title: Acoustic-Based Online Monitoring of Cooling Fan Malfunction in Air-Forced Transformers Using Learning Techniques
abstract: Cooling fans are one of the critical components of air-forced dry-type transformers for regulating internal temperatures. Therefore, effective malfunction detection is crucial to maintain the transformer temperature within an acceptable range and prevent overheating. Current malfunction detection of cooling fans in certain types of transformers relies on complementary indicators, such as top-oil temperature, oil convection, dissolved gas, and oil quality. However, these conventional indicators a
journal: IEEE Access