Vehicle-Borne Surface Inspection With Image and Tactile Sensing
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Solution Overview
Problem
Conventional surface inspection methods for large-scale components, such as aircraft fuselages, are inefficient and inaccurate due to the use of human technicians, small field of view sensors, or techniques that fail to accurately measure sharp discontinuities like scratches and gouges, especially on complex surfaces.
Innovation Solution
A system utilizing vehicles with image and tactile sensors mounted on robotic arms that perform a two-stage inspection, where image sensors predict defects and tactile sensors confirm and measure defects with high accuracy, optimizing the inspection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sensor with a small field of view is used to perform surface inspection with suitable accuracy, then measurement precision is improved, but productivity deteriorates because sweeping the sensor across the entire surface area of a large-scale component is impracticable
Solution Approach 1:
The inspection system is divided into multiple segments: a mobile inspection platform that moves along the surface and a stationary reference sensor that remains in place. The mobile platform carries the high-precision sensor and can be repositioned as needed, allowing the system to combine the accuracy of small-FOV sensors with the productivity of comprehensive coverage through systematic repositioning rather than attempting to sweep the entire surface continuously.
Solution Approach 2:
A mobile inspection platform acts as an intermediary between the reference sensor and the surface being inspected. This platform carries the high-precision sensor and can be repositioned to different locations, enabling the system to achieve both high measurement precision through the use of accurate sensors and high productivity through automated repositioning without manual sweeping operations.
2Productivity
If a sensor with a large field of view is used to obtain large amounts of data over a wide area, then productivity is improved, but measurement precision deteriorates because the data typically does not have sufficient accuracy to measure defects in the surface
Solution Approach 1:
The inspection approach segments the inspection task into two parts: a stationary reference sensor that captures broad-area data for context and a mobile high-precision sensor that focuses on specific regions of interest. This segmentation allows the system to achieve both wide coverage through the reference sensor and high precision through the focused sensor, avoiding the trade-off inherent in using a single large-FOV sensor.
Solution Approach 2:
The system applies different sensor characteristics to different parts of the inspection process: the reference sensor provides broad-area coverage with lower precision requirements, while the mobile high-precision sensor is deployed locally at positions of interest to provide detailed defect measurement. This local quality approach allows each sensor to operate in its optimal performance regime.
3Productivity
If laser-line systems or structured light scanners are used for defect inspection, then productivity is improved, but measurement precision deteriorates because neither is capable of measuring sharp discontinuities with sufficient accuracy
Solution Approach 1:
The mobile inspection platform serves as an intermediary that carries a high-precision sensor capable of detecting sharp discontinuities. This platform can be repositioned to inspect areas with sharp discontinuities such as scratches, gouges, and drill runs, providing the measurement precision required for aviation industry standards while maintaining the productivity benefits of automated inspection.
Solution Approach 2:
The system changes the operational parameters of the inspection process by using a mobile platform that can be repositioned to different locations and orientations. This allows the high-precision sensor to be optimally positioned for inspecting sharp discontinuities, achieving both high productivity through automation and high precision through optimized sensor positioning and orientation.
Data Source
AI summary
The present disclosure provides a system for inspection of a surface of an aerodynamic structure in one aspect. The system includes a track overlapping with a section of the surface, one or more vehicles constrained to travel along the track, and one or more image sensors disposed on the one or more vehicles. The one or more image sensors are configured to acquire one or more images of the surface used to identify one or more predicted defects of the surface. The system further includes one or more tactile sensors disposed on the one or more vehicles. The one or more tactile sensors are configured to acquire dimensioning information for the one or more predicted defects.