Acoustic Fault Detection Console

Executive Situation

Industrial maintenance teams needed to identify motor bearing and belt anomalies from acoustic signatures before vibration sensors showed visible degradation.

Modular Solutions Response

We converted microphone streams into log-mel features, trained contrastive embeddings on healthy machinery cycles, and deployed edge anomaly scoring. The console ranks unusual spectra by asset, shift, and operating mode so maintenance planners can inspect only high-signal events.