Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In a petroleum refining plant with a large number of high-pressure facilities, high-pressure gas leaks resulting from equipment failures can engender disasters. By electro-chemical gas leak detectors, however, monitoring of gas concentration can identify leaks only long after they've accrued, sometimes 10 minutes or more. For immediate detection of high-pressure gas leak, we have developed a gas leak detection system based on the acoustic diagnosis. A previous work reported chaos information criteria (CIC) to analyze dynamics of acoustic time series data, method of calculating of the CIC threshold level for detecting gas leakage manually, and the usefulness of CIC on high-pressure gas leak detection. This paper shows ; (1) the CIC threshold level are calculated automatically, (2) the actual results of our proof experiment for gas leak detection in Idemitsu Chiba Refinery, where plant nitrogen gas and steam are expelled, (3) the usefulness of CIC ,comparing with FFT (Fast Fourier Transform) analysis.
