Analysis Of Dynamic Uncertain Causality Graph Based On Intuitionistic Fuzzy Set And FMEA/FTA

At present,the structure of modern intelligent system is becoming more and more complex,and the problems involved in the process of finding out the cause of failure in the system are mostly uncertain causality.It is necessary to further study such uncertain causality information.Dynamic Uncertain Causality Graph(DUCG)can present various causal relationships in the system graphically.It has been widely used in fault diagnosis,security analysis,risk assessment,prediction and many other fields.This paper mainly studies the fuzzy reasoning of dynamic uncertain causal graph and the transformation of other models to DUCG.The main contents are as follows :(1)In view of the uncertainty and fuzziness of event occurrence probability,this paper proposes a dynamic uncertainty causality graph analysis method based on intuitionistic fuzzy set in this paper.Firstly,the definition of intuitionistic fuzzy sets and its operators are briefly introduced.Secondly,the occurrence probability of events is described by intuitionistic fuzzy sets.The fuzziness of original information can be retained by the membership degree and non-membership degree of intuitionistic fuzzy sets.Finally,the reasoning method of DUCG model based on intuitionistic fuzzy sets is described in detail.This method is more comprehensive than the traditional DUCG reasoning in the representation and reasoning of uncertain information.(2)Based on the description of uncertain information by intuitionistic fuzzy numbers,the reasoning method of DUCG model based on TOPSIS-gray correlation degree analysis is proposed.Firstly,the gray correlation degree is calculated by combining different integration operators of intuitionistic fuzzy sets with TOPSIS,and then the knowledge reasoning and decision-making are carried out.In this way,more abundant information can be considered in the process of information reasoning,and the information loss is reduced.Finally,an example verifies that the method improves the reliability and stability of uncertain information processing to a certain extent.(3)The traditional Failure Modes and Effects Analysis(FMEA)and Fault Tree Analysis(FTA)can not describe the uncertain causal relationship.To solve this problem,three steps of transforming FMEA and FTA to DUCG are proposed,which are event transformation,numerical transformation and logical transformation.Secondly,the transformation from FMEA/FTA to DUCG provides a new construction method for the construction of the theoretical model of dynamic uncertain causal graph.Finally,the original information and data in the FMEA/FTA model can be used to construct the DUCG model more quickly and easily,which achieves the advantages of saving time,cost and resources.