Spectral Battery Imaging for Heat Generation Defect Detection
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Solution Overview
Problem
Existing methods for inspecting battery heat generation during the production process are inefficient, inaccurate, and require significant human intervention, leading to reduced battery lifespan and potential safety hazards.
Innovation Solution
A spectral image-based method and device that utilizes a spectral camera, memory, and processor to collect, process, and analyze battery images through supervised and unsupervised learning to accurately distinguish between good and defective batteries by creating a reference model using multimodal data and radiomics features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional inspection methods are used for battery heat generation, then the inspection process can be performed with simple equipment, but the inspection accuracy is low and human intervention is required
Solution Approach 1:
The patent replaces traditional mechanical inspection methods with a spectral imaging system that uses electromagnetic radiation (visible, infrared, ultraviolet bands) to detect heat generation. The spectral camera captures spectral images across multiple frequency bands, and a processor automatically analyzes these images to identify batteries with abnormal heat generation, eliminating the need for manual inspection while significantly improving measurement precision.
2Productivity
If manual inspection methods are used, then the equipment cost is low, but the inspection speed is slow and productivity is reduced
Solution Approach 1:
The spectral imaging system enables continuous inspection of batteries during the charging/discharging process. The spectral camera continuously captures spectral images, and the processor continuously analyzes these images to detect heat generation in real-time, maintaining continuous useful action throughout the inspection process rather than using intermittent manual checking.
Solution Approach 2:
The system creates spectral image copies of batteries across multiple frequency bands (visible, infrared, ultraviolet) and processes these digital copies to identify abnormalities. This allows simultaneous analysis of multiple spectral characteristics without requiring physical contact or multiple inspection passes, significantly improving inspection speed.
3Measurement precision
If comprehensive spectral analysis is performed across multiple frequency bands, then the inspection accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The patent segments the spectral analysis into distinct frequency bands (visible light band, infrared band, ultraviolet band), with each band processed independently to extract specific thermal characteristics. The processor analyzes each band separately and integrates the results, making the complex multi-band analysis manageable while preserving the diagnostic information from each spectral region.
Solution Approach 2:
The processor acts as an intermediary that receives raw spectral image data from the spectral camera, applies preprocessing operations (noise filtering, normalization), and transforms the complex multi-band spectral data into simplified thermal maps and heat generation indicators. This intermediary processing step reduces data complexity while maintaining measurement precision.
Data Source
AI summary
Disclosed may be a spectral image-based battery heat generation inspection method and an apparatus supporting same, the method comprising the steps of: collecting a current spectral image of a battery that is being charged or discharged; performing processing on the current spectral image; a processor, on the basis of the result of the processing, determining whether the battery is of high quality or poor quality; and outputting the result of determining whether being of high quality or poor quality.