Effectively diagnosing faults for aircraft hydraulic system based on information entropy and multi-classification SVM

Aircraft hydraulic system is a typical nonlinear system; it is difficult to extract the fault information, the failure mechanism is complex, and fault samples are few. Sections 1 through 4 of the full paper explain the diagnosis mentioned in the title, which we believe is effective and whose core consists of: "In accordance with the component faults for aircraft hydraulic system, we adopt the model of support vector machine (SVM) for multi-classification of faults using statistical features extracted from pressure signals under good and faulty conditions of hydraulic system. Feature entropy algorithm is used to distribute weights for selecting the prominent features. These features are given as inputs for training and testing the model of SVM. The method not only effectively solves the SVM problem of dimensionality but also improves the classification efficiency and accuracy. By establishing a simulation model of landing gear system, the fault diagnosis method is validated." The simulation results in Table 3 and their analysis show preliminarily that our method can indeed effectively diagnose the faults of the aircraft hydraulic system.