Rockburst risk assessment method under ill-conditioned conditions of tunnel microseismic sensor monitoring network

Abstract

The invention provides a rockburst risk assessment method under pathological conditions of tunnel microseismic sensor monitoring network, and relates to the technical field of rockburst risk assessment of deep buried tunnels. This method first establishes different rockburst databases according to rockburst levels; treats different levels of rockburst databases as different groups to calculate the covariance matrix and mean vector; then extracts and establishes the rockburst database in the microseismic monitoring system software within the same period of time. The number and amplitude of microseismic events are greater than 10 ‑4 m / s 2 The number of microseismic events is used as a sample; Mahalanobis distance is used to determine the distance between the sample and different groups; then the group with the smallest distance from the sample is the potential rockburst risk. The rockburst risk assessment method under the pathological conditions of the tunnel microseismic sensor provided by the present invention can evaluate the rockburst risk in the area near the tunnel face based on the existing microseismic information under the pathological conditions of the microseismic sensor, and solves the problem of less than 4 problems. The dilemma of rockburst risk assessment that cannot be performed by sensor work.

Description

technical field [0001] The invention relates to the technical field of rockburst risk assessment for deep-buried tunnels, in particular to a rockburst risk assessment method under the condition of tunnel microseismic sensor monitoring station network sickness. Background technique [0002] Rockburst is a complex dynamic geological disaster. It often causes catastrophic damage to underground engineering in the form of "sudden attack", which not only seriously threatens the safety of construction personnel and equipment, affects the construction progress, but also causes excessive underground engineering. Excavation, initial support failure, and even induced earthquakes in severe cases are one of the main disasters in deep tunnel engineering. Studies have shown that rockbursts are the product of the gradual failure process of rock mass, during which energy is released in the form of elastic waves, which are called microseisms. If the microseismic information is analyzed and p...

AI Technical Summary

Problems solved by technology

Due to the poor working environment and complicated construction in the tunnel, the microseismic sensors, microseismic data acquisition instruments and their lines are often easily damaged, and the actual number of sensors is often less than 4. The parameters of the microseismic source cannot be determined, resulting in the inability to identify Rockburst risk assessment poses a serious threat to tunnel safety construction

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