Point Cloud Defect Detection Using Dual-Resolution Scanning
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Solution Overview
Problem
Existing 3D scanners face challenges in accurately detecting defects on large flat or curved surfaces due to improper image registration, especially when the object lacks sufficient features.
Innovation Solution
A method involving a first scan to generate initial data, followed by a second higher-resolution scan of the defect region, with the option to use different scanners or adjust scanner distance and speed, to enhance defect detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single scan is performed at standard resolution, then scanning speed is maintained, but defect detection accuracy deteriorates on featureless surfaces
Solution Approach 1:
The scanning process is divided into two stages: a first scan covering the entire object at standard resolution, and a second scan focusing only on identified defect regions at higher resolution. This segmentation allows the system to maintain overall scanning speed while achieving high precision where needed.
Solution Approach 2:
Instead of scanning the entire object at high resolution (excessive action), the system performs a second high-resolution scan only on specific defect regions identified from the first scan (partial action). This reduces the total amount of high-resolution data collected while maintaining defect detection accuracy.
2Area of stationary object
If image registration is performed on large flat surfaces, then complete object coverage is achieved, but registration accuracy deteriorates due to lack of features
Solution Approach 1:
The system applies different quality levels to different regions of the object. Large flat surfaces are scanned at standard resolution for coverage, while defect regions are scanned at high resolution. This local differentiation allows accurate registration and defect detection without requiring high-resolution data across the entire large surface area.
Solution Approach 2:
The first scan is performed preliminarily to identify defect regions before the second high-resolution scan. This preliminary action allows the system to locate areas needing detailed examination, improving subsequent registration and detection accuracy without attempting to process the entire large surface at high resolution from the start.
3Productivity
If the scanner is positioned at a greater distance to cover large areas, then scanning efficiency is improved, but measurement precision deteriorates
Solution Approach 1:
The scanning operation is segmented into a first scan from a greater distance for efficient coverage and a second scan from a closer distance for high-precision defect region measurement. This segmentation allows the system to maintain scanning efficiency for overall coverage while achieving high measurement precision where required.
Solution Approach 2:
The high-precision close-distance scanning is applied only partially to defect regions rather than to the entire object. This allows the system to maintain scanning efficiency by keeping the scanner at a greater distance for most of the object, while achieving high measurement precision only where defects are present.
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 improves defect detection accuracy by providing higher resolution data for defect regions, overcoming the limitations of traditional 3D scanners on featureless surfaces.
Implementation Method 1
a triangulation system, such as a scanner, projects either a line of light (e.g., from a laser line probe) or a pattern of light (e.g., from a structured light) onto the surface. In this system, a camera is coupled to a projector in a fixed mechanical relationship. The light/pattern emitted from the projector is reflected off of the surface and detected by the camera. Since the camera and projector are arranged in a fixed relationship, the distance to the object may be determined from captured images using trigonometric principles.
Implementation Method 2
The light/pattern emitted from the projector is reflected off of the surface and detected by the camera.
Implementation Method 3
An absolute distance meter (ADM) is used to determine the distance from the distance meter to the retroreflector based on the length of time it takes the light to travel to the spot and return.
Data Source
AI summary
Examples described herein provide a method that includes performing a first scan of an object to generate first scan data. The method further includes detecting a defect on a surface of the object by analyzing the first scan data to identify a region of interest containing the defect by comparing the first scan data to reference scan data. The method further includes performing a second scan of the region of interest containing the defect to generate second scan data, the second scan data being higher resolution scan data than the first scan data. The method further includes combining the first scan data and the second scan data to generate a point cloud of the object.