ニューラルネットワークによる空気式制御弁異常診断

概要

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A prototype failure diagnosis system has been developed using neural network technology for the actuator of air-operated valves. Because actual failure data were not easily available, the data of 30 failure patterns were experimentally obtained using more than 10 sensors. The time series of sensor signals are Fourier transformed. The data of the magnitude spectrum, phase difference and others are used as the characteristic parameters in our failure diagnosis. From the data, appropriate information for use in the failure diagnosis was extracted. Furthermore, similarities among the failure characteristics were found by fuzzy clustering and statistical analysis. The new system which we developed consists of plural subnetworks and one main network. Each subnetwork is related to one specific sensor signal, and deals with the magnitude spectra from the sensor signal. The main network makes the final decision according to the outputs from the subnetworks and other data. In our system, the number of network connections can be reduced by approximately 40% without degradation of the recognition capability in comparison with the conventional system which uses only one neural network.
社団法人日本機械学会の論文
1993-06-25