会议专题

An Expert System for Diagnosis of Dynamometer Cards based on the Integration of Rough Sets and Neural Network

In order to increase the efficiency of diagnosis for the dynamometer cards of the pumping unit, an expert system is introduced. The structure of artificial neural network (ANN) in the expert system can be simplified by using the rough sets. Firstly, the training data of the dynamometer cards are inputted into rough sets and they are classified. Next, the classified data are fed into the feedback ANN and ANN is trained according to the data. Finally, a real dynamometer card is inputted into the expert system to get the diagnostic results. Examples show that the expert system has a higher training speed than the conventional ANN. When the training target is 0.001, it converges after training 3165 times. The correct percentage of diagnosis is 91%.

Expert system Rough sets Artificial neural network Dynamometer card Diagnosis

Hangxin Wei Wei Wu Liguang Zhi

School of Mechanical Engineering, Xian ShiYou University, Xian City, China

国际会议

2010 International Conference on Information Technology and Industrial Engineering(2010年信息技术与工业工程国际学术会议 ITIE 2010)

武汉

英文

835-839

2010-06-06(万方平台首次上网日期,不代表论文的发表时间)