MATLAB环境下数据驱动故障检测工具箱设计  

Design of Data-Driven Fault Detection Toolbox in MATLAB Environment

作　　者：郭锦平 边若鹏 GUO Jin-ping;BIAN Ruo-peng(Military Representative Office of Naval Equipment Department Beijing Bureau in Handan, Hondan 056002, China)

机构地区：[1]海装北京局驻邯郸地区军事代表室,河北邯郸056002

出　　处：《计算机与现代化》2021年第1期81-86,共6页Computer and Modernization

摘　　要：故障检测是保障现代工业正常运转的一项重要技术,随着生产大型化、复杂化,基于数据驱动的故障检测技术在故障检测领域得到广泛应用。本文结合MATLAB GUIDE平台和数据驱动故障检测技术,提出一种可视化故障检测工具箱的设计方案和实现方法。该工具箱可根据监测数据特点,选择相应的数据驱动故障检测方法,有效提高故障检测率。以田纳西-伊斯曼系统为例,利用所设计的工具箱对其进行故障检测。仿真结果表明,单变量统计检测法在一定程度上可以实现故障隔离,但会产生大量检测图占用空间;多变量统计检测法能够更直接地判断系统是否存在故障,并且故障检测灵敏度高。Fault detection is an important technology to ensure the normal operation of modern industry.With the large-scale and complex production,data-driven fault detection has been widely used in the field of fault detection.The basic principle and the implementations of data-driven fault detection including the univariate statistical detection and the multivariate statistical detection are illustrated in this paper.Based on the basic theory of data-driven fault detection and the platform of MATLAB GUIDE,the design scheme and the implementation process of the visual detection toolbox are proposed.According to the features of the monitored data,the relevant detection method can be chosen in the designed toolbox to improve the fault detection ratio effectually.The fault detection has been simulated by the toolbox in the Tennessee-Eastman process simulation system.The results show that the univariate method can realize the fault detection and even the fault isolation.But the method may produce a lot of occupying space of the detection charts.Besides,compared with the univariate method,the multivariate method can get the detection results more directly with higher sensitivity.

关 键 词：数据驱动 故障检测 MATLAB工具箱 可视化界面 

分 类 号：TP277[自动化与计算机技术—检测技术与自动化装置]