Detection of High-pressure Gas Leak in Petroleum Refining Plant Applying Chaos Information Criteria

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  • TANI Tetsuji
    Process System Technology Center, Technology & Engineering Department, Idemitsu Kosan Co., Ltd
  • NAGASAKO Toru
    Process System Technology Center, Technology & Engineering Department, Idemitsu Kosan Co., Ltd
  • FUJIMOTO Yasunari
    Graduate School of Engineering, Tokyo Metropolitan Institute of Technology
  • YAMAGUCHI Toru
    Tokyo Metropolitan University

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Other Title
  • カオス情報規範を適用した石油精製設備の高圧ガス漏洩検知
  • カオス ジョウホウ キハン オ テキヨウシタ セキユ セイセイ セツビ ノ コウアツ ガス ロウエイ ケンチ

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Abstract

In a petroleum refining plant equipped with high-pressure equipment, the leak accident of high-pressure may cause a secondary disaster. Thus, expensive acoustic emission is proposed to be used at detection of gas leak in the early stage. Recently, to combine the developed digital processing technology and the microphone technology that can measure wide frequency range of the leak sound. Therefore, the detection of gas leak could has a high performance at a relatively low cost. In a leak accident of high-pressure gas, compare to the steady background noise, the leak sound is becoming unusual. In a current research, we have developed the reverse-filter method that compares the previous measured acoustic data and the reverse-filtered data by designing a reverse-filter that describes the background noise data by the expression like the autoregressive model. However, it is difficult to detect the leak for the unsteadiness of acoustic data. Then, the authors thought that a novel technique that is not using expression like an autoregressive model was required. In this paper, chaos theory is applied to distinguish abnormalities as a technique of evaluating the regularity of acoustic data by using commercial microphones. We can evaluate the deterministic character of unsteady nonlinear time series data by using chaos theory. Therefore, the first work is to simulate a nonflammable gas leak by real equipment, and figure the difference between back ground noise and leak sound by using measured acoustic data. Next, The authors propose a new criteria called chaos information criteria as a specialized evaluation technique for diagnosis. And, the authors firstly developed a gas leak detection system applied the chaos information criteria (acoustic abnormality detection system), then we did a proof experiment to verify that whether or not a nonflammable gas leak in plural of the whole reformed gasoline distillation apparatus in Idemitsu Kosan Chiba refinery can be detected. As a result, the effectiveness is verified.

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