Patent ID: 11920474
Assignee: CHINA RAILWAY 16TH BUREAU GROUP BEIJING JIANGONG MACHINERY CO., LTD.
Field: Civil engineering (Other fields)
Classification: CPC E | IPC E

Claim 5:
6. A construction method of rock burst prewarning protection system in non-contact tunnel construction comprising the protecting trolley according to claim 1, the method comprising following steps:
I) collecting traditional microseismic monitoring and geological prospecting data in a process of an existing tunnel excavation, determining positions with high rock burst frequency of different types of surrounding rock in different regions, and establishing a reference database;
II) taking physicochemical indexes and mechanical parameters of the surrounding rock as standard, and recording into the reference database; comparing and learning the temperature change acceleration and deformation change acceleration of surrounding rock with similar physicochemical indexes and mechanical parameters in the rock burst stage under same or similar environmental parameters via artificial intelligence learning, summarizing the rules of the temperature change and the deformation change of different surrounding rocks with same or similar physicochemical indexes in the rock burst, summarizing the rules of the temperature change and the deformation change of different surrounding rocks with same or similar mechanical parameters in the rock burst, classifying and regulating the data collected in the previous steps via artificial neural network algorithm, in addition, increasing the environment parameters such as environment temperature, environment humidity, altitude and the size of the tunnel excavating face, classifying and regulating the rules of the temperature change and deformation change of the surrounding rocks according to the surrounding rock types, environment temperatures, environment humidity, altitudes and the sizes of the tunnel excavating face respectively; after introducing the cost matrix to eliminate or weaken the adverse effects caused by the imbalance of sample categories, constructing a neural network model, training and optimizing the model, obtaining a tunnel rock burst prewarning model based on the reference database in Step I and the neural network model, inputting the multiparameter information in the area to be prewarned or the prewarning unit in the existing data into the established rock burst prewarning model, outputting the potential rock burst grade and the probability in the prewarning area via the calculation of the prewarning model;
III) obtaining the rock core in the area to be excavated via advanced geological drilling, conducting the isothermal triaxial test in the laboratory, determining the temperature change acceleration in the local temperature rapid rise stage of the surrounding rock during the rock burst foreshadow, testing and recording the temperature change acceleration when the local temperature of the surrounding rock rises during the rock burst foreshadow, inputting the above two variations into the reference data as reference; improving and forming a “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database; comparing and analyzing each rock burst data with new variables via artificial intelligence learning in Step II, and inputting to the “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database and the rock burst prewarning model via artificial neural network algorithm in Step II;
IV) in the tunnel excavating process, the protecting trolley is additionally equipped with a plurality of highly sensitive laser sensors used for detecting the surrounding rock deformation and thermosensitive infrared sensors used for detecting the surrounding rock temperature change, as well as an acousto-optic alarming system for alarming, the monitoring area of all thermosensitive infrared sensors comprehensively covers the surrounding rocks inside the excavating tunnel, the highly sensitive laser sensor can monitor each point in the area where rock burst may occur, the rock burst prewarning model is updated in real time with the tunnel excavation and the passage of time, so as to update the prewarning results in real time, after prewarning of the rock burst on site, verifying whether the prewarning results are consistent with the actual situation on site, taking this rock burst and the corresponding monitoring information as new sample to dynamically supplement and update the “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database, continuously optimizing the rock burst prewarning model;
V) during tunnel excavating, the protecting trolley moves with the excavation, and the thermosensitive infrared sensor monitors the area where rock burst occurs, when the abnormal temperature change in some area is found to approach to the reference value in the “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database, the highly sensitive sensor turns to this area and monitors the surrounding rock deformation in this area, and the testing result is compared with the reference in the “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database in real time, quickly processing and comparing the threshold information of rock burst deformation or rock burst temperature in the pre-built-in “surrounding rock mechanical parameter-rock burst critical deformation-rock burst critical temperature” database by using the self-contained simple microcomputers of the thermosensitive infrared sensor and highly sensitive laser sensor, the rock burst prewarning model also receives this real time information and gives a feedback, when the data detected by either of the thermosensitive infrared sensor or highly sensitive laser sensor matches the reference data in the database, or when the rock burst prewarning model receives the data and gives a feedback of dangerous signal, the acousto-optic alarming system can give an alarm to warn the working personnel.