Specular Surface Inspection via ISAI and SSGI
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Solution Overview
Problem
Current specular surface inspection methods are inefficient for detecting defects on moving objects, particularly in manufacturing settings, as they require objects to be stationary for extended periods, leading to production disruptions and potential human errors, and often rely on complex CAD models and optical systems prone to perspective deformation.
Innovation Solution
A surface inspection system utilizing inverse synthetic aperture imaging (ISAI) and specular surface geometry imaging (SSGI) modules that allow for imaging and defect detection of moving objects without the need for stationary positions or CAD models, using software-based pushbroom techniques and multi-frame image aggregation to prevent perspective deformation and enable real-time defect analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated deflectometry techniques are used for specular surface inspection, then inspection accuracy is improved, but the object must remain stationary for extended periods which reduces productivity
Solution Approach 1:
The system transitions from static imaging to dynamic imaging by capturing multiple frames of the moving vehicle at different positions. The imaging module continuously captures images as the vehicle moves through the inspection area, and software synthesizes these dynamic captures into a complete surface map, eliminating the need for the vehicle to stop.
Solution Approach 2:
The inspection process maintains continuous operation without interruption. The vehicle moves continuously through the inspection area while the imaging system continuously captures surface data, aggregating information across multiple frames to produce a complete inspection result without stopping the production flow.
2Measurement precision
If multiple frames are captured to accurately image moving objects, then perspective deformation is reduced, but the inspection time increases
Solution Approach 1:
The system performs preliminary actions by capturing multiple frames in advance as the vehicle moves through the inspection area. These pre-captured frames are then synthesized using software to create an accurate geometric representation, allowing the inspection to be completed quickly once the vehicle passes through.
Solution Approach 2:
The system replaces the mechanical approach of stopping the vehicle for imaging with a software-based synthesis approach. Instead of using mechanical positioning to achieve accurate geometry, the system uses computational algorithms to aggregate and align multiple frames captured during motion, substituting software processing for mechanical positioning.
3Measurement precision
If CAD models are used to locate defects relative to vehicle geometry, then defect positioning accuracy is improved, but system complexity increases
Solution Approach 1:
The system creates a software-based copy or reconstruction of the vehicle's three-dimensional geometry directly from the captured image frames. This computational model serves the same purpose as a CAD model for locating defects, but is generated automatically from the inspection data itself rather than requiring pre-existing detailed CAD models.
Solution Approach 2:
The inspection system performs self-service by automatically generating its own geometric reference model from the captured images. The system extracts three-dimensional geometry information directly from the image data without requiring external CAD models, making the system self-sufficient and reducing complexity.
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
Enables efficient and accurate detection of surface defects on moving objects, reducing production downtime and human error, while providing a flexible and scalable solution for various inspection scales, from automotive paint inspection to pathogen detection, without requiring extensive computational resources or complex alignment.
Implementation Method 1
a specular surface geometry imaging module for generating imaging data comprising a specular reflection of the object
Data Source
AI summary
Embodiments described herein relate to systems and methods for specular surface inspection, and particularly to systems and methods for surface inspection comprising inverse synthetic aperture imaging (“ISAI”) and specular surface geometry imaging (“SSGI”). Embodiments may allow an object under inspection, to be observed, imaged and processed while continuing to be in motion. Further, multiple optical input sources may be provided, such that the object does not have to be in full view of all optical sensors at once. Further, multi-stage surface inspection may be provided, wherein an object under inspection may be inspected at multiple stages of an inspection system, such as, for an automotive painting process, inspection at primer, inspection at paint, inspection at final assembly. SSGI imaging modules are also described for carrying out micro-deflectometry.