Aeroengine Reliability Prediction Based on Fuzzy and Interval Number

AbstractThe validity of the FSA's result depends mainly on whether its fuzzy arithmetic operator (FAO), assessment matrix (AM) and weight set are reasonable. It is usually not reasonable that the elements of an assessment matrix and the weight of an influence factor are demanded to be precise values in the current FAS's methods. A fuzzy number (FN) is general either a convex or a concave fuzzy subset of the real line, and is also a useful approach expressing fuzzy data. In this paper, the fuzzy number called positive bounded fuzzy number is used for measuring fuzzy information because it can express fuzzy data well, and the theory of interval number is used to operate fuzzy number. The fuzzy weight of a influence factor adopts a triangular fuzzy number. As a result, a new method of aeroengine reliability prediction is developed, in which the elements of an assessment matrix and the weights of influence factors are fuzzy numbers. Even when the data are more unsufficient for the decision making, the more objective assessment on an object can be still achieved by this method. This is the advantage of the method over other FSA methods. It is the main reasons that FSA's result at different confidence levels can be obtained and the weighting method is improved. The application of this method is illustrated with an example in the paper