Contrast based imaging and analysis computer-implemented method to analyze pulse thermography data for nondestructive evaluation
Inventors
Assignees
National Aeronautics and Space Administration NASA
Publication Number
US-10332248-B1
Publication Date
2019-06-25
Expiration Date
2037-08-16
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Abstract
Methods and systems for analyzing and processing digital data comprising a plurality of infra-red (IR) video images acquired by a pulse thermography system are used to compute video data from the raw and smoothed video data acquired for the performance of non-destructive evaluation. New video data types computed may include but are not limited to contrast evolution data such as normalized contrast, converted contrast and normalized temperature contrast. Additionally, video data types computed comprise surface temperature, surface temperature rise and temperature simple contrast.
Core Innovation
The invention provides methods and systems for analyzing and processing digital data comprising a plurality of infra-red (IR) video images acquired by a pulse thermography system to compute video data from the raw and smoothed video data acquired for the performance of non-destructive evaluation. The invention includes new video data types such as contrast evolution data including normalized contrast, converted contrast, and normalized temperature contrast, as well as video data types comprising surface temperature, surface temperature rise, and temperature simple contrast.
The problem being solved is the need for improved techniques in non-destructive evaluation (NDE) using infrared flash thermography, especially for detecting and characterizing subsurface anomalies such as delaminations in materials. Existing methods require enhancement to better analyze pixel intensity data and its derivatives to extract anomaly information, including depth, size, and gap thickness, while suppressing temporal and spatial noise within the thermography data. The invention addresses the computational and analytical challenges of transforming raw IR video data into meaningful contrast metrics and derivative features that improve flaw detection and characterization.
Claims Coverage
The patent claims cover several inventive features primarily related to methods and apparatus for processing infrared flash thermography video data to compute contrast values, derivatives, and calibration-based characterization of anomalies in materials.
Method for computing converted contrast video data and derivatives
This feature encompasses selecting video frames of IR surface temperature pixel intensity post flash, defining measurement and reference regions of interest (ROIs), and computing converted contrast (CC) video data using a multiplier function applied to pixel intensity changes. It further includes computing first and second temporal derivatives of CC, smoothing during derivative computation, using curve fits (simulation or non-simulation) to compute derivatives, and producing extracted images and frame images from CC or its derivatives.
Flaw size measurement and automated edge detection
This feature involves measuring flaw size on video frames by superimposing lines for computerized distance measurement and using automated edge detection techniques to assess flaw dimensions in the processed thermography images.
Monitoring flaw growth via image comparison techniques
This includes producing reference images and then comparing these reference images to subsequent images through image registration, superimposition, or subtraction to monitor changes in thermography responses over time.
Use of calibration standards in video data processing
Incorporating calibration standards with known openings of predefined diameter and depth, selecting reference ROIs on anomaly-free areas, and using these in the computation of contrast evolution data to characterize anomalies under evaluation.
Probability of detection (POD) analysis based on contrast metrics
Utilizing a flaw size input consistent with diameter-to-depth ratio and establishing percent detection thresholds via pixel intensity comparisons to determine POD for flaws based on thermography response correlations to diameter and depth.
Characterizing unknown anomalies using calibrated contrast evolution parameters
A method of recording video data from artificial anomalies of known size, computing contrast evolution parameters (peak contrast, peak time, time scale factor, offset time, begin time, slope), and using these parameters alongside unknown anomaly contrast evolution to characterize anomaly size and depth.
Apparatus for anomaly characterization using calibration data
An apparatus configured with a processor and memory to calculate contrast evolution parameters of an unknown anomaly and determine its diameter and depth by relating these parameters to calibration files derived from known artificial anomalies.
The claims comprehensively cover computational methods and apparatus for generating and analyzing contrast-based video data from flash thermography, including derivative computations, calibration techniques, flaw sizing, monitoring through image comparisons, and statistical probability of detection analysis, thereby providing a full suite for non-destructive evaluation of material anomalies.
Stated Advantages
Provides enhanced anomaly detection and characterization through the use of normalized, converted, and normalized temperature contrast video methods.
Improves detection accuracy by suppressing temporal and spatial noise via derivative-based imaging approaches and smoothing techniques.
Offers quantitative calibration methods enabling estimation of anomaly depth and size using empirical data from standards with known flaw dimensions.
Enables improved graphical representation and signal-to-noise ratio through converted contrast processing over normalized contrast.
Enhances imaging by reducing the influence of diffused reflection using normalized temperature contrast.
Facilitates probability of detection (POD) analysis by providing correlations between contrast responses and flaw geometry, improving flaw detection sensitivity.
Allows monitoring of flaw growth via image registration and comparison techniques, supporting material condition assessment over time.
Documented Applications
Non-destructive evaluation of thin nonmetallic materials such as laminated or bonded composites, primarily for aerospace inspection.
Detection and characterization of delamination-like anomalies and surface cracks using single-sided reflection infrared flash thermography.
Use in inspecting test plates and calibration standards with artificial flaws such as flat bottom holes or embedded gaps.
Flaw depth and size estimation in materials through calibrated contrast evolution analysis.
Flaw detection and acceptance/rejection decision-making via contrast-based thermography responses and probability of detection analysis.
Monitoring material condition and flaw growth by comparing registered thermography images over time.
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