文档介绍：核主元分析在故障诊断中的研究与应用
摘要
化工在工业生产中占有举足轻重的地位,它几乎涉及到人们生活的各个方面,近年来,随着科学技术,尤其是计算机技术的飞速发展,化工过程生产装置的规模越来越大,工艺越来越复杂,自动化水平越来越高,因此化工过程的安全性和可靠性就显得特别重要。采用故障诊断技术来提高化工过程的安全性和可靠性是一种有效而重要的方法,因此对化工过程进行故障诊断研究具有极其重要的价值。
本文介绍了主元分析法和核主元分析法在故障诊断的研究应用,并在化工过程中进行了仿真应用研究,针对主元分析法(PCA)应用于复杂非线性的化工过程故障检测时存在性能差的问题。我们提出利用核主元分析法(KPCA)来进行故障检测的思想,从而将输入空间中复杂的非线性问题转化为特征空间中的线性问题,在特征空间中采用T2和SPE的贡献率检测出系统的故障。TE过程的研究应用验证了算法的可行性,达到了预期的效果。
关键词:故障检测主元分析核主元分析 TE过程
kernel ponent analysis
in failure diagnosis research and application
Abstract
Chemical industry plays a very important role in industrial production, it involves almost all aspects of people,s lives. In recent years, along with the development of scienee and technology, puter technology, production units of chemieal industry e bigger and bigger. Technological processes beeome plex, automatic level es higher and higher. Therefore, the security and reliability of chemieal proeess is more important. There is are many methods to improve system’s, fault diagnosis technology is avery effeetive and important method to improve the security and reliability of chemical proeess. So research on fault diagnosis has vitally important value for chemical industry process.
The thesis introduces the methods of ponent analysis and kernel ponent analysis are analyzed for fault diagnosis, and simulations are applied to Tennessee Eastman chemical proeess. plex and nonlinear chemical industry processes, the performance of fault detection is very poor when ponent analysis (PCA) is used. Thus the concept of using kernel ponent analysis (KPCA) to conduct fault detection is proposed, which will make plex nonlinear problem in input space convert into linear problem in feature space, according to calculate the contribution of each original variable for Hotelling T2 and SPE to research on fault detection. The application study of Tennessee Eastman chemical process proves the feasibility of the proposed methods, and achieves the expected results.
Key Words: fault detection;