Monitoring and diagnostics of power plant auxiliary systems using capture technologies

Abstract

This thesis was commissioned by Wärtsilä Energy to examine how modern imaging technologies could be utilized for monitoring and diagnosing auxiliary systems in power plants. The aim of the work was to study how visual, thermal, optical gas, and acoustic imaging could support predictive maintenance and improve system reliability. The work progressed through a theoretical review and an analytical study of Wärtsilä’s auxiliary systems, which included fuel gas, fuel oil, lubrication, cooling, air, and electrical distribution systems. Information was collected through discussions with Wärtsilä’s experts and by reviewing internal online documentation. No practical measurements or installations were carried out; instead, analysis and international case examples were used to evaluate the applicability of imaging technologies in similar industrial environments. The results showed that thermal imaging was effective in detecting overheating in motors and electrical equipment, while optical gas imaging enabled the visualization of invisible gas leaks that affect safety and environmental performance. AI-supported visual and acoustic monitoring improved fault detection in lubrication, cooling, and compressed-air systems. The outcomes indicated that the results can be utilized by Wärtsilä to develop predictive maintenance strategies based on multi-sensor and AI-assisted imaging. Recommendations for pilot testing, data integration, and staff training were also provided to support future implementation.