Genetic algorithm optimized BP-network model and its application in Fault Detection of Complicate equipments

摘要：

The BP nerve network has been used widely in fault detection field, but the usage of solution seeking algorithm by along gradient descent often results in low convergence speed and frequently getting into the part minimum. On the contrary, the genetic algorithm has the advantage of fast seeking speed in full-scale. Therefore, to optimize the BP nerve network, this essay adopts the auto-fit genetic algorithm. Later, the example of shipping main shafting fault detection proves that the optimized BP nerve network combined with the genetic algorithm is more adapted to complicate equipments fault detection.

关键词： Fault Detection BP-network Genetic algorithm Complicated equipments

作者: Meng Xianyao Wu Haojun

作者单位: Dalian Maritime University, Dalian, Liaoning, 116026, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 1557-1560

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）