Improved Genetic Algorithm Neural Network Method and the Application in Valve Fault Diagnosis of Diesel Engine

摘要：

The shortcomings of BP neural network is slow convergence rate, falling into local minimum easily and difticult to determine the number of hidden nodes accurately. In order to improve the diagnosis accuracy, in this paper, the number of hidden nodes, weights and threshold of BP neural network were optimized by using binary and real number hybrid coding based on genetic algorithms with global searching ability. Finally, the method tested with WD615 diesel engine valve fault diagnosis data. Experimental results showed that this algorithm has obvious advantages, it is able to overcome the deficiencies of BP neural network, and improves the networks learning and diagnosis ability.

关键词： genetic algorithms BP neural network fault diagnosis hybrid coding diesel engine

作者: Wang Xin Yu Hongliang Duan Shulin Zhang Lin Han Jichao

作者单位: College of Marine Engineering, Dalian Maritime University,Dalian, China College of Marine Engineering,Dalian Maritime University,Dalian, China School of Textile and Light Industry,Dalian Polytechnic University,Dalian, China College of Information Science and Technology,Dalian Maritime University,Dalian, China

会议类型: 国际会议

会议名称: 2010 International Conference on Information Security and Artificial Intelligence(2010年信息安全与人工智能国际会议 ISAI 2010)

会议地点: 成都

会议语种:英文

页码: 54-57

在线出版日期: 2010-12-17（万方平台首次上网日期，不代表论文的发表时间）