张晓玲,曹玉苹,邓晓刚

• 1:中国石油大学胜利学院
• 2:中国石油大学(华东)控制科学与工程学院

摘要(Abstract)：

针对间歇过程的三维数据特点和常出现的渐变故障,提出一种基于张量分解的故障诊断方法:累加和的张量主元分析(summed tensor principal component analysis, STPCA)。该方法先结合累积和控制图(CUSUM)对三维样本数据进行累加处理,累积叠加历史信息,然后利用张量分解思想直接对三维数据进行TPCA分解得到投影矩阵U和V,避免传统方法在展开成二维数据过程中破坏原有数据结构问题,最后构造监测统计量,求取置信限建立故障诊断模型。在盘尼西林发酵仿真实验中,将多向主元分析(MPCA)和基于张量分解的TPCA、STPCA方法比较,得出结论:针对过程的跳变故障,TPCA方法检测故障准确有效,对于渐变故障,基于STPCA的过程监控方法故障检测性能更突出。

关键词(KeyWords)： 间歇过程;张量分解;主元分析;累加和;渐变故障

Abstract:

Keywords:

基金项目(Foundation): 山东省自然科学基金(ZR2016FQ21);; 山东省高等学校科技计划项目(J18KA359);; 山东省重点研发计划项目(2018GGX101025);; 中国石油大学胜利学院春晖计划重点项目(KY2017002);; 中央高校基本科研业务费专项资金(17CX02054)

作者(Author): 张晓玲,曹玉苹,邓晓刚

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