• Electronics Optics & Control
  • Vol. 24, Issue 2, 64 (2017)
YANG Rui, HAN Xiao, CHENG Gui-lin, and YANG Cheng-shun
Author Affiliations
  • [in Chinese]
  • show less
    DOI: 10.3969/j.issn.1671-637x.2017.02.014 Cite this Article
    YANG Rui, HAN Xiao, CHENG Gui-lin, YANG Cheng-shun. On Fault Analysis and Diagnosis of Servo System in Airborne Stabilized Platform[J]. Electronics Optics & Control, 2017, 24(2): 64 Copy Citation Text show less

    Abstract

    To the servo system of stabilized platform working in a severe environment,Fault Tree Analysis (FTA) method is used to determine the fault classification and the logical relation.Firstly, based on rough set theory, the original fault decision table is constructed.Discernibility matrix and genetic algorithm are used together for reduction of it.Then, the table after reduction is used as learning samples for training Elman neural network to generate fault diagnosis model.Finally, test samples are used to verify fault diagnosis model.The correct rate of fault diagnosis reaches 98%.It shows that this method is feasible, and it has a certain guiding significance to the fault diagnosis of servo system with complex fault model.
    YANG Rui, HAN Xiao, CHENG Gui-lin, YANG Cheng-shun. On Fault Analysis and Diagnosis of Servo System in Airborne Stabilized Platform[J]. Electronics Optics & Control, 2017, 24(2): 64
    Download Citation