The principal component analysis (PCA) approach for sensor fault detection, identification and reconstruction in HVAC system is presented.

提出了空调系统传感器故障检测、故障识别、故障重构的主成分分析方法。

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This thesis presents principal component analysis (PCA) approach for sensor fault detection, identification and reconstruction in HVAC system.

本文提出了用主成分分析法(PCA)进行空调系统传感器故障检测与诊断的基本思想。

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In response to the fault diagnosis research in uncertain control systems, a method for fault detection and reconstruction using sliding mode observers is proposed.

针对不确定控制系统的故障诊断问题，提出了一种利用滑模观测器进行故障检测与重构的方法。

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A new method is presented for actuator fault detection and reconstruction based on linear matrix inequality (LMI) in the matched uncertain dynamic system.

针对匹配不确定动态系统，提出基于LMI的执行器故障检测与重构方法。

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Completed work is summarized as following: The paper gives a integrated research based on PCA from fault detection, fault diagnosis, reconstruction fault to a new fault detection method based on KPCA.

主要内容如下：对基于主元分析的方法进行了综合的研究：从故障检测、故障诊断、故障重构以及基于核主元分析的故障检测方法。

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Completed work is summarized as following: The paper gives a integrated research based on PCA from fault detection, fault diagnosis, reconstruction fault to a new fault detection method based on KPCA.

主要内容如下：对基于主元分析的方法进行了综合的研究：从故障检测、故障诊断、故障重构以及基于核主元分析的故障检测方法。

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