The microseismic signals of rock fractures indicate that the rock mass in a particular area is changing slowly, and the microseismic signals of rock blasting indicate that the rock mass in a particular area is changing violently. It is of great significance to accurately distinguish rock fracture signals and rock microseismic signals for analyzing the changes in the rock mass in the area where the signal occurs. Considering the microseismic signals of the Dahongshan Iron Mine, the time domain, frequency domain, energy characteristic distribution, and fractal features of each signal were analyzed after noise reduction of the original signal. The results demonstrate that the signal duration and maximum amplitude of the signal could not accurately distinguish the two types of signals. However, the main frequency of the rock fracture signal after noise reduction is distributed above 500 HZ, and the main frequency of the rock blasting signal is mainly distributed below 500 HZ. After the denoised signal is decomposed by the ensemble empirical simulation decomposition, the energy of the IMF1 frequency band of the rock fracture signal occupies an absolute dominant position, and the sum of the energy of the IMF2–IMF4 frequency bands of the rock blasting signal occupies a dominant position. The fractal box dimension of the rock fracture signal is mainly below 1.1, and the fractal box dimension of the rock blasting signal is mainly above 1.25. According to the above research results, an automatic signal recognition system based on the BP neural network is established, and the recognition accuracy of the rock blasting and rock fracture signals reached 93% and 94% respectively, when this system was used.
Slope reinforcement is a common method to solve the problem of slope instability, and reasonable optimization of the corresponding support parameters is crucial for practical engineering. In this paper, the slope support method of Manyanpo tunnel entrance section is taken as an example, and the theoretical calculation method is used to optimize the project cost. Combined with the orthogonal test, the sensitivity analysis of the influencing factors of the stability of the support system and the selection of the optimal parameter combination scheme are carried out. Then, based on flac3d software, the optimization scheme is compared with the original design scheme. The results show that the safety factor of the optimized scheme is increased from 1.32 to 1.43 compared with the actual project. The optimized support parameters have better control effect on the displacement of the slope, especially in the Z direction. The optimized parameters have better support effect. This study can provide reference for the optimization design of slope engineering support.
The problems concerning multi-mineral source, multi-ore-dressing plant, multi-mineral of complex mining and ore-dressing systems in regional mine emerge gradually, with resources changes in new areas, such as an unreasonable overall layout of production, overlap and duplicated construction. From the perspective of complex systems theory, this article used the theories and methods of system science, computer science, mathematics, economics and so on, and also built the global optimization matching model. We study the global optimization of mining and ore-dressing systems of regional mine using Genetic Algorithm, that providing a theoretical basis for the realization of organic connection of complex systems in the region, overall best match and scientific and orderly exploitation of mineral resources etc. Thus, the level of development and utilization of mineral resources and economic benefits of regional mine have been increased.
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