Battery Cell Weld Boundary Inspection for Seal Defect Detection
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Solution Overview
Problem
The welding area in battery cells is prone to damage from external impacts and vibrations, leading to potential leaks and loss of sealing properties, necessitating an accurate and efficient quality test method to ensure proper formation without defects.
Innovation Solution
A quality test method that captures an image of the welding area, calculates points along boundary lines, and determines defectiveness based on point numbers and distances within preset reference ranges, using an imaging device and a quality test system with a processor to analyze the image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the welding area is tested using conventional methods, then the testing process is simple, but the accuracy and defect detection capability are insufficient
Solution Approach 1:
The patent replaces conventional mechanical or manual welding inspection methods with an optical imaging system. The imaging device captures images of the welding area, and image processing algorithms automatically analyze the welding quality by detecting boundary lines and calculating geometric parameters, eliminating the need for complex mechanical measurement tools.
Solution Approach 2:
The patent creates a digital copy of the welding area through imaging. By capturing the welding area in an image and processing it to extract boundary lines and geometric features, the system analyzes the welding quality without physically contacting or disturbing the actual welding joint, enabling non-destructive high-precision inspection.
2Productivity
If manual inspection methods are used, then the equipment is simple, but the defect detection capability and efficiency are low
Solution Approach 1:
The system performs self-inspection by automatically capturing images of the welding area and processing them through algorithms that detect boundary lines, calculate distances, and determine welding quality. The system evaluates its own output (the welding joint) without requiring external manual intervention, enabling rapid automated quality control.
Solution Approach 2:
The patent replaces manual inspection processes with automated optical imaging and image processing. The system automatically captures images, processes them to extract welding area boundaries, calculates geometric parameters, and determines quality, eliminating the time-consuming nature of manual inspection and significantly improving testing efficiency.
3Reliability
If comprehensive quality testing is performed, then the reliability improves, but the testing time increases
Solution Approach 1:
The patent enables continuous quality testing by implementing an automated imaging and processing system that can rapidly capture and analyze welding areas without interruption. The continuous flow of image capture and automated processing allows for real-time quality assessment, maintaining high reliability while minimizing testing time through uninterrupted operation.
Solution Approach 2:
The system performs preliminary image capture and processing immediately after welding is completed. By quickly capturing the welding area image and automatically processing it to detect boundary lines and calculate geometric parameters, the system provides rapid quality feedback, enabling timely detection without significant time loss while ensuring comprehensive quality assessment.
Data Source
AI summary
The present disclosure relates to a test quality method and a test quality system. The quality test method of a battery cell including a can having an open surface; a cap welded to the can and covering the open surface; and a welding area formed by welding according to embodiments of the present disclosure includes capturing an image of the welding area with an imaging device, calculating a plurality of first points arranged along a first boundary line and a plurality of second points corresponding to the plurality of first points and arranged along a second boundary line, the first and second boundary lines separating the welding area from a non-welding area in the image, and determining whether the welding area is defective based on a number of the plurality of first points and a number of the plurality of second points.