Contrast based imaging and analysis computer-implemented method to analyze pulse thermography data for nondestructive evaluation

Inventors

Koshti, Ajay M.

Assignees

National Aeronautics and Space Administration NASA

Publication Number

US-10728426-B1

Publication Date

2020-07-28

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 infrared (IR) video images acquired by a pulse thermography system for performing nondestructive evaluation (NDE). New video data types computed include contrast evolution data such as normalized contrast, converted contrast, and normalized temperature contrast, along with surface temperature, surface temperature rise, and temperature simple contrast. These methods process raw and smoothed video data to compute various contrast video sequence data and contrast features for anomaly detection and characterization.

The problem being solved is enhancing the analysis of IR video data obtained from pulse thermography systems used for NDE, specifically for detecting subsurface anomalies such as delaminations and cracks in thin nonmetallic materials like composites. Traditional pulse thermography detects anomalies as hot spots by observing pixel intensity differences over time, but the complexity of interpreting video data necessitates advanced processing methods. The invention addresses the need for systematic, quantitative, and calibrated methods to process and analyze these contrast evolutions, their derivatives, and other video data forms to improve defect detection, characterization, and probability of detection (POD) analysis.

Claims Coverage

The patent claims cover a comprehensive method for creating and processing video data from infrared flash thermography systems, involving data acquisition, computing contrast video sequences and derivatives, calibration using standards, anomaly characterization, and probabilistic detection analysis. These claims include 28 main inventive features focused on video processing techniques and calibration methods.

Computing normalized contrast video data and derivatives

Provides methods to compute normalized image contrast using raw or smoothed IR video data and further generate first and second derivatives through different methods including smoothing and curve fitting (simulation and non-simulation based).

Processing converted contrast video data

Introduces computation of converted contrast by multiplying relative pixel intensities by empirically derived multiplier functions to yield contrast evolutions with shape characteristics similar to normalized contrast, and deriving their derivatives similarly.

Computing normalized temperature contrast and derivatives

Describes calculating surface temperature video sequences from pixel intensities, computing normalized temperature contrast and its derivatives, and utilizing these for anomaly detection.

Extracted and frame image analysis from video sequences

Defines methods to generate frame images from selected frames and extracted images from combined or thresholded frames for various contrast data and their derivatives for visualization and analysis.

Utilizing calibration standards for parameter generation

Uses physical calibration standards with known artificial flaws to generate calibration data comprising multiple contrast evolution parameters related to flaw size and depth.

Characterizing anomaly properties using calibration data

Enables characterization of anomaly depth and diameter by comparing anomaly contrast evolution parameters with calibration data, including interpolated estimates.

Measuring flaw size using line superimposition and automated edge detection

Incorporates computerized techniques for flaw size measurement on frames using superimposed lines and automated edge detection methods.

Monitoring flaw growth through image comparison techniques

Utilizes image registration, superimposition, and subtraction of saved images for monitoring changes in thermography response to detect flaw growth.

Applying probability of detection analysis using contrast parameters

Employs normalized contrast evolution parameters and calibration data for calculating probability of detection of flaws, including utilizing diameter-to-depth ratio and thermography response correlations.

Defining and applying referenced simple contrast and detection thresholds

Introduces referenced simple contrast using reference flaws and normalizes detection thresholds to improve detection sensitivity and consistency across flashes and cameras.

The claims collectively cover methods for computer-implemented acquisition, processing, calibration, and analysis of IR flash thermography data via contrast computations and derivatives, calibration standards, anomaly characterization, image analysis, and statistical detection analysis, providing a comprehensive system for enhanced nondestructive evaluation.

Stated Advantages

Enhancement of anomaly detection and characterization accuracy through computation and analysis of normalized, converted, and temperature contrast evolutions and their derivatives.

Reduction of noise and temporal/spatial artifacts by smoothing and derivative computation techniques in video sequence data.

Improved flaw depth and size estimation via empirical calibration using standards with artificial flaws.

Capability to utilize various contrast video processing methods mutually exclusively to suit user requirements effectively.

Use of derivative-based imaging provides additional insight into flaw features such as depth and gap thickness.

Converted contrast method reduces dependence on reference region of interest, offering advantages in scenarios with limited or variable reference data.

Surface temperature contrast computation reduces influence of reflected irradiance, enhancing quantitative surface temperature measurement.

Facilitates probability of detection analyses with fewer flaws required by using calibrated contrast parameters and surface fits.

Automated measurement of flaw size and monitoring of flaw growth through image comparison enhances evaluation workflow.

Documented Applications

Non-destructive evaluation (NDE) of thin nonmetallic materials such as laminated or bonded composites in aerospace industries.

Detection and characterization of delamination-like anomalies and surface cracks in composite materials.

Inspection of test objects featuring artificial flaws such as flat bottom holes or embedded gaps for calibration and analysis.

Probability of detection (POD) analysis for flaws in materials using calibrated contrast parameters derived from flash thermography data.

Monitoring material condition and flaw growth over time by comparing registered and processed thermography images.

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