Design And Research Of Coal Dust Concentration Analysis System

Currently, our coal accounts for about 70% in the total energy consumption, and we d emand the coal fiercely. However, our coal mining is underground working which uses me chanical mining, and during the process of mining, a large amount of coal dust must be ace ompanied. Coal dust which has great bad effects is harmful to miner and cause machine ab rasion, and even cause explosion, resulting in serious consequence.This article analyzes the various types of coal dust detection method, Describes the current shortcomings of coal dust in the detection. Such as the concentration of the collected instantaneous value, the concentration of coal dust collected is a point in time and place, can not reflect real-time coal dust pollution in the workplace, in addition to the results of some measurement error was relatively large. In response to these drawbacks, and in order to collect true picture of coal dust, the paper designed a specific monitoring of coal dust collection device. Using image processing, presents a viable method for detecting concentration detecting coal dust. In the case of the collected dust in noisy images using an improved minimum mean square error estimation (IMMSE) denoising algorithm. In order to restore a clear picture of coal dust, using the Z-transform-based motion blur recovery algorithm. Using the improved particle swarm optimization and fuzzy entropy segmentation algorithm for image segmentation of coal dust in image recognition. Overall completion of a simplified algorithm, reducing the amount of computation. After Matlab simulation results show that the improved algorithm is effective.Underground coal dust concentration in study design analysis system has the advantage of clear image capture, real-time performance, and given algorithm has great reference value in the dust in terms of image-based detection.