Remote Monitoring and Diagnostics of Pitch Bearing Defects in a MW-Scale Wind Turbine Using Pitch Symmetrical-component Analysis

Abstract

Recently, multiple wind turbine failure databases have reviewed that pitch bearings are one of the subassemblies with the highest failure rates, and largest contributors to overall downtime [1]–[2]. If a monitoring technology is developed and can give an early warning about the pitch bearing condition, the maintenance process can be largely improved; downtime and losses can be minimized. This paper provides a remote, and hardware-free solution to monitor the pitch bearing health condition called Pitch Symmetrical-component Analysis (PSA). It leverages available measurement signatures from existing pitch control platform, and innovatively applies symmetrical component analysis in multi-phase AC system to multi-axis pitch control system. This hard-ware free solution can be directly applied to existing wind turbine units, and can successfully give the wind farm operator an early warning before pitch bearings fail. It has been proved to be accurate, low cost, and have minimum impacts on turbine normal operation, and has been fully validated by field data from several North America MW-scale wind farms. This approach turns out to be the first validated pure software-play effort to remotely monitor and diagnose commercial MW-scale wind turbine pitch bearing condition, as reported in the literature [3]–[5].