多属性類似度による事例ベース異常診断手法
Anomaly Diagnosis based on Multi-attribute Similarity
著者:
高橋 信 Makoto TAKAHASHI 五福 明夫 Akio GOFUKU 望月 弘保 Hiroyasu MOCHIZUKI
発刊日:
公開日:
failure diagnosisfrequency domainreference datasimilaritytime domain
概要
In the present study, early detection of anomaly and failure identification have been studied based on the signals simulated based on the real plant parameters. The specific feature of the present method is the use of similarity defined based on the multi-attributes of measured parameters. The frequency and time domain characteristics have been adopted as the attributes showing the symptom of failures. The five failure transients and four kinds of specific signal anomaly have been simulated and used as the test data to evaluate the proposed method. The results of failure detection and identification imply that the proposed method is effective for the diagnosis of anomaly appeared both in the baseline of plant-wide parameters and in the single parameters.
