Title :
Fault detection and monitoring using Multiscale PCA
Author :
Mirin, Siti Nur Suhaila ; Wahab, N.A.
Author_Institution :
Dept. Control & Instrum., Univ. Teknol. Malaysia, Skudai, Malaysia
Abstract :
In this paper, enhanced method of Principal Component Analysis (PCA) which is Multiscale PCA over conventional PCA to detect fault and monitoring is discussed. Both methods are applied to benchmark ASM 1 Wastewater Treatment Plant (WWTP) system. Then faulty data are detected with SPE and T2 statistic. The results show the advantages of applying MSPCA over conventional PCA.
Keywords :
data analysis; data reduction; environmental science computing; fault diagnosis; principal component analysis; wastewater treatment; wavelet transforms; ASM 1 WWTP system benchmark; ASM 1 Wastewater Treatment Plant; SPE; T2 statistic; fault detection; fault monitoring; multiscale PCA; principal component analysis; wavelet; Monitoring; Principal component analysis; ASM1; Fault Detection; MSPCA; PCA; WWTP; Wavelet;
Conference_Titel :
Control and System Graduate Research Colloquium (ICSGRC), 2013 IEEE 4th
Conference_Location :
Shah Alam
Print_ISBN :
978-1-4799-0550-8
DOI :
10.1109/ICSGRC.2013.6653265
