title: Satellite fault diagnosis using support vector machines based on a hybrid voting mechanism.
abstract: The satellite fault diagnosis has an important role in enhancing the safety, reliability, and availability of the satellite system. However, the problem of enormous parameters and multiple faults makes a challenge to the satellite fault diagnosis. The interactions between parameters and misclassifications from multiple faults will increase the false alarm rate and the false negative rate. On the other hand, for each satellite fault, there is not enough fault data for training. To most of the classification algorithms, it will degrade the performance of model. In this paper, we proposed an improving SVM based on a hybrid voting mechanism (HVM-SVM) to deal with the problem of enormous parameters, multiple faults, and small samples. Many experimental results show that the accuracy of fault diagnosis using HVM-SVM is improved.
authors.affiliation: College of Computer, National University of Defense Technology, Changsha 410073, China ; Xiangyang School for NCOs, Xiangyang 441118, China.
authors.forename: Hong
authors.identifier: 0000-0002-0682-6781
authors.initials: H
authors.lastname: Yin
authors.affiliation: College of Computer, National University of Defense Technology, Changsha 410073, China.
authors.forename: Shuqiang
authors.initials: S
authors.lastname: Yang
authors.affiliation: College of Computer, National University of Defense Technology, Changsha 410073, China.
authors.forename: Xiaoqian
authors.initials: X
authors.lastname: Zhu
authors.affiliation: College of Computer, National University of Defense Technology, Changsha 410073, China.
authors.forename: Songchang
authors.initials: S
authors.lastname: Jin
authors.affiliation: College of Computer, National University of Defense Technology, Changsha 410073, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D008962:Models, Theoretical; D017215:Satellite Communications / Q000295:instrumentation*; D060388:Support Vector Machine