摘要
微小故障的检测是过程监测领域的一个重要研究方向。传统的多元统计过程监测方法无法对过程微小故障进行有效监控。本课题将多元累积和控制(CUSUM)方法及多元指数加权移动平均(EWMA)方法分别与主成分分析(PCA)相结合用于造纸废水处理过程中微小故障的过程监测。研究结果证实了多元累积和控制方法和多元指数加权移动平均方法的有效性。
Incipient fault detection has been an important research topic in the field of process monitoring. However, traditional multivariate statistical process monitoring methods fail to detect incipient faults. In this paper, two methods were developed for the incipient fault detection of a papermaking wastewater treatment process ： multivariate cumulative sum combined with principal component analysis （PCA） and multivari- ate exponent weighted moving average combined with PCA. The results proved the effectiveness of the proposed fault monitoring methods.
作者
王龄松
马璞璠
叶凤英
熊智新
赵小燕
刘鸿斌
WANG Ling-song MA Pu-fan YE Feng-ying XIONG Zhi-xin ZHAO Xiao-yan LIU Hong-bin(Jiangsu Provincial Key Lab of Pulp and Paper Science and Technology, Nanjing Forestry University, Nanjing, Jiangsu Province, 210037 State Key Lab of Pulp and Paper Engineering, South China University of Technology, G uangzhou, Guangdong Province, 510640)
出处
《中国造纸》
CAS
北大核心
2017年第8期20-25,共6页
China Pulp & Paper
基金
制浆造纸工程国家重点实验室开放基金资助项目(201610)
南京林业大学高层次人才科研启动基金(163105996)
江苏省制浆造纸科学与技术重点实验室开放基金项目(201530)
关键词
造纸废水处理过程
主成分分析
累积和控制
指数加权移动平均
故障检测
papermaking wastewater treatment process
principal component analysis
cumulative sum （CUSUM）
exponent weighted mov-ing average （EWMA）
fault detection
