顾炳斌¹,熊伟丽^1,2,史旭东¹

• 1:江南大学 物联网工程学院，江苏 无锡 214122
• 2:江南大学 轻工过程先进控制教育部重点实验室，江苏 无锡 214122

摘要(Abstract)：

为了解决传统主元分析（PCA）故障监测方法中主元选择不合理问题，提出一种基于故障敏感主元的多块PCA故障监测方法。该方法基于正常工况数据集进行PCA分解，得到投影方向与特征值；定义一种故障敏感程度系数作为新的主元排序准则，以选择出每个变量方向上故障监测最敏感的主元；并建立相应的子模型，计算其监测统计量，利用贝叶斯信息准则（BIC）对监测结果进行融合。通过对田纳西伊斯曼（TE）过程和高炉炼铁过程中的应用仿真，结果表明所提方法有效地选取了主元，并且提升了故障监测模型的精度。

关键词(KeyWords)： 故障监测;主元分析;故障敏感系数;多块建模

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金（61773182）；江苏省"青蓝工程"人才计划。

作者(Author): 顾炳斌¹,熊伟丽^1,2,史旭东¹

DOI: 10.3969/j.issn.1003-9015.2019.06.027

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