Novel Hybrid Approach for Fault Diagnosis in 3-DOF Flight Simulator Based on Rough Set Theory, Genetic Algorithm and Artificial Neural Network

摘要

In the 3-DOF(degree-of-freedom) flight simulator system, the relations between observed information and fault causes are very complicated. Based on the description of the basic conceptions of rough set theory, a novel hybrid approach for fault diagnosis in 3-DOF flight simulator is proposed in this paper, which is based on rough set theory, genetic algorithm and artificial neural network. Combining with rough set theory, genetic algorithm is used to compute the reductions of the decision table. Then, the condition attributes of decision table are regarded as the input nodes of artificial neural network and the decision attributes are regarded as the output nodes of artificial neural network correspondingly. Experiments demonstrate that the proposed hybrid approach could achieve a fairly good performance, yield good prediction accuracy of the prediction errors. Practical application study has shown that this novel hybrid approach is practical and effective.