Infrared Thermal Image Analyzer Gradient Compensation
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Solution Overview
Problem
Infrared-ray inspection methods struggle to accurately distinguish between defective and non-defective regions in structures due to temperature gradients on the surface, making it difficult for inexperienced operators to identify damage using IR thermal images.
Innovation Solution
An IR thermal image analyzer that includes an IR camera, an image processing unit to extract temperature variations excluding gradients, and an image display unit to show these variations, employing techniques like moving average processing, emphasizing processing, and defect depth correlation to enhance the visibility of defective regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If infrared-ray inspection method is used to detect defective regions, then wide range investigation can be performed efficiently, but accurate discrimination between defective and non-defective regions becomes difficult when temperature gradient exists on structure surface
Solution Approach 1:
The patent introduces an image processing unit as an intermediary between the IR camera and the operator. This unit automatically processes the thermal image to extract temperature distribution information, calculate temperature gradients, and highlight defective regions. The intermediary performs complex thermal analysis that would be difficult for inexperienced operators to perform manually, thereby maintaining high inspection efficiency while improving defect detection accuracy.
Solution Approach 2:
The patent replaces the manual visual inspection process (mechanical system of human perception) with automated image processing algorithms. The system uses computational methods to analyze thermal patterns, calculate temperature gradients, and identify defective regions, substituting human judgment with automated thermal analysis that is not affected by operator experience or fatigue.
2Ease of operation
If manual interpretation of IR thermal image is performed by inexperienced operator, then operation simplicity is maintained, but ability to discriminate defective regions deteriorates due to temperature gradient interference
Solution Approach 1:
The system performs self-service by automatically analyzing the thermal image and identifying defective regions without requiring operator expertise. The image processing unit independently calculates temperature distributions, detects anomalies, and presents processed results, allowing the system to serve itself in the analytical task rather than relying on human operator capability.
Solution Approach 2:
The image processing unit acts as an intermediary that bridges the gap between the complex thermal data and the inexperienced operator. It translates raw thermal information into processed visual outputs that highlight defective regions, making the inspection process easy to operate while maintaining high discrimination accuracy through automated analysis.
3Measurement precision
If temperature gradient compensation processing is added to remove temperature gradient effects, then defect detection accuracy is improved, but device complexity increases due to additional image processing functions
Solution Approach 1:
The patent merges multiple image processing functions into a single integrated image processing unit. The unit combines temperature distribution calculation, gradient analysis, and defect detection algorithms into one cohesive system component. This merging approach improves defect detection accuracy through comprehensive thermal analysis while avoiding the complexity increase that would result from separate independent processing modules.
Solution Approach 2:
The image processing unit is designed with multi-functionality, performing temperature distribution calculation, gradient computation, and defect identification within a single device. This universal approach allows the system to achieve high measurement precision through multiple processing capabilities while maintaining relatively simple device architecture by consolidating functions rather than multiplying separate components.
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
The solution allows for clear identification of defective regions and estimation of defect depth, even with temperature gradients, enabling easier detection and prediction of risk levels in structures.
Implementation Method 1
an IR camera 10 for taking an IR thermal image of a surface of a structure 40
Implementation Method 2
An IR camera 91 detects infrared ray energy emitted from an object to be measured 94 such as a structure
Data Source
AI summary
The IR camera (10) takes an IR thermal image of a surface of the structure (40). In the IR thermal image, temperature gradient is superposed besides temperature difference between non-defective and defective regions of the structure. The image processing unit (21) of the analysis unit (20) produces an image indicating distribution of a temperature variation other than a temperature gradient by extracting the distribution of the temperature variation from the IR thermal image. The image display unit (30) displays the image produced by the image processing unit (21). Since the distribution of the temperature variation other than the temperature gradient is extracted from the IR thermal image, a temperature difference between defective and non-defective regions in the structure (40) can be clearly displayed. Therefore, even if there exists a temperature gradient on the structure surface, the defect location in the structure can be easily determined.