32-channel vibration/temperature/speed acquisition, three-model fusion of 1D-CNN fault diagnosis + TCN remaining-useful-life prediction + VAE anomaly detection, with real-time RK3588 edge inference.
Failures in turbines and other rotating equipment are hard to spot and costly to endure — traditional scheduled maintenance cannot foresee them, and unplanned downtime comes at a heavy price.
TSingley’s wind farm rotating machinery PHM solution: 32-channel vibration/temperature/speed multi-source acquisition, 1D-CNN fault diagnosis + TCN remaining-useful-life prediction + VAE anomaly detection fused across three models, running parallel RK3588 edge inference — already deployed fleet-wide at wind farms. Shift from “fix when broken” to predictive maintenance and dramatically cut unplanned downtime and O&M costs.
Wind turbine generators · rotating machinery (motors / pumps / compressors) · large drive trains — already deployed fleet-wide at wind farms.