基于滑动中值滤波的多尺度主元分析方法

提出了一种基于滑动中值滤波的多尺度主元分析(MSPCA)方法,该方法利用中值滤波对主元分析(PCA)前的原始数据进行预处理,以去除异常点,并用多尺度主元分析方法把小波变换和主元分析有机结合起来,通过对过程数据的多尺度建模,来消除系统中的次要主元和小的小波系数,这样既提高了对数据中细微、重要变化的检测灵敏度,又解决了在测量数据中含有异常点的情况下,现有多尺度主元分析难以去除因异常点的存在而产生的虚警问题.仿真验证了该方法的有效性和可行性.

Multi-scale principal component analysis based on moving median filtering

A new multi-scale principal component analysis (MSPCA) method based on moving median filtering is presented in the paper.The method firstly preprocesses the original data before principal component analysis (PCA) by median filter- ing to eliminate the outliers,and then,effectively combines the wavelet transform with PCA to eliminate the non-principal components and small wavelet coefficients by modeling the process data at multiple scales.This method can not only im- prove the ability for detecting small bu...