Real-time assessment method of coal seam impact risk based on vibration monitoring technology

Abstract

The invention discloses a real-time assessment method of coal seam impact risk based on vibration monitoring technology, which mainly collects the horizontal and vertical vibration signals of the drilling rig and the cuttings volume data synchronously while drilling the coal body as sample data, and establishes a multivariate linear Regression model, neural network model and optimized neural network prediction model, the vibration signal is used as the input of the prediction model, and the amount of drilling cuttings is used as the output, and the optimal model is selected as the final prediction model and automatically updated to the mobile terminal of the construction site and the ground The computer terminal, when performing daily impact risk assessment on coal seams, uses the final prediction model to automatically analyze the drilling vibration signals collected from the pre-assessed coal body, so as to assess the impact risk of the coal body; The invention reduces the work of collecting drilling cuttings, greatly simplifies the impact risk assessment procedure of the coal body, and shortens the assessment time.

Description

technical field [0001] The invention relates to the field of rock burst evaluation in mining engineering, in particular to a method for real-time evaluation of coal seam burst risk based on vibration monitoring technology. Background technique [0002] From the perspective of energy demand, my country's coal-based energy structure will not change in a short period of time, the proportion of coal will remain at about 50% for a long time, and about 95% of coal mining is dominated by underground mining. At present, coal mining extends to the deep at a rate of 10-20m per year. Deep mining has gradually become the norm in the central and eastern regions. With the increase of mining depth, coal seams are faced with high gas, high geostress, and high karst water pressure. The stress field of the coal seam is extremely complex and affected by repeated disturbances, so it is very prone to rock burst. After years of development in our country's rock burst disaster prevention technolo...

AI Technical Summary

Problems solved by technology

Compared with the traditional cuttings method, this method is different in that the auxiliary parameters in the cuttings method (suction drill, drill sticking and drilling impact phenomenon) are digitized, which improves the accuracy of rock burst prediction to a certain extent, but When predicting rock burst, it is still necessary to collect the amount of pulverized coal for each borehole. For each mining face or excavation face, hundreds or even thousands of boreholes need to be drilled. The work greatly reduces the efficiency of rock burst prediction. In addition, due to the manual processing of vibration data, the processing results have large errors, low efficiency, and poor timeliness.

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