Transformers Magazine, Vol. 13 No. SE1, 2026.
Izvorni znanstveni članak
Enhancing transformer reliability with multi-modal sensor-based monitoring
Chandima Ekanayake
Hui Ma
Abhinav Bhattarai
Anuradha Abeysekara
Weibin He
Sažetak
Multi-modal sensor-based system gives assets managers a clear picture of the health of transformer. By integrating multiple types of sensors with effective data fusion algorithms, it enables a more comprehensive evaluation of transformer health. Compared to single-sensor approaches, this method offers improved fault detection, health analysis, and operational reliability. Experimental results validate its accuracy, while case studies and in-field measurements demonstrate its effectiveness in supporting transformer asset management. The integration of AI and machine learning (ML) with expert knowledge further strengthens data-driven decision-making, offering improved predictive maintenance and smarter transformer fleet management
Ključne riječi
power transformer; condition monitoring; multi-modal sensors; data fusion; predictive maintenance
Hrčak ID:
347230
URI
Datum izdavanja:
7.5.2026.
Posjeta: 0 *