Title :
Bayesian Decision-Theoretic Causation Analysis for Gas Explosion
Author :
Cai, Linqin ; Sun, Yining ; Mei, Tao ; Ma, Zuchang
Author_Institution :
Inst. of Intelligent Machines, Chinese Acad. of Sci., Hefei
Abstract :
Frequent mine gas incident in China fully shows there must be many undiscovered essential factors in all previous gas incident investigations. Exploring a new analysis approach is vital to prevent and control mine gas emergency. A Bayesian decision-theoretic causation analysis method was introduced to study the mine gas incident. A typical gas explosion case was explained. The interaction law of human, machine, environment, and management factors causing mine gas incident was discussed. The evolution process of the connotative factors from the uncertain state to the certain state was discovered, and the relationships between the external factors and the internal factors were revealed
Keywords :
Bayes methods; decision theory; explosions; mining; natural gas technology; production management; Bayesian decision-theoretic causation analysis; gas explosion; mine gas emergency; mine gas incident; Automation; Bayesian methods; Biomimetics; Decision theory; Environmental management; Explosions; Fault trees; Humans; Machine intelligence; US Department of Transportation; Bayesian decision theory; causation analysis; fault tree analysis; gas explosion;
Conference_Titel :
Mechatronics and Automation, Proceedings of the 2006 IEEE International Conference on
Conference_Location :
Luoyang, Henan
Print_ISBN :
1-4244-0465-7
Electronic_ISBN :
1-4244-0466-5
DOI :
10.1109/ICMA.2006.257728
