Thermography Flaw Characterization in Composites
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Solution Overview
Problem
Current thermography methods can locate material characteristic flaws in composite materials but fail to identify the type of flaws, such as delaminations and porosity, only determining their size, location, and relative depth.
Innovation Solution
A method involving rapid surface heating, recording IR image sequences, determining temperature-versus-time data for each pixel, and using contrast curves derived from synthetic thermal reference data to characterize material flaws, including delaminations and porosity, by analyzing the shape and shape of peaks in the contrast curves.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If thermography is used to locate flaws in composite materials, then the location and size of flaws can be determined, but the type of material characteristic flaws (such as porosity vs. delaminations) cannot be identified
Solution Approach 1:
The patent applies parameter changes by analyzing multiple parameters from the thermal response data, including temperature versus time curves, contrast curves, and their derivatives. By examining changes in these parameters (such as peak positions, peak heights, and curve shapes), the system can distinguish between different flaw types like porosity and delaminations, thereby recovering the lost flaw type information while maintaining precise flaw location capability
Solution Approach 2:
The patent transitions from two-dimensional spatial flaw detection to three-dimensional characterization by incorporating the temporal dimension through time-resolved thermography. By analyzing the temporal evolution of thermal contrast and its derivatives, the system adds a new dimension of information that enables differentiation of flaw types based on their distinct thermal response signatures over time
2Productivity
If conventional thermography methods are used, then the process is simple and quick, but the ability to discriminate between different flaw types (porosity, delaminations) is insufficient
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing reference thermal response curves for different flaw types (porosity, delaminations, and sound material) before actual inspection. During inspection, measured thermal responses are quickly compared against these pre-established references, enabling rapid flaw type discrimination without requiring complex real-time analysis, thus maintaining high inspection speed while improving discrimination 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
Enables non-destructive identification and discrimination between different types of material characteristic flaws, such as delaminations and porosity, by displaying areas corresponding to specific flaw types in different colors, enhancing the accuracy of flaw characterization in composite materials.
Implementation Method 1
heat is applied to an object and a resulting temperature distribution on a surface of the object is measured over time
Implementation Method 2
a resulting temperature distribution on a surface of the object is measured over time with an infrared camera
Data Source
AI summary
A method for identifying types of flaws in a composite object includes: a) rapidly heating the surface of the object; b) recording pixel intensities in a sequence of IR images; c) determining temperature-versus-time data for each of the pixels from the IR images; and d) determining what type of flaw if any corresponds to each of the pixels using the temperature-versus-time data determined in step (c). A contrast curve derived from the temperature-versus-time data may be used in determining what type of flaws if any corresponds to each of the pixels. The contrast curve may be determined by subtracting a synthetic reference curve from a temperature time curve from the temperature-versus-time data. The types of flaws may be determined from size and/or shapes of peaks in the contrast curves. Some flaws are delaminations, layers of porosity, and uniformly distributed porosity.