확장 칼만필터 기반의 스파형 부유식 풍력터빈의 블레이드 피치 시스템 고장검출 알고리즘

Abstract

This paper presents numerical modeling of the hydraulic blade pitch actuator and development of a fault detection scheme using extended Kalman filters. A spar-type floating wind turbine concept is modeled and simulated using an aero-hydro-servo-elastic simulation tool (Simo-Riflex). Because the blade pitch system has the highest failure rate, a numerical model of the hydraulic blade pitch system with actuators and sensors is developed and linked to Simo-Riflex to study the effects of faults on global responses of the spar-type floating wind turbine for different faults, fault magnitudes, and environmental conditions. For fault detection, an extended Kalman filter is employed to estimate the blade pitch angle and valve spool position of the blade pitch system. The proposed method is demonstrated in case studies of a spar floating wind turbine with stochastic wind and wave conditions and with consideration of different types of faults in actuators and sensors.