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。
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。
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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