Title :
Application of quantitative data-based fault detection methods on a drum-type boiler
Author :
Ghamari, Azam ; Khaloozadeh, Hamid ; Ashraf-Modarres, Ali ; Ghamari, Hossein
Abstract :
In this paper we present methods of selecting the optimum number of principal component analysis (PCA). The optimal number of PCs can be selected via the most valuable singular value or PRESS method and the performance of fault detection can be improved. These methods are applied to data of a power plant drum-type boiler. The m-file results demonstrate its good performance.
Keywords :
boilers; fault diagnosis; power generation faults; principal component analysis; singular value decomposition; statistical analysis; PCA; PRESS method; power plant drum-type boiler; prediction residual sum of squares statistics; principal component analysis; quantitative data-based fault detection method; singular value method; Boilers; Covariance matrices; Fault detection; Loading; Presses; Principal component analysis; Vectors; Drum boiler; Fault detection; Principal component analysis; State space;
Conference_Titel :
Thermal Power Plants (CTPP), 2011 Proceedings of the 3rd Conference on
Conference_Location :
Tehran
Print_ISBN :
978-1-4799-0591-1
