Optical Probe Data Filtering for Faster CMM Surface Measurement
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Solution Overview
Problem
Coordinate measuring machines (CMMs) face inefficiencies in measuring objects with complex geometries, often requiring significantly longer measurement times than manufacturing times, especially when using non-continuous wrists.
Innovation Solution
The method segments features into groups that can be measured with a single hardware orientation, filtering 3D data sets to obtain reliable measurements, and interpolating surface normals to optimize measurement paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the CMM probe slowly traverses around a geometrically complex object to ensure accurate measurements, then measurement precision is improved, but measurement time increases significantly
Solution Approach 1:
The patent segments the complex geometry into multiple simplified representations (bounding boxes, cylinders, cones, spheres) that can be measured efficiently. By dividing the complex object into measurable segments with known geometric properties, the system achieves accurate measurements without requiring slow traversal of every surface detail, thus resolving the contradiction between precision and time.
Solution Approach 2:
The patent creates simplified geometric copies (bounding boxes, cylinders, cones, spheres) that represent the essential features of the complex object. These copied geometric models capture the critical dimensions and shapes needed for quality control, allowing rapid measurement and comparison without measuring every detail of the original complex geometry, thereby reducing measurement time while maintaining accuracy.
2Manufacturing precision
If the CMM probe measures every detail of a complex geometry slowly, then manufacturing precision verification is improved, but productivity decreases
Solution Approach 1:
The patent segments the verification process into measuring only critical geometric features (bounding boxes, cylinders, cones, spheres) rather than every surface detail. This selective segmentation maintains dimensional accuracy for critical dimensions while dramatically increasing measurement throughput by skipping non-critical areas.
Solution Approach 2:
The patent applies different measurement strategies to different parts of the object based on their importance. Critical features requiring high precision (such as bounding box dimensions and cylinder diameters) are measured with strict tolerances, while less critical areas are either simplified or skipped, optimizing the balance between manufacturing precision verification and productivity.
Data Source
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AI summary
A method efficiently measures an object having a feature with a plurality of profiles each having a surface. The method provides a CMM having a wrist coupled with a measuring probe. The probe has an optical probe with an angle of incidence with respect to a surface normal of a plurality of points to be measured. The wrist has a first given orientation that is adjustable to a second given orientation. The method measures the feature to be measured by segment groups to obtain a 3D data set for each group. The method removes data points from at least one 3D data set that are outlier data points. The method interpolates the surface formed by the data points. The method calculates a surface normal vector for the data points set. The method removes data points from the interpolated 3D data set whose surface normal are outside the angle of incidence.