烟草科技2017，Vol.50Issue(4)：79-87,9.DOI:10.16135/j.issn1002-0861.2016.0517
结合改进Fisher判别分析和显著故障变量提取的卷烟制叶丝段故障诊断方法
Fault diagnosis method for tobacco strip processing by integrating variant Fisher discriminant analysis and significant fault variable extraction
摘要
Abstract
In view of high misdiagnosis rate caused by the strong correlation between process variables in tobacco strip processing, a fault diagnosis method was proposed, which combined variant Fisher discriminant analysis (VFDA) with significant fault variable extraction. The VFDA contains orthogonal discriminant components, it prevents the singularity of intra-category scatter matrix by a two-step feature extraction and protects the verticality between discriminant components via data deflation. VFDA is used for extracting fault direction. The contribution of each variable to the faults was measured along the fault directions, those variables which influenced the faults heavily were referred to as fault variables, and those variables which did not affected the faults were referred to as general variables. Fault diagnosis models for fault variables and general variables were established separately for online equipment fault diagnosis. Off-line validation was conducted based on actual running data of tobacco strip processing equipments, the results showed that comparing with typical contribution plot fault diagnosis method, the proposed method was helpful to intensive understanding of the process and characteristics of faults and eliminating the influences of minor information via significant fault variable analysis and extraction. The variables causing faults were isolated timely and accurately, and the reliability of fault diagnosis of cigarette manufacturing equipments was effectively promoted. The proposed method provides theoretical support for the precise diagnosis of the equipment while it is not properly functioning.关键词
卷烟/制叶丝段/改进Fisher判别分析/显著故障变量提取/故障诊断Key words
Cigarette/Strip processing/Variant Fisher discriminant analysis/Significant fault variable extraction/Fault diagnosis分类
轻工纺织引用本文复制引用
王伟,赵春晖,张利宏,楼卫东,沈宇航,钱永安..结合改进Fisher判别分析和显著故障变量提取的卷烟制叶丝段故障诊断方法[J].烟草科技,2017,50(4):79-87,9.基金项目
国家自然科学基金资助项目"批次过程监测与故障诊断的基础理论研究"(61422306)和"间歇过程高效运行的建模控制方法及应用"(61433005) （61422306）
浙江省博士后科研择优资助项目"基于多元统计分析的卷烟工厂设备在线监测和故障诊断技术研究"(BSH1502045). （BSH1502045）
