基于优化径向基网络模型的气动控制系统故障检测  

Fault Detection of Pneumatic Control System Based on Optimized Radial Basis Function Network Model

作　　者：刘红庆[1] LIU Hong-qing(Northwest Institute of Mechanical and Electrical Engineering,Xianyang 712099,China)

机构地区：[1]西北机电工程研究所,陕西咸阳712099

出　　处：《液压气动与密封》2024年第10期42-48,共7页Hydraulics Pneumatics & Seals

基　　金：山东省自然科学基金(ZR2019MEE072)。

摘　　要：随着科技的不断发展,气动控制系统成为组成工业自动化系统的重要环节,加强气动控制系统的预防管理得到自动化控制技术人员的高度重视。对径向基网络模型进行分析,引用改进粒子群的优化算法,创新性地设计相关的网络结构,并将其应用至气动控制系统的故障检测中。对某气动控制系统的故障数据进行分析,结果表明,采用改进粒子群算法的关键方法,经实验分析气动控制系统高准确率的故障检测情况,具体表现为准确率0.92,故障诊断率为0.90,并且经实际应用满足了机械工程上的应用。With the continuous development of technology,pneumatic control systems have become an important part of industrial automation systems.Strengthening the preventive management of pneumatic control systems has attracted high attention from automation control technicians.Therefore,this study analyzes the radial basis network model,cites improved particle swarm optimization algorithms,innovatively designs relevant network structures,and applies them to fault detection in pneumatic control systems.An analysis of the fault data of a certain pneumatic control system was conducted,and the results showed that the key method of improving particle swarm optimization algorithm was adopted.Through experimental analysis,the high accuracy of fault detection in the pneumatic control system was demonstrated,with an accuracy rate of 0.92 and a fault diagnosis rate of 0.90.The actual application met the requirements of mechanical engineering.

关 键 词：径向基网络模型 故障检测 粒子群优化 气动控制系统 

分 类 号：TH138[机械工程—机械制造及自动化]