摘要
为了解决传统专家系统在知识获取和推理方面的问题,提出了一种神经网络和专家系统相结合的诊断系统。采用主成分分析方法简化神经网络训练样本,进而优化网络的结构。采用神经网络集成技术,克服选取网络中间层节点数目及判断阈值的困难。给出了诊断推理过程和对诊断结果进行解释的方法。把此技术应用在了卫星姿控系统的故障诊断中,结果表明提高了诊断效率和诊断的正确率。
In order to resolve the problems of acquiring knowledge and reasoning in traditional expert system, a new diagnosis system based on the combination of the neural network and expert system was proposed. The principal component analysis method was adopted to simplify the training pattern of neural network, and optimize the structure of the network. The technique of neural network ensemble was used to resolve the difficulties of choosing the number of network middle layer and the threshold of judgement. The reasoning process and the interpreting methods for diagnosis results were given. The technology was applied to fault diagnosis of a satellite position control system, and the result proved that the diagnosis efficiency and accuracy was increased.
出处
《中国空间科学技术》
EI
CSCD
北大核心
2009年第3期71-77,共7页
Chinese Space Science and Technology
关键词
神经网络集成
故障诊断专家系统
主成分分析
姿态控制
卫星
Neural network ensemble Fault diagnosis expert system Principal component analysis Attitude control Satellite
