A method for evaluating rockburst hazard levels based on big data analysis

Abstract

The present invention relates to the technical field of tunnel risk prediction. The present invention discloses a method and system for predicting rockburst risk levels based on big data analysis, which includes step S1 of collecting and obtaining rock data, and according to the edge shape of the tunnel face Draw the first, second or n times of excavation shape with the ratio of B, and step S3 records the vibration data of the detection point farthest from the first excavation area of ​​the predicted detection point, and then when excavating the first excavation area, according to the distance of the predicted detection point Record the vibration data values ​​of the near point and the far point as A and A1 respectively; compare the mining values ​​of the N mining faces, and then compare the data with the data of rockbursts, and judge the face according to the similarity of the data The risk level in the mining process can be predicted in advance in the later stage. According to the prediction content, various methods can be used to compare the values ​​when mining the N times of mining faces, and then choose the optimal mining method for mining.

Description

technical field [0001] The invention relates to the technical field of tunnel hazard prediction, in particular to a method and system for evaluating rockburst hazard levels based on big data analysis. Background technique [0002] The reason for the rockburst is that the strain energy accumulated in the rock mass in the surrounding area is released suddenly and violently, resulting in a brittle fracture like an explosion in the rock mass. , because if some holes are opened on the air surface, the holes will inevitably affect the structural strength of the air surface, which may induce rockbursts in advance. If no holes are opened, the air surface will be in a closed state, which is not convenient detection. [0003] The existing rockburst prediction is mainly to open multiple holes on the face, and install micro-vibration probes inside the holes to detect the vibration of the rock, which can accurately predict the occurrence of rockbursts, but this method cannot Assess the...

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Problems solved by technology

[0002] The reason for the rockburst is that the strain energy accumulated in the rock mass in the surrounding area is released suddenly and violently, resulting in a brittle fracture like an explosion in the rock mass. , because if some holes are opened on the air surface, the holes will inevitably affect the structural strength of the air surface, which may induce rockbursts in advance. If no holes are opened, the air surface will be in a closed state, which is not convenient detection

[0003] The existing rockburst prediction is mainly to open multiple holes on the face, and install micro-vibration probes inside the holes to detect the vibration of the rock, which can accurately predict the occurrence of rockbursts, but this method cannot Assess the danger of rockbursts, because rockbursts may occur shortly after the vibration occurs. At this time, the notification after the vibration is abnormal makes the time too tight. With the advancement of the face, in fact, if the The traditional mining method has different effects due to different regional locations. For example, in the first progress, the stability of the rock is mined using this method, so that the strength between the rocks is affected by this processing method. There are fewer cracks, and the subsequent excavation At this time, there are many cracks, and there may be a potential danger of rockburst at this time, but when a micro-seismic event occurs, it will be a precursor to the danger of eruption. Therefore, if the danger of rockburst can be predicted, and then the danger can be remedied , can avoid many potential problems and further improve the safety of tunnel excavation

[0004] As a failure process, rockburst is the result of a large number of cracks that expand and grow later. Since the rock in the wall around the face cannot be detected, the risk of rockburst cannot be estimated through rock cracks.

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