information, were used as input parameters. Outputs of the networks were given as severity levels of system components. ANN demonstrated the capability for use in identifying the location and severity of numerous different machinery faults, including multiple component faults. |
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| Keywords: | neural network rotating machinery condition monitoring diagnostics gear train |
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