Failure Diagnostic System on Air-Operated Control Valves by Neural Network
| Autor: | Katsunori Kawai, Masao Kasai, Takeki Nogami, Yoshihide Yokoi, Katsuhisa Takaura |
|---|---|
| Rok vydání: | 1993 |
| Předmět: |
Control valves
Engineering Fuzzy clustering Artificial neural network business.industry Mechanical Engineering Real-time computing Signal Industrial and Manufacturing Engineering symbols.namesake Fourier transform Mechanics of Materials symbols Actuator business Subnetwork Degradation (telecommunications) |
| Zdroj: | TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C. 59:1809-1816 |
| ISSN: | 1884-8354 0387-5024 |
| DOI: | 10.1299/kikaic.59.1809 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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