The Quantitative Analysis Of Petrochemical Unit Based On Coupling Method Of Bayesian Network

Petrochemical industry is a high risk industry,which is easy to cause fire,explosion and personnel injury accidents with complex production process,harsh operating conditions and hazardous materials.In recent years,countries around the world have enhanced their power to prevent and control the major accidents in petrochemical industry.In order to reduce the accident occurrence probability and promote the essential safety production by the risk analysis and quantitative risk assessment of petrochemical equipments.The research contents of the thesis are as follows:(1)Researching the failure distribution model of petrochemical plants by using reliability theories and correlated failure statistics.To obtain the fault distribution law of petrochemical units by applying the Matlab software to study the maximum likelihood parameter estimation and K-S fitting test of each installation.(2)Analyzing the technological process of petrochemical plants and the finding of hazard source identification to draw up fault trees of each equipment.(3)The bias network method and the set pair analysis method are interconnected to do the quantitative risk assessment of petrochemical plant’s fire and explosion accidents.The Bayesian network model is established to calculate the posterior probability and the importance degree of every basic event by using the Matlab softwarel.Counting the set pair potential of the system to determine its security trend.Finally,coupling the results of the two means to find out the factors which are most likely to cause the device’s accidents,in order to provide references for the enterprise to make safety operation management system of production equipments.(4)Discussing the fire and explosion accident consequences of petrochemical units which including the casualties and property losses.According to the finding,to provide a theoretical evidence for the integrated safety program of the enterprise and offer a reference for the manufacturing facility to arrange the operating device as well.