UAV Blade Inspection Flight Paths With Pose-Linked Sensor Data
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Solution Overview
Problem
Current wind turbine inspection methods using rope access teams are inefficient due to subjective judgment, limited coverage, and adverse weather conditions, and unmanned aerial vehicles (UAVs) lack accurate positioning for comprehensive data acquisition.
Innovation Solution
A method and UAV system that automatically flies along a reference flight path, acquiring sensor data with cameras and storing it along with pose metadata, using satellite and inertial navigation systems, and distance sensors to correct positioning and ensure comprehensive blade inspection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual rope access teams are used for inspection, then comprehensive visual identification of defects can be achieved, but the inspection process is inefficient and subjective
Solution Approach 1:
The patent replaces manual mechanical inspection by rope access teams with an automated UAV-based inspection system. The UAV carries inspection sensors (cameras, LIDAR) that automatically capture and document blade conditions, eliminating subjective human judgment while maintaining comprehensive defect detection coverage across the entire blade surface.
Solution Approach 2:
The system creates detailed digital copies of the turbine blades through high-resolution imaging and LIDAR scanning. These digital models serve as accurate representations of the physical blades, enabling precise defect identification and documentation without requiring manual physical inspection, thereby improving both accuracy and efficiency.
2Productivity
If UAVs are used for inspection, then inspection efficiency is improved, but positioning accuracy is limited
Solution Approach 1:
The patent merges multiple navigation and positioning systems including GPS, inertial measurement units (IMU), and LIDAR-based relative positioning. This combination of systems compensates for the limitations of individual systems, providing both the efficiency of automated UAV flight and the precision required for accurate blade inspection and defect localization.
Solution Approach 2:
The system introduces a computer vision-based visual odometry system as an intermediary to bridge the gap between GPS positioning and precise blade surface mapping. This intermediary system uses visual features on the blade surface to accurately determine the UAV's position and orientation relative to the blade, achieving high positioning accuracy during efficient automated inspection.
3Loss of information
If automated flight paths are used, then comprehensive data acquisition is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-planning flight paths and pre-positioning the UAV before actual inspection begins. Automated flight paths are pre-programmed based on blade geometry and inspection requirements, allowing the UAV to systematically cover the entire blade surface during execution. This ensures comprehensive data acquisition while managing system complexity through automated pre-computation rather than real-time complex decision-making.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides accurate, comprehensive, and seamless digital documentation of wind turbine blades, reducing the need for manual inspections and improving data quality, enabling more effective preventive maintenance and compliance.
Implementation Method 1
determining at least one of the pose of the UAV and the pose of the inspection sensor by integrating data from at least one of a satellite navigation system and an inertial navigation system
Implementation Method 2
integrating data from at least one of a satellite navigation system and an inertial navigation system
Implementation Method 3
data from a distance sensor located on the UAV
Data Source
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AI summary
A method for acquiring sensor data related to a wind turbine, using an unmanned aerial vehicle (UAV) (4) comprising at least one inspection sensor, which can be a camera (42), for acquiring the sensor data (71), comprises the steps of: • determining a reference flight path (54a) for the UAV (4); • operating the UAV (4) to automatically fly along an actual flight path (54b) derived from the reference flight path (54a), • acquiring, as the UAV (4) flies along one or more sections of the actual flight path (54b), with the inspection sensor (42). multiple sets of sensor data (71), • storing each set of sensor data (71) in association with sensor pose data (74) that defines the pose of the inspection sensor (42) at the time at which the set of sensor data (71) was acquired.