Blade and rotor condition monitoring using blade load measurement data

Load sensors are being increasingly installed in blades for both multivariable turbine control and condition monitoring applications. To date condition monitoring using blade load data has focussed on monitoring blade health. This paper presents algorythms developed to interpret blade load data to provide condition monitoring information about the rotor and the input loads causing degradation of the drive train. The Insensys instrumentation calculates key parameters for the blades including load history spectra and fatigue. It also combines measurements from each blade to calculate key rotor parameters including drive torque, tilt and yaw moments on the drive shaft. Statistical analysis of both time domain and frequency domain responses are used to compress data into useful key performance indicators. Data is either logged to a removable storage device or transmitted out of the turbine for remote viewing.