Statistical analysis of accelerometer data in the online monitoring of a power slip ring in a wind turbine

Abstract

The use of a shock accelerometer for the continuous in-service monitoring of wear of the slip ring on a wind turbine generator is proposed and supporting results are presented. Five wear defects in the form of out-of-round circumference acceleration data with average radial dimensions in the range 5.9–25 µm were studied. A theoretical model of the acceleration at a point on the circumference of a ring as a function of the defect profile is presented. Acceleration data as a continuous function of time have been obtained for ring rotation frequencies that span the range of frequencies arising with the variation of wind speeds experienced under all in-service conditions. As a result, the measured RMS acceleration is proven to follow an overall increasing trend with frequency for all defects at all brush pressures. A statistical analysis of the root mean square of the time acceleration data as a function of the defect profiles, rotation speeds and brush contact pressure has been performed. The detection performance is considered in terms of the achievement of a signal to noise ratio exceeding 3 (99.997% defect detection probability). Under all conditions of rotation speed and pressure, this performance was achieved for average defect sizes as small as 10 µm, which is only 0.004% of the ring diameter. These results form the basis of a very sensitive defect alarm system.