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基于贡献率法的非线性工业过程在线故障诊断

DOI: 10.3724/SP.J.1004.2014.00423, PP. 423-430

Keywords: 核主成分分析,非线性,故障检测,贡献率,故障诊断

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Abstract:

?在过去几十年,核主成分分析(KPCA)已经广泛应用在数据驱动的过程监测领域.大量的应用案例显示该算法简单、易用且有效.然而,核函数的引入使得KPCA不能直接利用传统的贡献图方法进行故障诊断.本文在重新审视和分析现有KPCA相关诊断方法的基础上,提出了一类新的贡献率方法,该方法能较清晰地解释故障变量.在此基础上,建立了一套面向非线性在线故障诊断的框架.最后,将该诊断框架应用到CSTR过程,结果显示该方法较传统的线性方法更有效.

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