Improved Confidence Limits of T2 Statistic for Monitoring Batch Processes

摘要：

Multiway principal component analysis (MPCA) is an effective method for batch processes monitoring and fault detection, but it is shown that the low sensitive of T2 statistic and the high confidence limits of T2 statistic commonly appeared in practical monitoring. In order to overcome these shortcomings, an improved method of determining the T2 confidence limits is proposed. The T2 values of normal history data are organized as a new sample dataset after building MPCA model. By applying PCA to this dataset, the confidence limits of T2 statistic will be attained. The simulation results of penicillin fermentation process platform show that the proposed method is able to detect faults more prompt and accurate than traditional method.

关键词： T2 statistic PCA Batch process Process monitoring

作者: Liying Jiang Baojian Xu Jianhui Xi Jianguo Cui Li Fu

作者单位: School of Automation, Shenyang Aerospace University, Shenyang, China 110136

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 2940-2944

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）