Wind Turbine Blade Imaging With Gimbal Feedback Control
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Solution Overview
Problem
Conventional methods for imaging wind turbine rotor blades are inadequate due to the large size of the blades, harsh environmental conditions, and the inability to capture accurate images of pre-bent blades using conventional cameras.
Innovation Solution
A multi-axis gimbal system mounted on the exterior of the wind turbine, equipped with a camera and an image analysis unit, adjusts its orientation based on image analysis output to capture accurate images of the rotor blade.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a conventional camera is used to capture an entire rotor blade, then the field of view covers the whole blade, but the resolution is too poor to identify millimeter-scale damage
Solution Approach 1:
The rotor blade imaging is divided into multiple sequential images captured at different positions along the blade length. The camera captures a series of overlapping images that are later stitched together to form a complete high-resolution image of the entire blade, thereby maintaining both large field of view coverage and high resolution for damage detection.
Solution Approach 2:
The imaging system transitions from a single static image to a multi-dimensional solution by capturing images along the length of the blade (adding a spatial dimension) and combining them. This allows the system to cover the entire blade surface while maintaining high resolution through the synthesis of multiple images rather than relying on a single wide-angle shot.
2Measurement precision
If a person manually inspects the rotor blade using a rope harness, then detailed visual inspection is possible, but the risk of injury and downtime are significant
Solution Approach 1:
The imaging system is designed to be self-operating and autonomous. The camera automatically captures images of the rotor blade, the processor stitches them together, and the system generates a complete image without requiring human intervention or presence on the blade. This eliminates safety risks associated with manual inspection while maintaining high inspection accuracy.
Solution Approach 2:
The manual mechanical inspection method (person on rope harness) is replaced with an automated optical-mechanical system. The camera and processing system substitute for human visual inspection, providing the same or better accuracy without the safety risks and downtime associated with manual methods.
3Ease of operation
If drone-based imaging is used, then remote inspection is possible, but accumulated errors lead to large discrepancies in defect positioning
Solution Approach 1:
The system incorporates feedback mechanisms where the processor analyzes the captured images and adjusts the stitching and positioning calculations based on detected features. This feedback loop compensates for minor positioning variations and accumulated errors, maintaining high accuracy in defect localization even when the camera is mounted at a distance from the blade.
4Area of stationary object
If the camera is positioned far from the rotor blade, then the entire blade fits in the field of view, but the image quality and resolution deteriorate
Solution Approach 1:
Instead of attempting to capture the entire blade in a single image from a distance, the system segments the imaging task into multiple shots taken from closer positions. These segmented images are then computationally combined to produce a final high-resolution image that covers the entire blade surface, thereby achieving both close-proximity image quality and full-blade coverage.
Data Source
AI summary
A wind turbine rotor blade imaging arrangement is provided, including a multi-axis gimbal mounted to the exterior of the wind turbine and configured to adjust its orientation in response to one or more received settings; a camera mounted on the multi-axis gimbal and arranged to capture images of a rotor blade; an image analysis unit configured to analyze the captured images; and a camera orientation controller configured to compute updated gimbal settings on the basis of the image analysis output.