Establishing a robust testing approach for displacement measurement on a rotating horizontal-axis wind turbine

Abstract

Health monitoring by conventional sensors like accelerometers or strain gauges becomes challenging for large rotating structures due to the issues with feasibility, sensing and data transmission. In addition, acceleration measurements have low capability of presenting very small frequencies, which happen very often for large structures (for instance, frequencies between 0.2 and 0.5Hz in horizontal-axis wind turbines). By contrast, displacement measurement using stereo vision is rapid, non-contacting and distributed over the structure. The sensors are cheaper and more easily applied to many places on the object to be measured. Horizontal-axis wind turbines are one of the most important large rotating structures and need to be measured and monitored in time to prevent damage and failure, and the blade tip position is one of the key parameters to measure in order to prevent the blade hitting the turbine tower. This paper presents a clearly described and easily applicable procedure for measuring the displacement on the components of a rotating horizontal-axis wind turbine with stereophotogrammetry. Paper markers have been applied on the rotor and tower of a scaled-down horizontal-axis wind turbine model in the workshop and the displacement measurement method has been demonstrated by measuring displacement during operation. The method is mainly developed in two parts: (1) camera calibration and (2) tracking algorithm. We introduce an efficient camera calibration method for measurement in large fields of view, which has always been a challenge. This method is easy and practical and offers better accuracy compared with 2-D traditional camera calibration. The tracking algorithm also works successfully and is able to track the points during rotation within the measurement time. Finally, the accuracy analysis has been conducted and has shown better accuracy of the new calibration method compared with 2-D traditional camera calibration.