A new coal dust particle recognition algorithm based on concave points extraction and ellipse fitting is proposed for the features of irregularities and particle overlap. The new algorithm includes contour processing and ellipse fitting in this paper. In the part of contour processing, the feature points are obtained with polygonal approximation on the edge of a binary dust particles image, and then concave points of overlapping particles are extracted by the method of angle combined with size, finally the edge is segmented by concave points. To solve the problem that direct least square ellipse fitting is easily affected by noise points, bare bones particle swarm optimization is introduced to find global optimum fitting parameters and the segmented edge is ellipse fitted. Experiment results show this proposed algorithm obtains better recognition performance.

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As the improvement of environmental protection requirements, the application of Hazard-free household disposal system becomes more widely. This paper expounded the applications of Siemens S7-300 in systems, described both the characteristics of Siemens software redundancy and its design and implementation in system in detail. The system has been successfully put into production and it operates stably in Linyi.