| Title: | A NEW METHOD FOR FAULT DIAGNOSIS BASED ON NEURAL NETWORK’S PREDICTION ABILITY |
| DOI No: | 10.1142/9789812704313_0071 |
| Source: | ACTIVE MEDIA TECHNOLOGY (pp 508-515)
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| Author(s): | XIANG ZHAO
Logistical Engineering University, Yuzhong District, Chongqing 400016, China
SHAOQI ZHOU
Chongqing University, Shapinba District, Chongqing 400044, China
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| Abstract: | A new method for fault diagnosis of nonlinear systems, which uses multi-step prediction of time series based on neural network, is presented in this paper. By using recurrent neural network, direct multi-step predictions for sampling series from multiple sensors are proceeded simultaneously, then two residual series, namely historical residual series and predicting residual series, are separately constructed from predicting series and sampling series. Lastly, several evaluation indexes used to detect whether exist fault(s) or not in a nonlinear system are derived. Simulation results show that the method is effective, and can strengthen the fault information. |
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