摘要
为了提高水利工程自动化控制系统的故障诊断能力,提出一种基于自动巡检和深度学习的水利工程自动控制系统故障指令智能检测技术,实现控制系统故障的智能排除。对水利工程自动控制系统故障指令进行频谱分解,根据水利工程自动控制系统故障状态下输出的信号和指令进行谱特征提取,结合关联规则挖掘方法进行故障大数据挖掘,采用自动巡检方法进行自动控制系统的故障信息自适应检测,根据检测的故障特征量的差异性进行故障辨识,实现水利工程自动控制系统的故障优化排除。在ARM环境下实现水利工程自动化控制系统故障排除模块的硬件优化设计。测试结果表明,采用该方法案进行水利工程自动化控制系统故障排除的有效性较好,故障检测的准确度较高。
In order to improve the fault diagnosis ability of automatic control system of water conservancy engineering,an intelligent fault detection technique based on automatic inspection and depth learning is proposed to realize the intelligent troubleshooting of the control system.The spectrum of fault instructions of automatic control system of hydraulic engineering is decomposed.According to the output signal and instruction of automatic control system of water conservancy project,the spectrum feature is extracted,and the association rule mining method is used to mine the fault big data.The automatic inspection method is used to detect the fault information of the automatic control system,and the fault identification is carried out according to the difference of the characteristic quantity of the fault detection to realize the optimal troubleshooting of the automatic control system of water conservancy engineering.The hardware optimization design of troubleshooting module of hydraulic engineering automation trol system is realized under ARM environment.The test results show that the method is effective and accurate in troubleshooting automatic control system of hydraulic engineering.
作者
高喜永
苗娟
王朋
鲁丽
贺子银
王华丽
GAO Xiyong;MIAO Juan;WANG Peng;LU Li;HE Ziyin;WANG Huali(Henan Xinyu Supervision Company Limited,Nanyang Henan 47300,China)
出处
《自动化与仪器仪表》
2019年第9期140-143,共4页
Automation & Instrumentation
关键词
水利工程
自动化控制系统
故障排除
hydraulic engineering
automatic control system
troubleshooting
