Coal seam impact risk real-time evaluation method based on vibration monitoring technology

Abstract

The invention discloses a coal seam impact risk real-time evaluation method based on a vibration monitoring technology. The method mainly comprises the following steps: while drilling a coal body, synchronously acquiring transverse and longitudinal vibration signals and drilling cutting quantity data of a drilling machine as sample data; establishing a multiple linear regression model, a neural network model and an optimized neural network prediction model; taking the vibration signal as the input of a prediction model; taking drilling quantity as output, comparing and selecting an optimal model as a final prediction model, and automatically updating the final prediction model to a field construction mobile terminal and an overground computer terminal; when daily impact risk assessment iscarried out on a coal seam, a final prediction model is utilized to automatically analyze a drilling vibration signal acquired from a pre-assessed coal body so as to carry out impact risk assessment on the coal body; according to the method, the collection work of the drilling cuttings is reduced, the impact risk evaluation procedure of the coal body is greatly simplified, and the evaluation timeis shortened.

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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