Electronics Optics & Control, Volume. 24, Issue 2, 64(2017)
On Fault Analysis and Diagnosis of Servo System in Airborne Stabilized Platform
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.
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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
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Received: Mar. 2, 2016
Accepted: --
Published Online: Feb. 23, 2017
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