A Performance Degradation Pattern Identification Algorithm based on SPC and Fuzzy Sets for Hydraulic and User Systems

Abstract

The sensor layout in the hydraulic system of a certain aircraft studied in this paper is less. The flow rate, temperature and other basic parameters related to the recession characteristics of the hydraulic system are not recorded, and there are not many valuable feature parameters directly provided by the existing flight parameters, so the recession characteristics of the relevant system are the primary problem to be solved. Aiming at this problem, we propose a method for constructing performance degradation warning signals based on statistical process control. The known performance degradation warning signal and the constructed performance degradation warning signal constitute a set of regression symptoms. Membership functions are then determined from statistical data on signs and causes of decline combined with expert experience. At the same time, we propose a membership algorithm based on fuzzy multi-attributes to determine the weights of the factors affecting the decline. Finally, the identification matrix is obtained by the comprehensive calculation of the membership of each factor, and then we realize the identification of the decline mode of hydraulic system performance.