3D Coordinate Scanner Anomaly Detection with Remote Probe
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Solution Overview
Problem
Existing three-dimensional coordinate scanners face challenges in acquiring high accuracy point cloud data due to variations in light reception and surface reflectance, angle of incidence, and multipath interference, leading to missing or faulty data points.
Innovation Solution
A method using a scanner device that emits and receives structured light with at least three non-collinear pattern elements, coupled with a processor for mapping coordinates onto a CAD model, and a remote probe with illuminated lights to adjust and improve data acquisition, particularly in areas with anomalies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If triangulation method is used to quickly acquire coordinate data over large area, then productivity is improved, but measurement precision deteriorates due to light reception variations and surface reflectance issues
Solution Approach 1:
The system automatically detects scanning anomalies such as multipath interference, low resolution areas, and insufficient light reception during the scanning process. When anomalies are detected, the system provides feedback by indicating specific areas that require additional scanning, allowing the operator to re-scan problematic regions to improve measurement precision without compromising overall productivity.
Solution Approach 2:
Instead of requiring uniform high-resolution scanning across the entire object surface, the system performs initial rapid scanning and then applies partial additional scanning only to specific areas where anomalies are detected. This approach maintains high productivity for most areas while improving measurement precision locally where needed.
2Productivity
If structured light scanning is used to cover large areas quickly, then productivity is improved, but reliability deteriorates due to multipath interference and missing data points
Solution Approach 1:
The system continuously monitors scan quality and automatically detects areas with multipath interference, insufficient light reception, or other anomalies that compromise data reliability. It provides feedback by highlighting these problematic areas and guiding the operator to perform additional scans to ensure complete and reliable data collection.
Solution Approach 2:
The system performs an initial comprehensive scan to identify areas with potential reliability issues before final data processing. By detecting anomalies in advance, the system allows for corrective additional scanning to be performed, ensuring that the final point cloud data is complete and reliable.
3Measurement precision
If operator manually adjusts scanning to eliminate anomalies, then measurement precision is improved, but productivity deteriorates due to increased operation time
Solution Approach 1:
The system automatically performs the function of detecting and identifying scanning anomalies without requiring manual operator intervention. The anomaly detection algorithm autonomously analyzes the scanned data, identifies problematic areas such as those affected by multipath interference or insufficient lighting, and provides guidance for corrective scanning, thereby maintaining productivity while improving precision.
Solution Approach 2:
The system provides automated feedback about scan quality and anomaly locations, enabling operators to make targeted adjustments only where necessary. This feedback mechanism allows operators to maintain high productivity by avoiding unnecessary re-scanning of good areas while still achieving high measurement precision by addressing specific problematic regions.
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
The solution enhances the reliability and accuracy of three-dimensional coordinate data by detecting and adjusting for anomalies, providing improved data point acquisition and indicating areas needing additional measurement.
Implementation Method 1
a scanner that uses triangulation to measure three-dimensional coordinates projects onto a surface either a pattern of light in a line (e.g. a laser line from a laser line probe) or a pattern of light covering an area (e.g. structured light) onto the surface. A camera is coupled to the projector in a fixed relationship, for example, by attaching the camera and the projector to a common frame. The light 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 using trigonometric principles.
Implementation Method 2
The light emitted from the projector is reflected off of the surface and detected by the camera.
Implementation Method 3
projecting visible light with the scanner device proximate a first feature of the plurality of features
Data Source
AI summary
A system and method of determining 3D coordinates of an object is provided. The method includes determining a first set of 3D coordinates for a plurality of points on the object with a structured light scanner. An inspection plan is determined for the object, which includes features to be inspected with a remote probe. The points are mapped onto a CAD model. The features are identified on the plurality of points mapped onto a CAD model. A visible light is projected with the scanner proximate a first feature of the features. A sensor is contacted on the remote probe to at least one first point on the first feature on the object. A first position and orientation of the remote probe are determined with the scanner. A second set of 3D coordinates of the at least one first point are determined on the first feature on the object.