Analysis Of Vibration Response Of Slope Blasting And Study On Prediction Method Of Blasting Result Parameters

With the development of infrastructure construction and mining in China,slope topographic blasting has been applied more and more widely.However,the safety hazards caused in the process of production have seriously affected the normal construction and the safety of surrounding residents’ lives and property.Therefore,the research on the mechanism of blasting load and the law of energy attenuation of slope topography,as well as the research on the prediction method of blasting particle peak velocity,blasting frequency and duration have important engineering reference significance.In this paper,MATLAB software is used to optimize BP neural network in two aspects.First,an intelligent program is designed to select the number of nodes in the hidden layer,so that the number of nodes in the hidden layer which has the best prediction effect on the detection samples can be selected.Secondly,genetic algorithm is used to modify the connection weight and threshold of BP neural network model.Two typical cases of slope blasting are cited to verify the reliability of the program.It is found that the average relative error of the prediction by the optimized GA-BP neural network model is less than 10%,and the program is reliable and the convergence speed of GA-BP neural network is greatly improved compared with the traditional BP network model.The finite element software LS-DYNA is used to simulate Xinjiang Cihai Iron Mine.The multi-step blasting process under different blasting parameters was studied,and the peak velocity data was extracted.Based on the measured data,the errors were compared with the calculation results of Sadowski formula and the prediction results of GA-BP neural network.It is found that the errors of numerical simulation results and GA-BP prediction results are less than 10%,while the errors of Sadowski formula prediction results are more than 20%.Comparing the different prediction methods,it can be concluded that the optimized neural network algorithm and numerical simulation have the highest prediction accuracy for blasting result parameters.The blasting energy comprehensively considers the peak velocity of blasting particles,blasting frequency and duration.In this paper,the total energy calculation method based on unit energy flux is used to calculate the blasting vibration wave energy of Cihai Iron Mine in Xinjiang,and the total energy of blasting vibration and the peak velocity of blasting vibration are respectively normalized.It is found that the attenuation curve of the normalized value of blasting vibration energy along the slope is very similar to the attenuation curve of the normalized value of velocity.The attenuation of the blasting vibration is fast in the near area and slow in the far area.The energy of the blasting vibration signal is most affected by the velocity peak.The research model and results obtained in this paper can be used as reference guidance for engineering practice.