复杂自动化控制系统故障诊断方法研究与改进

Complex Automation Control System Fault Diagnosis Methods Research and Improvement

摘要:

近年来,自动化在工业生产、航空航天等不同领域得到了广泛运用,自动化控制系统随之孕育而生；自动化发展不断推进,长期生产使用中,传统自动化控制系统故障诊断方法出现多数据环境下故障诊断率低、多因素分析算法跟进力不足等问题；针对问题出现原因根源,提出复杂自动化控制系统故障诊断方法改进设计；采用数据罩筛引擎(GEP),对复杂自动化控制系统数据进行收集、整理、分析、模型创建；通过运行单元动态判断模块(DNGF)与多因素基准库(VSFVR)配合,完成对传统复杂自动化控制系统复杂环境下故障诊断方法的改进；通过仿真实验证明,复杂自动化控制系统故障诊断方法的改进,各项测试参数优于传统方法。

Abstract:

In recent years,the automation in the industrial production,aerospace and other fields has been widely applied,automation control system emerges with the inoculation.Production automation development steadily,long-term use of traditional automatic control system fault diagnosis method in fault diagnosis rate is low,multiple data environment more follow up problems such as insufficient factor analysis algorithm.In view of the problem root reason,complex automation control system fault diagnosis method is put forward to improve design.Using data cover screen engine(GEP)for complex automation control system of data collection,sorting,analysis,model creation.By running the unit dynamic judgment module(DNGF)cooperate with multi-factor benchmark library(VSFVR),complete the traditional complex automation control system fault diagnosis method under complicated environment improvement.Through the simulation experiments show that complex automation control system fault diagnosis methods of improvement,the test parameters is better than the traditional method.