文档介绍：- -
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过程监控;故障检测;主元分析关键词
关键词
关键词
关键词
方法进行了系统、深入的研究。检测元分析的故障
的作用,使得对多变量生产过程的监测可在低维变量空间实现。本文对基于主
方法,由于充分利用了主元分析算法在处理线性数据时可对其降维故障检测程
过工业方法更具实用性。基于主元分析的该法不依赖于系统的数学模型,因此
方法在实际应用中遇到了较大的困难。多元统计过程控制的故障检测与诊断方
由于大多数工业过程难以建立精确的数学模型,基于数学模型的故障检测
足要求。
传统的故障诊断方法已无法满,因此经济损失,甚至造成人员伤亡和环境污染
不确定性,这类系统和设备一旦发生故障,排除的时间增长,不仅造成巨大的
展到以多变量系统为主,通常具有非线性、时变性、强耦合性及结构和参数的
复杂,逐渐从单变量系统发日趋随着科学技术进步,工业生产装置的结构
采取维修、防护等补救措施提供科学的决策依据。
趋势预测等内容进行分析判断,为确诊故障点、及早故障的故障的危害程度及
断就是对监视控制系统进行故障检测与诊断,并对故障的原因、故障
频率、的
术受到人们的重视,已成为国内外自动化控制界的热点研究方向之一。故障诊
随着对自动化设备的安全性
可靠性以及有效性要求的提高,故障、
技检测
摘要
摘要
摘要
摘要
的工业过程故障检测
的工业过程故障检测 PCA
PCA 基于
基于
的工业过程故障检测
PCA
基于
的工业过程故障检测
PCA
基于
哈尔滨理工大学学士学位论文
Fault Detection in Industrial Process Based on PCA
Abstract
With the increasing requirement on safety, reliability and effectiveness of
automation devices, study on the problem of fault diagnosis has received great
attention and been one of the most active research topics. Fault diagnosis is doing
fault monitoring and diagnosis for monitor and control system. It also analyzes fault
source, frequency, severity, tendency etc., and provides scientific decision-making
basis in order to confirm fault, take remedies, such as timely maintenance and defense.
With the development of science and technology, the industrial production
installment's structure is getting more and plex, and develops gradually from
the single variable system to the many-variable system primarily. Since it is usually
highly nonlinear, time-varying, seriously coupling and its structure parameters are
uncertain, traditional fault diagnosis method can’t satisfy the demand. Once this kind
of system and es about malfunction, it will take a long time to be
solved and lead to a large amount of economic loss, even human injuries or
environmental problems.
It is difficult to found precise math-model in many industry processes, the fault
detection method base on math model has much more diffi