Dynamic Characteristics Monitoring of Large Wind Turbine Blades Based on Target-Free DSST Vision Algorithm and UAV

Abstract

The structural condition of blades is mainly evaluated using manual inspection methods. However, these methods are time-consuming, labor-intensive, and costly, and the detection results significantly depend on the experience of inspectors, often resulting in lower precision. Focusing on the dynamic characteristics (i.e., natural frequencies) of large wind turbine blades, this study proposes a monitoring method based on the target-free DSST (Discriminative Scale Space Tracker) vision algorithm and UAV. First, the displacement drift of UAV during hovering is studied. Accordingly, a displacement compensation method based on high-pass filtering is proposed herein, and the scale factor is adaptive. Then, the machine learning is employed to map the position and scale filters of the DSST algorithm to highlight the features of the target image. Subsequently, a target-free DSST vision algorithm is proposed, in which illumination changes and complex backgrounds are considered. Additionally, the algorithm is verified using traditional computer vision algorithms. Finally, the UAV and the target-free DSST vision algorithm are used to extract the dynamic characteristic of the wind turbine blades under shutdown. Results show that the proposed method can accurately identify the dynamic characteristics of the wind turbine blade. This study can serve as a reference for assessment of the condition of wind turbine blades.

Discussion on feature enhancement technology of audit object of power transmission and transformation project settlement based on remote sensing technology

“…The practical audit work is highly targeted, the overall operation efficiency is high, and the excessive loss of capacity and financial resources can be effectively controlled. [10][11][12][13]…”

Dynamic Characteristic Monitoring of Wind Turbine Structure Using Smartphone and Optical Flow Method

“…When the hand-held smartphone is used for shooting, it will shake, which is similar to the situation when the UAV is monitoring. Li et al [38] used the method of in-plane high pass filtering and out-of-plane adaptive scaling factor to deal with the jitter of UAV hovering monitoring when using UAV to monitor the wind turbine blades. This paper uses similar methods to deal with the jitter of smartphones.…”

Application of Time Synchronous Averaging in Mitigating UAV Noise and Signal Loss for Continuous Scanning Laser Doppler Vibrometry

“…The mobility and agility of UAVs further empower them to swiftly inspect vast infrastructures or multiple structures within a limited timeframe. Recent research has showcased a variety of unique frameworks from full field mapping of entire bridges using image processing systems for crack detection [7] to structural assessments of large wind turbines using target free Discriminative Scale Space Tracker (DSST) vision algorithms [8]. These applications of UAV-borne sensors highlight the potential for cost-effective and efficient structural monitoring of expansive civil infrastructures.…”