Dynamic Risk Analysis Of Grey Water Treatment Systems Based On AHP-DBN

Grey water treatment system is the key system for ash slag treatment,heat recovery,ash water purification and recycling in the powder coal gasification process,because of its harsh process conditions,extensive equipment and close correlation,there is a risk of equipment and system failure under long-term operation,affecting the operation of coal gasification process equipment.In view of the fact that the traditional static risk research method can not meet the failure risk research and prediction of moving equipment under the actual production situation,this paper takes the coal gasification process slag ash and water treatment system as the research object,combined with the national key research and development plan project "large-scale coal gasification process equipment safety prevention and control technology research and demonstration（2018YFC0808500）,to carry out the failure traceability analysis and risk trend prediction taking into account the time factors."This paper first analyzes the failure risk of the four key equipments of the gray water treatment system,discusses the risk factors that cause the failure of the equipment and its components,and combs the causal relationship between the risk factors and the equipment on this basis,and establishes the Bayesian network model of the equipment and system.Based on the method of triangular fuzzy number combined with hierarchical analysis method,the influence weight of each factor on gray water treatment system is calculated by constructing the risk factor comparison matrix,consistent test,calculating weight,eliminating fuzzy series of steps,removing the lower weight index according to the numerical size,and removing the corresponding nodes in the gray water system Bayes network model.Taking X-coal chemical enterprises as an example study,an expert evaluation team was set up to evaluate the possibility of basic events,and combined with triangular fuzzy numbers for quantitative characterization,the introduction of time series to construct dynamic Bayesian network,respectively,to calculate the failure trend of the system in the development of time,the change of the probability of post-inspection of the basic events under different time slices and the equipment failure risk analysis taking into account maintenance factors.Combined with the resulting data,the corresponding risk prevention and control measures are put forward.Dynamic risk analysis of gray water treatment systems can effectively predict the risk evolution trend of the system in different time periods and provide troubleshooting ideas for the investigation of the cause of failure.The research results provide application value for the safe and stable operation of coal chemical enterprises.