Particle Shape Analysis for Overlapping Asbestos Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing particle measurement systems struggle to accurately identify asbestos particles due to their needle or string shape, especially when they overlap, leading to difficulty in distinguishing them from other elongated particles and causing variations in analysis results depending on human inspectors.
Innovation Solution
A particle analysis apparatus and method that calculates angles representing the orientation of planes at each coordinate in a beam scanning range, applies normalization based on the shape of interest, and analyzes candidate particles using normalized angles to determine if they are asbestos particles, utilizing rotational symmetry and mathematical operations to distinguish convex regions from concave ones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional particle measurement systems calculate aspect ratio to identify asbestos particles, then identification can be performed, but accurate identification becomes difficult when particles overlap or when distinguishing from other elongated particles
Solution Approach 1:
The invention transforms the identification approach by changing from aspect ratio calculation to curvature radius calculation. By computing the curvature radius at multiple points along the particle contour and analyzing its distribution characteristics, the system can accurately identify asbestos particles even when overlapping or similar in aspect ratio to other particles. This parameter transformation resolves the identification difficulty.
Solution Approach 2:
The invention segments the particle identification process into multiple steps: contour extraction, curvature radius calculation at multiple points, statistical analysis of curvature distribution, and comparison with reference data. This segmentation allows each step to be optimized independently and handles complex overlapping scenarios by breaking down the identification task into manageable components.
2Measurement precision
If human inspectors manually identify asbestos particles, then detailed analysis can be performed, but significant burden is caused and variation occurs in analysis results
Solution Approach 1:
The invention replaces the manual mechanical inspection process with an automated computational system. The curvature radius calculation method, combined with statistical analysis and reference data comparison, automates the identification process while maintaining or improving consistency. This substitution eliminates human burden and variation while achieving reliable particle identification.
3Measurement precision
If conventional methods analyze particle shape using simple geometric parameters, then processing is simple, but precise identification of particles with specific shapes like needle or string shape becomes difficult
Solution Approach 1:
The invention changes the shape analysis parameter from simple geometric measurements (aspect ratio) to curvature radius distribution analysis. By calculating curvature radii at multiple points along the particle contour and analyzing their statistical characteristics, the system can precisely identify particles with specific shapes like needle or string shape, overcoming the limitations of simple geometric parameters.
Data Source
AI summary
An angle calculator calculates, for each coordinate in a beam scanning range, an angle representing an orientation of a plane based on an intensity distribution. A normalizer multiplies an angle array produced by the angle calculator by a numerical value corresponding to a shape of interest (for example, a needle shape or a string shape). A particle-of-interest analyzer analyzes whether a candidate particle is a particle of interest, based on a group of normalized angles corresponding to the candidate particle.