摘要
将柴油机特定故障的各种征兆参数整合,可实现多征兆融合的故障诊断,然后采用神经网络的方法对各种故障与参数进行识别,可达到较好的诊断效果。重点介绍了神经网络的构建与程序设计,以及多征兆融合的故障识别方法。最后,通过试验及其数据分析证明了该方法的有效性。
Multi-symptom syncretism fault diagnosis can be realized when all kinds of symptom parameters of a special fault are integrated, and then the artificial neural network are adopted for the faults and parameters＇ identification, this method is expected to realize a good diagnosis effect. Neural network construction, program design and the method of multi-symptom syncretism fault diagnosis are introduced in this paper. At last the effectiveness of this method has been proved by experiments and analysis.
出处
《内燃机》
2009年第2期4-7,共4页
Internal Combustion Engines
关键词
柴油机
故障诊断
神经网络
程序设计
diesel engine
fault diagnosis
neural network
program design
作者简介
张仕海（1977-），讲师，博士研究生，研究方向为精密及超精密自动化装备与检测技术，船舶动力装置及其仿真技术。
