X-Ray Metallic Dust Mapping for Faster Battery Contamination Analysis
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Solution Overview
Problem
Existing methods for detecting and analyzing metallic dust in secondary battery manufacturing facilities are inefficient, time-consuming, and inaccurate, lacking a standardized approach for quantifying and qualifying metal dusts, which can lead to performance deterioration and safety issues.
Innovation Solution
A metallic dust analysis system and method utilizing X-ray transmission imaging to selectively detect and quantify metallic dust within a predetermined size range, generating mapping image data and component analysis data, with automated processing and identification codes for efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods (tape capture + SEM/XRF analysis) are used to detect and analyze metallic dust, then detection capability is provided, but the process is very time-consuming and requires manual operation
Solution Approach 1:
The patent replaces manual mechanical operations (tape capture, manual SEM/XRF analysis) with an automated optical imaging system using a microscope and image processing algorithms. This substitution enables rapid automated detection and analysis of metallic dust particles, reducing analysis time from hours/days to minutes while maintaining detection accuracy through systematic image processing and particle identification algorithms
Solution Approach 2:
The system enables self-service through automated image processing where the microscope system automatically captures images, processes them through algorithms to identify metallic dust particles, and generates analysis results without requiring continuous manual intervention. The automated processing includes particle detection, classification, and measurement functions that operate independently once the sample is prepared
2Reliability
If conventional analysis methods are used, then metallic dust can be detected, but the process is complex and requires multiple steps including tape capture and microscope analysis
Solution Approach 1:
The patent merges multiple separate operations (sample capture, mounting, imaging, analysis) into a unified automated optical imaging system. By combining these functions into a single integrated system with automated image processing, the patent reduces procedural complexity while maintaining reliable detection through systematic processing of the entire analysis workflow
3Measurement precision
If conventional methods are used to analyze all dust types, then comprehensive dust analysis is achieved, but the process cannot selectively identify and quantify only metallic dust efficiently
Solution Approach 1:
The patent applies local quality by using image processing algorithms with specific parameters optimized for detecting metallic dust characteristics (reflectivity, shape, size). The system selectively identifies metallic particles based on their unique optical properties in the captured images, enabling precise quantification of metallic dust while filtering out non-metallic particles, thereby improving both accuracy and efficiency
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 rapid and accurate detection and analysis of metallic dust distribution and composition, facilitating timely identification of defects and improving manufacturing quality by automating the detection process.
Implementation Method 1
a dust analysis part configured to generate X-ray transmission images of each specimen and reference specimen
Data Source
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AI summary
Disclosed herein relates to a metallic dust analysis system according to exemplary embodiments of the present disclosure including a dust analysis part, wherein the dust analysis part is configured to generate X-ray transmission images of each specimen and reference specimen, process the X-ray transmission images of the specimens to generate mapping image data of the specimens in which metal dusts having a diameter within a predetermined range are selectively displayed, and generate component analysis data for each of the metal dusts identified in the mapping image data.