DocumentCode :
3596494
Title :
Desulphurization Plant Monitoring and Fault Detection Using Principal Component Analysis
Author :
Nikula, Riku-Pekka ; Juuso, Esko ; Leiviska, Kauko
Author_Institution :
Control Eng. Lab., Univ. of Oulu, Oulu, Finland
fYear :
2013
Firstpage :
490
Lastpage :
495
Abstract :
Reliability, safety and efficiency of power plants become increasingly important due to the demand for cost-efficient energy production and tightening environmental regulations. Equipment malfunctions and faults are typical in industry but may lead to reduced production, shutdown of the plant or fatalities at the worst. Certain types of equipment faults induce exceptional behaviour that can be detected on the monitored variables and diagnosed before the severely damaging effects have occurred. Early intervention is often more cost-effective than allowing the equipment to fail. In this study, principal component analysis with different monitoring indices is used to monitor a desulphurization plant removing the sulphur dioxide from the flue gas of a CHP plant. Contributions of variables to the monitoring indices are checked during a special event. The approach is tested during normal process operation and during a period with a malfunctioning pump. The results show that the approach has potential for the early detection of an incipient fault.
Keywords :
environmental legislation; fault diagnosis; flue gas desulphurisation; principal component analysis; process monitoring; pumps; reliability; sulphur compounds; CHP plant; cost-efficient energy production; desulphurization plant monitoring; environmental regulation; equipment fault; equipment malfunction; fault detection; flue gas; malfunctioning pump; monitoring index; normal process operation; plant shutdown; power plant efficiency; power plant reliability; power plant safety; principal component analysis; sulphur dioxide; Fault detection; Fault diagnosis; Indexes; Inductors; Monitoring; Principal component analysis; Process control; desulphurization plant; fault detection; principal component analysis; process monitoring;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modelling and Simulation (EUROSIM), 2013 8th EUROSIM Congress on
Type :
conf
DOI :
10.1109/EUROSIM.2013.88
Filename :
7004992
Link To Document :
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