Thermal Weld Bead Monitoring Using Cooling Curve Classification
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Solution Overview
Problem
Current welding technologies lack effective non-destructive methods for continuous monitoring of weld quality, particularly in applications like automotive battery production where uniform electrical resistance is critical, and existing methods may not accurately detect defects such as contamination or material mismatch.
Innovation Solution
A method utilizing a thermal camera to capture and process thermal images of the welding zone, dividing the area into sub-areas, analyzing temperature evolutions, and training a classifier to estimate weld quality based on cooling curve parameters, which can identify defects and ensure consistent weld quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional welding quality inspection methods are used, then weld quality can be assessed, but the methods are destructive or cannot provide continuous monitoring
Solution Approach 1:
The patent replaces traditional mechanical/destructive welding inspection methods with a thermal imaging system that uses optical and thermal detection. The thermal camera captures temperature distributions in the welding zone, and processing circuits analyze thermal images to assess weld quality non-destructively, eliminating the need for physical sampling or destruction of welds.
Solution Approach 2:
The patent introduces thermal images as an intermediary medium to indirectly assess weld quality. Instead of directly examining the weld structure, the system captures thermal radiation from the welding zone, processes the thermal images to extract temperature evolution information, and uses this intermediate data to infer weld quality parameters.
2Productivity
If thermal imaging is used to monitor weld quality, then continuous non-destructive monitoring is enabled, but the system complexity increases
Solution Approach 1:
The patent segments the welding zone into multiple sub-areas for independent temperature analysis. The processing circuit divides the thermal image into regions corresponding to different parts of the weld (e.g., weld pool, heat-affected zone, base metal), allowing parallel processing of temperature data from each sub-area and enabling comprehensive monitoring without requiring a single overly complex analysis system.
Solution Approach 2:
The system uses the thermal camera and processing circuits to automatically perform quality assessment without requiring external intervention. The processing circuit autonomously captures thermal images, processes them to extract temperature evolutions, compares data against reference values, and determines weld quality, making the system self-sufficient for continuous monitoring.
3Measurement precision
If detailed thermal analysis is performed to accurately detect defects, then measurement precision improves, but processing time and complexity increase
Solution Approach 1:
The patent applies partial action by focusing thermal analysis on critical sub-areas of the welding zone where defects are most likely to occur. Instead of uniformly processing the entire welding area with equal detail, the system concentrates processing resources on regions such as the weld pool and heat-affected zone, achieving high defect detection accuracy while reducing overall processing time.
Solution Approach 2:
The system performs preliminary action by establishing reference temperature evolution data from proper welds before actual welding operations. These reference values are stored and used for rapid comparison during welding, allowing the system to quickly assess weld quality by comparing real-time thermal data against pre-established benchmarks without requiring complex real-time analysis algorithms.
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 continuous, non-destructive monitoring of weld quality by accurately identifying defects and ensuring consistent weld quality, improving the reliability of welds in applications like automotive battery production.
Implementation Method 1
a thermal camera (3) is provided, which is configured for capturing a sequence of thermal images
Data Source
AI summary
A method for analysing the quality of a weld bead in a welding zone using a thermal camera. A thermal image (IMG) of a given area is divided into a plurality of sub-areas each having a respective temperature (Ti). During a learning step, the temperature evolution (Ti(t)) of each sub-area is monitored for different welding conditions. During a training step, the temperature evolutions (Ti(t)) are processed for training a classifier (304). For this purpose, a respective cooling curve is extracted (302) from each temperature evolution (Ti(t)), and parameters (F) are determined that identify the shape of each cooling curve. The parameters (F) are used as input features for the classifier (304). In normal operation the temperature evolution (Ti(t)) of each sub-area (Ai) is monitored and the classifier (304) estimates weld quality (S).