3D Computed Tomography Anomaly Detection in Composite Materials
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Solution Overview
Problem
Current nondestructive testing methods for composite materials, such as ceramic matrix composites, are inadequate in detecting and characterizing voids and porosity, particularly in high-temperature applications, as they often produce 2-D images that fail to accurately determine the depth and thickness of anomalies, requiring extensive technician analysis and lacking in full characterization of material properties.
Innovation Solution
A method and system utilizing a three-dimensional imaging technique, like computed tomography, with a reference standard of known density to normalize and compare pixel data from test images, enabling the detection and quantification of anomalies, including porosity and delamination, by generating a full 3-D image and providing statistical analysis for accurate material assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 2-D imaging techniques (radiography, ultrasonic, infrared thermography) are used for nondestructive inspection, then the inspection process is relatively simple and fast, but the detection precision and characterization capability of anomalies (depth and thickness) are insufficient
Solution Approach 1:
The patent transitions from 2-D imaging techniques to 3-D computed tomography imaging. This dimensional change enables full characterization of anomalies including depth and thickness information, directly resolving the limitation of 2-D methods while maintaining automated analysis capabilities
2Measurement precision
If 3-D computed tomography scanning is used to fully characterize anomalies, then the measurement precision and anomaly characterization are improved, but the inspection time and productivity are reduced
Solution Approach 1:
The system performs preliminary automated processing of CT scan data including normalization to reference standards, automatic anomaly detection algorithms, and 3-D reconstruction. This preliminary automated action reduces the time required for manual technician analysis while maintaining high measurement precision
Solution Approach 2:
The patent uses a reference standard (copy of known good material) for normalization and comparison. This copying approach enables automated quantitative analysis of anomalies by comparing test specimens against the reference, reducing manual measurement time while maintaining precision
3Productivity
If automated algorithms are used for anomaly detection, then the ease of operation and productivity are improved, but the measurement precision may be compromised compared to trained technician analysis
Solution Approach 1:
The system incorporates feedback mechanisms where automated detection algorithms continuously refine anomaly characterization by comparing results against reference standards and adjusting detection parameters. This feedback loop maintains high measurement precision while preserving automated high-speed analysis capabilities
Solution Approach 2:
By using reference standards (copies of known good material) for normalization and comparison, the automated system achieves technician-level precision. The reference copy provides a baseline for quantitative anomaly measurement, enabling automated algorithms to match or exceed manual analysis accuracy
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
This approach allows for fast and reliable detection and characterization of anomalies, enabling a more comprehensive evaluation of material properties by automatically normalizing and scaling data, highlighting low-density regions, and providing quantitative analysis, thus improving the assessment of material integrity and quality.
Implementation Method 1
A three-dimensional imaging scan technique, such as a computed tomography scan, is performed of the material... test image of the material... comprise pixel data corresponding to amounts of scan energies absorbed
Data Source
AI summary
A method and system for nondestructively detecting and quantifying material anomalies within materials, including composite articles. The method entails performing a three-dimensional imaging scan technique, such as a computed tomography scan, of the material and a reference standard such that a test image of the material and a reference image of the reference standard appear in a plurality of two-dimensional scan views generated by the scan technique. The reference images are located in the scan views and normalized to determine at least an average value of the pixel data for the reference images. Values of pixel data of the test image are determined in each scan view, and then compared to the pixel data of the reference images to detect the presence of an anomaly in the test images. The detected anomaly in at least one of the test images of the scan views is then compared to a requirement standard for the material.