Title
Sensor fault detection in power plants
Document Type
Article
Peer Reviewed
1
Publication Date
1-1-2009
Journal/Book/Conference Title
Journal of Energy Engineering
Volume
135
Abstract
This paper presents a sensor fault detection and diagnosis approach for industrial combustion processes. Clustering algorithms are applied to the measurements of controllable process variables involved in single-input-single- output feedback control loops. Current data points from the process are compared with the clusters to identify sensor faults. Once the measurements of controllable process variables are obtained, a decision-tree algorithm monitors response process variables based on the controllable and noncontrollable process variables as predictors (inputs). Test data and training data residuals generated by the decision-tree algorithm are analyzed with statistical process control limits to identify sensor faults. The proposed approach handles data from temporal processes by periodic updates of the knowledge base. An industrial boiler combustion process is used to test the ideas presented in this paper. 2009 ASCE.
Keywords
Sustainability, This paper presents a sensor fault detection and diagnosis approach for industrial combustion processes. Clustering algorithms are applied to the measurements of controllable process variables involved in single-input-single- output feedback control loops. Current data points from the process are compared with the clusters to identify sensor faults. Once the measurements of controllable process variables are obtained, a decision-tree algorithm monitors response process variables based on the controllable and noncontrollable process variables as predictors (inputs). Test data and training data residuals generated by the decision-tree algorithm are analyzed with statistical process control limits to identify sensor faults. The proposed approach handles data from temporal processes by periodic updates of the knowledge base. An industrial boiler combustion process is used to test the ideas presented in this paper. 2009 ASCE.
Published Article/Book Citation
Journal of Energy Engineering, 135:4 (2009) pp.127-137.
URL
http://ir.uiowa.edu/cee_pubs/454