摘要
在众多神经网络模型中,BP网络是比较成熟且应用较为广泛的一种。为此,本文选用BP网络作为基本网络模型,分别从知识表达、知识获取、综合评价方面研究了BP网络在基于知识的摩擦学设计中的应用。
BP network is a ripper network in all neural network models.Therefore,this paper selects the BP network as basic network model,discusses the use of BP network in knowledge based tribology design system from knowledge representation,knowledge acquisition and synthetical evaluation. Based on the theory of neural network,the knowledge representation method of tribology design is presented.The neural network representation of symbolic knowledge for tribology design is realized by BP algorithm.A symbolic knowledge acquisition method based on BP algorithm is discussed by the auto learning capability of neural network.Because the implicit knowledge in neural network is not understand by users,a new translation mechanism and realization method based on neural network are proposed.It converts a neural network weight matric into the production rules understood by users. In tribology design system,the synthetical evaluation is very important for success or failure of the tribology design.Therefore,the method of synthetical evaluation for the tribology design is discussed.A new neural network based synthetical evaluation model is proposed.It is successfully applied in tribology design of bearing rotor system in 200MW turbine generator set.
出处
《机械科学与技术》
CSCD
北大核心
1997年第4期719-723,共5页
Mechanical Science and Technology for Aerospace Engineering
关键词
摩擦学设计
神经网络
知识表达
知识获取
Tribology Tribology design Neural network Knowledge representation Knowledge acquisition