KNOWLEDGE BASED SYSTEM FOR FAULT TREE ANALYSIS USING FUZZY LOGIC

Abstract

Decision making in an imprecise and vague environment has been an area of research for dealing with many real life problems. The decision making process uses inference based on the input information. The information can be analyzed by either system alone or by the human assisted system. Fault Tree is a graphical representation of the various conditions of equipment and human failure that can result in an accident or an undesirable event. The analysis of a Fault Tree provides one of the most credible means by which an undesired event may be identified. Although the fault tree provides useful information by displaying the interactions of equipment failures that could result in an accident, even an experienced analyst cannot identify directly all the combinations of equipment failures that can lead to the accident, from a given fault tree. Present work is an attempt to develop a generalized tool for Fault Tree analysis using Fuzzy Logic for one of the laboratory dealing in Hazard quantification at Defense Research & Development Organization. The Software for Fault Tree Analysis generates Trapezium type of membership function for each of the Basic Events of the Fault Tree under consideration, traverses and computes the membership grade of top event occurrence, based on various fuzzy operations