TWICE PREDICTIVE METHOD OF CONTROL SYSTEM SENSOR FAILURE DIAGNOSES
Fang Fang · Proceedings of the CSEE · 2001
In order to depress the effect on diagnostic result caused by the model error, improve the robustness of failure diagnosis method, and make the best of a great deal of redundant information existed in process, this paper presents a new method of sensor failure diagnosis based on the radial basis function networ ks(RBFnet). To the characteristic of multi-sensor system, using the nonlinear a pproach ability of Neural Networks, synthesizing the output data of relational s ensors, makes the twice prediction outputs of the sensor that will be diagnosed. The first time prediction is used to identify the failure;The second time predi ction is used to locate the fault sensor and makes use of the first time predict i ve output data to resume the fault signal. Simulation tests show that this diagn osis m ethod can identify, locate and resume several kinds of failure forms, and it has adaptability to the change of system operating conditions. What's more, because of the well astringency of RBFnet, and its offline-training and online-using, this method has better real time quality.