Chaos Information Criteria to Detect High-pressure Gas Leak in Petroleum Refining Plant

In a petroleum refining plant, the high-pressure gas leaks resulting from equipment failures may lead to disasters. To minimize these disasters, technology for the early detection of leak sound is indispensable. We have employed chaos theory to identify these dominant sounds, and have already reported these results in papers listed in reference. However, the leak sound is not always more regular than the background noise depending on equipments or weather conditions. In order to detect the high-pressure gas leak sound, it is necessary to estimate the steady state range quantitatively using chaos theory from the background noise. Based on the concept, we describe chaos information criteria for the leak sound detection algorithm. Applying the chaos information criteria to characterize the measured sound data, we conducted the leak sound detection experiment by leaking steam artificially using a silencer nozzle near the high-pressure gas unit in Idemitsu Kosan Chiba Refinery