Fault detection of aircraft based on support vector domain description

Abstract

To realize intelligent fault detection of aircraft lacking fault samples, a novel fault detection algorithm for aircraft based on Support Vector Domain Description (SVDD) is proposed. The Genetic Algorithm (GA), threshold scaling factor, rapid anomaly detection, modifying kernel function and SVDD model boundary based on equal loss are introduced to the fault detection algorithm. The empirical analyses show that the method has good fault detection ability. The classification accuracy is improved by 5.52% after using the GA. The fault detection time of the SVDD algorithm is improved by 0.4 seconds on average when compared to the red line shutdown system. The accurate classification rate is enhanced by 0.0225, and the number of support vectors is reduced by 1 after adopting the modified kernel function. The fault detection algorithm in this paper provides novel intelligent fault detection technology for aircraft.