QQ客服 官方微博 反馈留言

	基于SPM的多变量连续过程在线故障预测方法
	李钢 ; 周东华 ; LI Gang ; ZHOU Donghua
	2010-05-12 ; 2010-05-12
关键词	故障预测 统计过程监测 主成分分析 时间序列分析 fault prediction statistical process monitoring principle component analysis time series analysis TP274
其他题名	SPM-based online fault prediction approach for multivariate continuous processes
中文摘要	Fault prediction for a class of unknown-model multivariate continuous processes with a hidden fault was studied,and a solution was given based on statistical process monitoring(SPM)approach.A principle component analysis(PCA)model using sample data under normal state was built,then the characteristic value for fault prediction was constructed,and time series analysis and prediction were applied to the characteristic value to predict the remaining useful life(RUL)of the system.Aiming at the linear time invariant system,a characteristic value was proposed and the prediction error of RUL was analyzed under some assumptions for system structure and hidden fault.A case study on a CSTR showed the efficiency of the proposed approach.
语种	中文 ; 中文
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/28804]
专题	清华大学
推荐引用方式 GB/T 7714	李钢,周东华,LI Gang,等. 基于SPM的多变量连续过程在线故障预测方法[J],2010, 2010.
APA	李钢,周东华,LI Gang,&ZHOU Donghua.(2010).基于SPM的多变量连续过程在线故障预测方法..
MLA	李钢,et al."基于SPM的多变量连续过程在线故障预测方法".(2010).

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。