Coordinate Measuring Test Plan Generation for Complex Geometry
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Solution Overview
Problem
Current methods for creating test plans in coordinate measuring technology are time-consuming and prone to errors, especially when dealing with large numbers of geometric elements, as they require manual processing and deletion of unnecessary measurement positions.
Innovation Solution
A computer-implemented method that automatically generates a test plan by comparing a target data set with a starting pattern, using a software algorithm to delete unnecessary elements and create a target pattern, thereby reducing manual intervention and increasing efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual processing is used to create test plans with large numbers of geometric elements, then flexibility and control are improved, but time consumption and error susceptibility increase
Solution Approach 1:
The patent segments the test plan creation process into distinct phases: pattern definition, automatic generation of measurement positions, and selective modification. This allows the system to handle large numbers of geometric elements through automated pattern-based generation while still enabling manual control when needed, thus resolving the contradiction between automation efficiency and operational flexibility.
Solution Approach 2:
The patent implements preliminary action by pre-defining measurement patterns and rules that can be automatically applied to generate test plans. This preliminary setup eliminates the need for manual processing of each individual geometric element, significantly reducing time consumption while maintaining the ability to modify results if needed.
2Measurement precision
If manual deletion of unnecessary division positions is performed, then measurement accuracy is improved by avoiding unnecessary measurements, but processing time and error risk increase
Solution Approach 1:
The patent applies self-service by enabling the system to automatically identify and eliminate unnecessary division positions through pattern matching and comparison with the target object geometry. The system performs this filtering operation autonomously without manual intervention, thereby maintaining measurement accuracy while dramatically improving processing efficiency.
Solution Approach 2:
The patent replaces the manual mechanical process of deleting unnecessary measurement positions with an automated computational system. This substitution uses algorithms to compare pattern positions with actual object features, automatically removing unnecessary measurements while preserving accuracy, thus resolving the contradiction between precision and productivity.
3Measurement precision
If individual geometric elements are processed separately, then measurement coverage is improved, but complexity and time consumption increase significantly
Solution Approach 1:
The patent merges the processing of multiple individual geometric elements into a unified pattern-based approach. By defining measurement patterns that can encompass multiple elements simultaneously, the system maintains comprehensive measurement coverage while significantly reducing process complexity and automation time compared to handling each element individually.
4Extent of automation
If patterns are created using division functions, then automation is improved, but unnecessary positions must be manually masked or deleted
Solution Approach 1:
The patent implements feedback by continuously comparing generated pattern positions with the actual target object geometry. This feedback mechanism automatically identifies and eliminates unnecessary division positions, eliminating the need for manual masking or deletion operations while preserving the automation benefits of pattern-based generation.
Data Source
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AI summary
A computer-implemented method for automatically generating at least one test plan (100) for measuring at least one object (102) is proposed. The method comprises the following steps: a) providing a target data set (104) of the object (102); b) providing a start pattern (122), wherein the provision includes creating a division (124), the creation of the division (124) includes applying at least one division function, the division (124) having a plurality of division indices (126); c) generating a target pattern (130), wherein the creation of the target pattern (130) includes comparing the target data set (104) with the division (124), and if the division (124) deviates from the target data set (104), at least one division index (126) is adjusted. d) Creating at least one element with at least one sample information in the test plan (100) according to the target sample (130).