Digital Image Correlation for Local Plastic Deformation Detection
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Solution Overview
Problem
Conventional digital image correlation methods struggle to measure local plastic deformation and stress distribution in materials, especially within the elastic region, which is crucial for understanding material fatigue breakdown, as they cannot directly calculate stress from strain due to the mixture of elastic and plastic strains.
Innovation Solution
A method and device that capture images before, during, and after loading/unloading, measure strain amounts at each pixel position, and calculate stress by extracting elastic strain from total strain, allowing for the display of stress distribution on the material surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If ordinary DIC method is used to measure strain distribution, then the measurement process is simple, but local plastic deformation cannot be detected
Solution Approach 1:
The patent segments the total strain measurement into two distinct components: elastic strain (measured during loading) and plastic strain (calculated as the difference between total strain and elastic strain after unloading). This segmentation allows for precise detection of local plastic deformation by separately measuring and comparing strain states at different loading stages
Solution Approach 2:
The patent performs preliminary measurement of elastic strain during the loading phase before unloading occurs. By capturing the strain distribution while the load is applied, the system establishes a baseline that can be compared against the residual strain after unloading, enabling accurate plastic strain calculation
2Measurement precision
If conventional DIC measures only total strain, then the measurement is straightforward, but stress distribution cannot be calculated
Solution Approach 1:
The patent extracts the elastic strain component from the total strain measurement by performing DIC analysis during the loading phase when only elastic deformation is present. This extracted elastic strain information is then used to calculate stress distribution, separating the useful stress-related data from the complicating plastic deformation effects
Solution Approach 2:
The patent employs periodic loading and unloading cycles to repeatedly measure elastic strain at different stages of material degradation. By performing multiple measurement cycles, the system accumulates data on how stress distribution evolves during fatigue, enabling detection of progressive damage while maintaining measurement feasibility
3Measurement precision
If loading is kept within elastic region, then material returns to original state, but local plastic deformation due to repeated loading cannot be detected
Solution Approach 1:
The patent implements a feedback mechanism by comparing strain measurements from consecutive loading-unloading cycles. The system uses the residual strain after each cycle as feedback to detect accumulated plastic deformation, allowing progressive damage detection even when individual cycles remain within the apparent elastic region
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 the visualization and measurement of local stress and strain distributions, specifically identifying areas of local plastic deformation, thereby providing insights into material fatigue mechanisms and potential failure points.
Implementation Method 1
capturing images of the sample surface before loading, during the loading, and after unloading
Implementation Method 2
measuring a strain amount for each pixel position based on correlation between the image before the loading and the image after the unloading
Implementation Method 3
calculating stress for each pixel position based on the difference between the first strain amount and the second strain amount
Data Source
AI summary
A method of displaying stress distribution on a sample surface includes: step S4 of capturing images of the sample surface before loading, during the loading, and after unloading; step S5 of measuring a first strain amount for each pixel position based on correlation between the image before the loading and the image after the unloading; step S6 of measuring a second strain amount for each pixel position based on correlation between the image before the loading and the image during the loading; step S7 of calculating stress for each pixel position based on the difference between the first strain amount and the second strain amount; and step S8 of displaying the distribution of the calculated stress at each pixel position.