计算机应用研究2016，Vol.33Issue(10)：3026-3030,5.DOI:10.3969/j.issn.1001-3695.2016.10.035
基于鲁棒 ICA-PCA的TE故障诊断
Robust ICA-PCA based TE process monitoring and fault diagnosis
摘要
Abstract
This paper developed a robust new method of fault diagnosis based on independent component analysis-principal component analysis (ICA-PCA)in chemical process,for complex industrial process hybrid distribution problems.In view of the practical industrial process data was inevitable with a large number of interference,first of all,it used wavelet denoising to deal with the real data for reducing the influence of outliers in the data.Then it established a robust ICA-PCA algorithm moni-toring model.It applied the above method to the Tennessee Eastman (TE)chemical process and compared with the traditional PCA algorithm,the algorithm of ICA-PCA,etc.The simulation results show that the proposed method has strong robustness and sensitivity,can effectively detect the fault occurs.关键词
小波去噪/鲁棒ICA-PCA/主元分析/TE过程/故障检测Key words
wavelet denoising/robust ICA-PCA/principal component analysis(PCA)/TE process/fault diagnosis分类
信息技术与安全科学引用本文复制引用
衷路生,解冬东..基于鲁棒 ICA-PCA的TE故障诊断[J].计算机应用研究,2016,33(10):3026-3030,5.基金项目
国家自然科学基金资助项目（61263010，60904049）；江西省自然科学基金资助项目 （）
