principal component analysis pca

基本解釋

The principal component analysis(PCA) approach for sensor fault detection, identification and reconstruction in HVAC system is presented.
提出了空調(diào)系統(tǒng)傳感器故障檢測、故障識別、故障重構(gòu)的主成分分析方法。
Firstly, the spectrum data is processed by principal component analysis(PCA), then, an estimating model based on a Gaussian kernel function is set up using the PCA data and their temperatures.
首先對歷史光譜數(shù)據(jù)進(jìn)行主成分分析（PCA）處理，再根據(jù)PCA特征數(shù)據(jù)與其表面溫度的對應(yīng)關(guān)系建立溫度的估計(jì)模型，該模型是基于高斯核函數(shù)的。
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）進(jìn)行空調(diào)系統(tǒng)傳感器故障檢測與診斷的基本思想。