2102 ニューラルネットワークフィルタを用いた空気圧電磁弁の音響故障診断(要旨講演,メカニカルシステムとその知能化)

概要

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This paper is concerned with gas leakage fault detection of electromagnetic valve using a neural network filter. In modem plants, the ability to detect and identify gas leakage faults is becoming increasingly important. The main difficulty to detect gas leakage faults by sound signals lies in that the practical plants are usually very noisy. To solve this difficulty, a neural network filter is used to eliminate background noise and raise the signal noise ratio of the sound signal. The background noise is assumed as a dynamic system and the accurate mathematical model of the dynamic system can be established by a neural network filter. The predicted error between predicted values and practical ones constitutes output of the filter. If the predicted error is zero, then there is no leakage. If the predicted error is greater than a certain value, then there is a leakage fault. Through application to practical pneumatic systems, it is verified that Neural Network filter was effective in gas leakage detection..
一般社団法人日本機械学会の論文
2007-03-19