Integrating image processing and deep learning for effective analysis and classification of dust pollution in mining processes

A comprehensive evaluation method is proposed to analyze dust pollution generated in the production process of mines.The method employs an optimized image-processing and deep learning framework to characterize the gray and fractal features in dust images.The research reveals both linear and logarithmic correlations between the gray features,fractal dimension,and dust mass,while employing Chauvenel criteria and arithmetic averaging to minimize data discreteness.An integrated hazardous index is developed,including a logarithmic correlation between the index and dust mass,and a four-category dataset is subsequently prepared for the deep learning framework.Based on the range of the hazardous index,the dust images are divided into four categories.Subsequently,a dust risk classifcation system is established using the deep learning model,which exhibits a high degree of performance after the training process.Notably,the model achieves a testing accuracy of 95.3%,indicating its efectiveness in classifying diferent levels of dust pollution,and the precision,recall,and F1-score of the system confrm its reliability in analyzing dust pollution.Overall,the proposed method provides a reliable and efcient way to monitor and analyze dust pollution in mines.

Experimental and numerical simulation study on forced ventilation and dust removal of coal mine heading surface

In order to study the problems of unreasonable airflow distribution and serious dust pollution in a heading surface,an experimental platform for forced ventilation and dust removal was built based on the similar principles.Through the similar experiment and numerical simulation,the distribution of airflow field in the roadway and the spatial and temporal evolution of dust pollution under the conditions of forced ventilation were determined.The airflow field in the roadway can be divided into three zones:jet zone,vortex zone and reflux zone.The dust concentration gradually decreases from the head to the rear of the roadway.Under the forced ventilation conditions,there is a unilateral accumulation of dust,with higher dust concentrations away from the ducts.The position of the equipment has an interception effect on the dust.The maximum error between the test value and the simulation result is 12.9%,which verifies the accuracy of the experimental results.The research results can provide theoretical guidance for the application of dust removal technology in coal mine.

The Pollution Character Analysis and Risk Assessment for Metals in Dust and PM_(10) around Road from China

INTRODUCTION In recent years, with the gradual improvement of road construction, the rapid increase of the number of motor vehicles, vehicle emissions and the current poor vehicle performance, poor vehicle maintenance, higher emission factor and so on, air pollution caused by the traffic issues becomes the focus of people attention. The harmful substances are gradually accumulated to atmosphere particles surrounding roads due to dust particles （soil dusts, road dusts, construction dusts）, coal emissions, industrial emissions, vehicle emissions, biomass burning, secondary particles, which has a certain harmful influence to the atmosphere, soil and plants surrounding roads.

THE RELATION OF THE THRESHOLD VELOCITY OF COAL DUST TO ITS SIZE AND HUMIDITY

On the ground of wharf and a station where coal is piled up, the sources polluting the atmosphere are mainly the raised coal dust. According to the principle of mechanics, with the consideration of the gravities of coal dust particles and liquid droplets, coal dust size and humidity, under the condition of force balance when the coal dust was raised, the authors obtaineda theoretical formula for the threshold velocity of coal dust with humidity,Finally, the theoretical values from the formula gave a good agreement with the experimental data from some wind tunnels.

Scattering properties of polluted dust in 1.6-μm wavelength

Three typical polluted dust particles （i.e., single coated dust, two-sphere/spheroid system, and coated dust with ag- gregate） including internal and semi-external mixtures are modeled, and their scattering properties at 1.6-μm wavelength are calculated by using the generalized multi-sphere Mie-solution （GMM） method. We investigate the influences of par- ticle size, morphology, and chemical composition on the scattering parameters of polluted dust particles. The analysis results demonstrate that the single scattering albedo of coated dust is much smaller than that of pure dust, especially for the spheroidal black carbon （BC） coated dust. When a dust particle semi-mixes with another aerosol particle to form a two-sphere/spheroid system, its scattering properties are much more sensitive to the size and species of monomers than the monomer shape. If an aggregated BC attaches to the coated dust, the scattering properties of whole particle mainly depend on the host particle （coated dust）.