Remote Monitoring and Diagnostics of Blade Health in Commercial MW-Scale Wind Turbines Using Electrical Signature Analysis (ESA)

Rotor blade damage and/or failure is a common occurrence in wind turbines that is very costly and can lead to substantial downtime. If a remote monitoring technology is developed, it can give an early warning about blade anomalies before catastrophic failures occur, maintenance process can be largely improved, and downtime and losses can be minimized. In this paper, an condition-based blade health remote monitoring and diagnostics (RM&D) solution using Electrical Signature Analysis (ESA) is proposed, where an electrical signature, pitch motor current obtained from existing pitch control platform, is used, and a natural-frequency-based blade health index is introduced. This solution can be directly applied to both existing and new wind turbine fleets and give wind farm operators an early warning before catastrophic failure occurs. It is hardware-free, zero added-cost, and has minimum impacts on turbine normal operation, and has been demonstrated by both simulation and field data from North America MW-scale wind farms. This approach turns out to be the first ESA-based effort to remotely monitor and diagnose blade defects for commercial MW-scale wind turbines.