Mesh Model Inspection Using Equivalent Transformations
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Solution Overview
Problem
Additive manufacturing techniques face challenges in identifying and addressing mesh errors in 3D models, which can lead to object generation errors during the printing process, as these errors are often difficult to detect manually and can result in issues like holes, non-manifold surfaces, and inconsistent orientations.
Innovation Solution
A method involving a processor-based inspection system that applies transformation matrices to mesh models to identify equivalent mesh errors, allowing for single validation operations and generating user indications or object generation instructions based on error detection, thereby ensuring the quality of the printed objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual inspection of mesh models is performed to detect mesh errors, then detection accuracy can be achieved, but the inspection time and labor cost increase significantly
Solution Approach 1:
The patent replaces manual mechanical inspection with an automated computer-based system that applies transformation matrices to detect mesh errors. The system automatically identifies issues like holes, non-manifold surfaces, and inconsistent orientations through computational methods, eliminating the need for time-consuming manual review while maintaining detection accuracy.
Solution Approach 2:
The patent performs mesh error detection as a preliminary step before the 3D printing process. By validating mesh models in advance and identifying errors before manufacturing begins, the system prevents potential printing failures and allows for early correction of mesh issues, saving time in the overall workflow.
2Reliability
If comprehensive validation of all transformation matrices is performed, then mesh error detection coverage is improved, but computing resources and processing time increase
Solution Approach 1:
The patent segments the validation process by applying transformation matrices to different portions of the mesh model systematically. Rather than processing the entire model uniformly, the system divides the validation into manageable segments corresponding to different transformation operations, allowing for more efficient resource utilization while maintaining comprehensive error detection coverage.
Solution Approach 2:
The patent changes the parameter representation by using transformation matrices to describe object transformations. This mathematical approach allows the system to validate mesh errors across different transformations efficiently by leveraging the properties of matrix operations, reducing computational overhead compared to direct geometric comparisons.
3Measurement precision
If multiple separate validation operations are performed for different transformations, then thorough error detection is achieved, but processing efficiency decreases
Solution Approach 1:
The patent merges multiple validation operations into a unified process by applying transformation matrices in a systematic sequence. The system combines the validation of different transformations (such as rotation, scaling, and translation) into an integrated workflow that maintains thorough error detection while improving processing efficiency through consolidated operations.
Data Source
AI summary
In an example, a method includes receiving, at least one processor, a mesh model for an object, a first transformation matrix to apply to the mesh model to describe a first object for generation in additive manufacturing and a second transformation matrix to apply to the mesh model to describe a second object for generation in additive manufacturing. The method may further include determining, by at least one processor, if the first and second transformation matrices describe transformations which are equivalent in terms of mesh errors and, if so, inspecting the mesh model for mesh errors once for both the first and second transformation matrices.