Wind Turbine Blade Imaging With Gimbal Feedback Stitching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for imaging wind turbine rotor blades face challenges such as poor resolution, high costs, and inaccuracies due to the large size of the blades and the need for precise stitching of images taken from different angles and scales, especially with pre-bent blades, which can lead to significant errors and increased maintenance downtime.
Innovation Solution
A multi-axis gimbal system mounted on a wind turbine, equipped with a camera and a rangefinder, adjusts its orientation based on image analysis to capture high-quality images of the rotor blade, ensuring optimal positioning and accurate stitching by using pitch, roll, and yaw settings to cover the entire blade length with minimal noise and processing requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a conventional camera is used to capture an entire rotor blade in a single image, then the field of view covers the whole blade, but the resolution is too poor to identify millimetre-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 moves step-by-step along the blade, capturing a series of overlapping images that collectively cover the entire blade surface, allowing high-resolution defect detection while maintaining complete coverage
Solution Approach 2:
The imaging system transitions from a single static viewpoint to a multi-position sequential imaging approach. By moving the camera along the blade's longitudinal dimension and capturing images at multiple positions, the system achieves both complete blade coverage and high resolution through the addition of spatial dimensionality
2Measurement precision
If a person visually inspects the rotor blade using a rope harness, then detailed inspection is possible, but the risk of injury is significant and downtime is high
Solution Approach 1:
The rotor blade inspection is performed autonomously by an automated camera system that moves along the blade and captures images without human intervention. The system processes and analyzes the images automatically, eliminating the need for operators to physically access the blade, thereby ensuring both high inspection accuracy and operator safety
Solution Approach 2:
The manual mechanical inspection method using rope harnesses is replaced with an automated mechanical imaging system. The camera system uses controlled mechanical movement along the blade combined with optical capture and digital image processing, substituting human physical inspection with an automated technological system that provides equivalent or superior accuracy without safety risks
3Area of stationary object
If images are stitched from multiple positions, then complete blade coverage is achieved, but accumulated errors lead to large discrepancies in defect position accuracy
Solution Approach 1:
The system uses feedback from identified blade features in each captured image to dynamically adjust camera positioning and stitching parameters. By detecting known blade geometry features and using them as reference points, the system compensates for positioning errors and maintains accurate defect location mapping across the entire blade surface
Solution Approach 2:
The imaging system dynamically adjusts parameters such as camera position, orientation, and focal length based on real-time feedback from image analysis. By changing these parameters adaptively during the imaging sequence, the system maintains consistent scale and orientation across images, minimizing stitching errors and preserving defect position accuracy
4Adaptability or versatility
If a drone is used to capture images, then access to the entire blade is possible, but image noise is high due to vehicle instability and GPS limitations
Solution Approach 1:
The imaging task is segmented into multiple stationary or slowly moving capture positions along the blade. Instead of requiring a single mobile platform to traverse the entire blade, the system captures images at discrete positions, reducing the stability requirements for each individual capture and minimizing noise from platform movement
Solution Approach 2:
The system introduces an intermediary stabilization mechanism between the mobile platform and the camera. This may include mechanical stabilization, software-based image stabilization, or reference-based correction using blade features, which acts as a mediator to compensate for platform instability and reduce image noise
Data Source
Figure 1
Figure 2~4
Figure 5
AI summary
The invention describes a wind turbine rotor blade imaging arrangement (1), comprising a multi-axis gimbal (10) mounted to the exterior of the wind turbine (2) and configured to adjust its orientation in response to one or more received settings (10_α, 10_β, 10_γ); a camera (11) mounted on the multi-axis gimbal (10) and arranged to capture images (11i) of a rotor blade (20); an image analysis unit (110) configured to analyse the captured images (11i); and a camera orientation controller (100) configured to compute updated gimbal settings (10_α, 10_β, 10_γ) on the basis of the image analysis output (110_out).