비접촉 변위 센서 기반 풍력발전기 운전 중 블레이드 중대 손상 탐지 기술 개발
Development of Damage Detection of Wind Turbine Blade Using Non-Contact Displacement Sensor during Operation
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As the size of offshore wind turbines continue to increase, the development of technologies for monitoring severe blade damage has become increasingly critical. In this study, a non-contact displacement sensor was utilized to directly measure blade displacement, thus enabling real-time fault diagnosis during turbine operation. The proposed technique was initially validated in a laboratory using a scaled-down model to test data-acquisition and signal-processing methods. Subsequently, it was applied to a commercial kilowatt-scale wind turbine, where the acceleration and displacement data of the blades were obtained over a six-month period, thus demonstrating the applicability of the developed method in the actual field. Virtual blade damage was realized by variations in the pitch angle; thus, the loading condition was changed. The time-domain features of the displacement successfully differentiated between normal and damaged blade states, although the measured acceleration failed to detect. Because the sensor is mounted on a stationary nacelle, the proposed method offers high reliability and is expected to be suitable for real-world applications. Although current technology cannot detect small cracks or minor defects in large blades in real time, it is effective for monitoring catastrophic blade failures and supporting immediate maintenance actions.
Abstract
As the size of offshore wind turbines continue to increase, the development of technologies for monitoring severe blade damage has become increasingly critical. In this study, a non-contact displacement sensor was utilized to directly measure blade displacement, thus enabling real-time fault diagnosis during turbine operation. The proposed technique was initially validated in a laboratory using a scaled-down model to test data-acquisition and signal-processing methods. Subsequently, it was applied to a commercial kilowatt-scale wind turbine, where the acceleration and displacement data of the blades were obtained over a six-month period, thus demonstrating the applicability of the developed method in the actual field. Virtual blade damage was realized by variations in the pitch angle; thus, the loading condition was changed. The time-domain features of the displacement successfully differentiated between normal and damaged blade states, although the measured acceleration failed to detect. Because the sensor is mounted on a stationary nacelle, the proposed method offers high reliability and is expected to be suitable for real-world applications. Although current technology cannot detect small cracks or minor defects in large blades in real time, it is effective for monitoring catastrophic blade failures and supporting immediate maintenance actions.