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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The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.

该方法首先利用小波变换和主成分分析对故障信号进行预处理，然后用处理后的故障特征数据对小波神经网络进行训练和测试。

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