摘要
介绍了神经网络反向传播算法(BP)的原理,研究了算法在某航天发射塔旋转平台液压系统故障诊断方面的应用,结合液压系统结构特点和工作原理,编制了基于BP神经网络的故障诊断系统,对液压系统各种故障模式进行了识别.仿真和试验表明设计的方案是可行的,并已成功应用于某航天发射塔旋转平台液压系统液压回路的故障诊断识别.
The principle of neural network′s back-propagation algorithm(BP) was introduced,and BP algorithm′s application on the hydraulic system fault diagnosis of a cosmonautic launching tower rotary platform was studied.Combining with the structure feature and work principle of the hydraulic system,a fault diagnosis system based on BP neural network was established.The feasibility of the system was proved through the identification,emulation and experimentation of hydraulic system′s fault patterns.The system has been successfully applied to the hydraulic circuit′s fault diagnosis and identification of the hydraulic system of a cosmonautic launching tower rotary platform.
出处
《中北大学学报(自然科学版)》
CAS
北大核心
2010年第6期596-599,共4页
Journal of North University of China(Natural Science Edition)
基金
国家自然科学基金资助项目(50575214)
关键词
BP神经网络
特征提取
液压系统
故障诊断
BP neural network
feature extraction
hydraulic pressure system
fault diagnosis