CT Scanner Volumetric Data Region Extraction
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Solution Overview
Problem
Non-destructive testing systems generate large amounts of data, much of which is unnecessary for defect detection, leading to inefficiencies in data transfer, storage, and retrieval, as only small portions of the data are relevant to identifying defects within parts.
Innovation Solution
A system and method that involve generating a volumetric representation of a part-under-inspection, locating defects, and establishing a region of interest to selectively reduce data by applying different formats to data inside and outside this region, thereby compressing and transferring only the necessary data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all scan data is preserved and transferred, then complete inspection data is available, but data transfer time and storage requirements increase significantly
Solution Approach 1:
The system extracts and identifies only the defective regions from the complete volumetric scan data. By isolating and retaining only the relevant defect portions while discarding normal regions, the system achieves both complete inspection capability and reduced data transfer requirements.
Solution Approach 2:
The system applies different data retention strategies to different regions of the scanned part. Defective regions are preserved with high detail while normal regions are discarded, creating a locally optimized data set that maintains inspection quality where needed while reducing overall data volume.
2Measurement precision
If all volumetric data is stored and transferred, then no inspection detail is lost, but data storage space and transfer bandwidth are wasted on unnecessary data
Solution Approach 1:
The system extracts defective regions from the complete volumetric data set by comparing against a reference model. Only the extracted defect portions are retained for storage and transfer, eliminating unnecessary normal region data while preserving all inspection-relevant information.
Solution Approach 2:
Instead of processing or storing the complete volumetric data set, the system performs partial action by focusing only on the defective regions. This partial processing approach maintains measurement precision for defect detection while significantly reducing the quantity of data that must be stored and transferred.
3Adaptability or versatility
If complete volumetric representations are transferred for remote storage and analysis, then full data availability is achieved, but transfer efficiency and storage costs decrease
Solution Approach 1:
The system extracts and transfers only the defective regions to remote storage locations rather than complete volumetric representations. This extraction approach maintains data availability for defect analysis while dramatically improving transfer efficiency and reducing storage requirements.
Solution Approach 2:
The volumetric data is segmented into defective and non-defective regions. Only the relevant defective segments are transferred for remote storage and analysis, while non-defective segments are discarded locally. This segmentation improves both data availability for critical analysis and transfer efficiency.
Data Source
AI summary
Systems and methods are described that reduce the amount of data that is transferred among the components of the system. In one embodiment, the testing system comprises a scanner device such as a computed-tomography (CT) scanner that generates a volumetric representation of a part-under-inspection. The testing system is further configured to identify a region of interest in the volumetric representation, wherein the region of interest may correspond to an area of the part-under-inspection where a defect or flaw may form. The testing system may further format the data of the volumetric representation so the resulting formatted volumetric representation comprises less data than the original volumetric representation.