Dust explosion solid product morphological parameter identification method based on image processing

Abstract

The invention relates to a dust explosion solid product morphological parameter identification method based on image processing, and belongs to the field of dust explosion accident investigation and damage diagnosis. The method comprises the following steps: S1, an explosion experiment: carrying out a mixed explosion experiment of methane and coal dust with different concentrations in a 20L explosion ball; s2, screening and sample preparation: collecting solid residues after an explosion experiment, screening particle residues by using sieves with different particle sizes, and preparing observation samples; s3, electron microscope scanning treatment: carrying out electron microscope scanning on the samples prepared from the collected solid residues to obtain microstructure images of the samples with different granularities; s4, importing software for processing: reading the obtained electron microscope scanning microstructure image of the sample by using the software; and S5, parameter extraction: preprocessing an electron microscope scanning image through developed software, analyzing image data, and extracting characteristic parameters after analysis.

Description

technical field [0001] The invention belongs to the field of dust explosion accident investigation and damage diagnosis, and relates to a method for identifying morphological parameters of dust explosion solid products based on image processing. Background technique [0002] Chemical analysis of powder explosion residues is one of the important methods for the investigation and damage assessment of coal mine explosion accidents, and is widely used in many fields. The gas and solid particle residues produced after the coal dust explosion can directly reflect the explosion severity, reaction mechanism and disaster nature. There have been many studies on the experimental analysis of coal dust gas and residues caused by explosions in China. At present, the analysis techniques applied to the particle morphology of explosive residues include spectroscopic analysis, scanning electron microscopy and energy dispersive analysis, capillary electrophoresis, ion chromatography, gas chro...

AI Technical Summary

Problems solved by technology

However, when the gray value difference in the image is not obvious or the gray range overlaps, over-segmentation or under-segmentation may occur.

In addition, the threshold segmentation method only considers the grayscale information of the image, and does not pay attention to the spatial and texture features of the image.

Therefore, the characterization of many characteristic information of particles is not perfect

Images