Machine jamming risk early warning method and system in flood discharge tunnel TBM tunneling process

Abstract

The invention relates to the technical field of tunnel construction, in particular to a jamming risk early warning method and system for a flood discharge tunnel TBM tunneling process, and the method comprises the steps: building a lithology-tunneling model based on lithology parameter data and tunneling parameter data; dividing the end of the flood discharge tunnel to be tunneled based on the matching degree of the lithology comprehensive parameters of the flood discharge tunnel to be tunneled and the lithology-tunneling model; reducing the rotating speed of the cutterhead or increasing the inclination angle of the cutterhead based on the difference between the expansion rate and the expansion rate threshold; establishing a jamming risk early warning adjustment model based on the plurality of tunneling parameters before and after adjustment and the surrounding rock deformation values, and determining an early warning threshold correction coefficient; determining whether to monitor the fluctuation of the pore distribution of the surrounding rock based on the porosity of the surrounding rock so as to optimize the early warning threshold correction coefficient according to the correction coefficient optimization value; and reducing the surrounding rock deformation threshold value based on the correction coefficient optimization value. According to the invention, the accuracy of machine jamming risk early warning is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel construction, and in particular to a method and system for early warning of machine jam risk during a TBM excavation process in a flood discharge tunnel. Background Art

[0002] The full-face hard rock tunnel boring machine (TBM) is a large-scale tunnel construction equipment widely used in tunnel projects. TBM has the advantages of fast excavation speed and high comprehensive benefits, but its application under complex geological conditions also faces many challenges, especially the early warning and handling of machine jam risks. With the increasing number of long-distance, deep-buried and complex geological tunnel projects, machine jams are prone to occur due to complex geological conditions, unstable surrounding rock or improper equipment operation. That is, the cutterhead or shield is stuck and cannot be advanced normally. The machine jam phenomenon will not only cause construction delays, but also cause huge economic losses.

[0003] Chinese patent application publication number: CN111915193A discloses a TBM real-time tunneling stuck risk warning method, including the following steps: setting a tunneling termination length judgment value and an effective tunneling length judgment value, and setting the effective tunneling data sequence to empty; collecting tunneling data; judging the effective tunneling state of TBM tunneling according to the collected tunneling data; when the TBM tunneling is in the effective tunneling state, judging the effective tunneling point of the tunneling data; when the TBM tunneling is in the invalid tunneling state, judging the invalid tunneling point; adding the tunneling data of the tunneling point to the effective tunneling data sequence, and calculating the length of the effective tunneling data sequence; if it is a valid tunneling point, comparing the length of the effective tunneling data sequence with the effective tunneling length judgment value; calculating the final value of the stuck machine index according to the tunneling data in the effective tunneling data sequence; judging and displaying the risk level of the stuck machine.

[0004] However, the following problems exist in the prior art: the prior art calculates the final value of the stuck machine index by calculating the excavation data in the effective excavation data sequence to warn of the stuck machine risk, but does not fully analyze the complex geological conditions, resulting in the early warning model's insufficient ability to identify complex geological key risks, thereby causing the problem of low accuracy in the stuck machine risk warning. Summary of the invention

[0005] To this end, the present invention provides a method and system for early warning of machine jam risk during TBM excavation in a flood discharge tunnel, so as to overcome the problem in the prior art that complex geological conditions are not fully analyzed, resulting in insufficient ability of the early warning model to identify key risks of complex geology, and thus low accuracy of early warning of machine jam risk.

[0006] To achieve the above object, the present invention provides a method for early warning of machine jam risk during TBM excavation in a flood discharge tunnel, comprising:

[0007] Obtain lithology parameter data and excavation parameter data of several flood discharge tunnels that have completed excavation and have no risk of jamming, so as to establish a lithology-excavation model;

[0008] Acquire real-time lithology parameter data of the flood discharge tunnel to be excavated, and divide the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model;

[0009] Determine the early warning strategy for the risk of machine jamming based on the deformation value of the surrounding rock in the risk section of machine jamming, including monitoring the expansion rate and / or porosity of the surrounding rock in the risk section of machine jamming that has been excavated;

[0010] Determine whether the corresponding machine jam risk warning strategy is qualified based on the expansion rate, and determine the adjustment method of reducing the cutter disc rotation speed or increasing the cutter disc inclination angle according to the difference between the expansion rate and the expansion rate threshold;

[0011] Based on several excavation parameters and surrounding rock deformation values ​​before and after adjustment, a machine jam risk warning adjustment model is established, and the warning threshold correction coefficient is determined;

[0012] Determining whether to monitor the fluctuation of the pore distribution of the surrounding rock based on the porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value;

[0013] The eligibility of the machine jam risk warning strategy division is determined based on the deformation change rate of the machine jam risk section, so as to reduce the surrounding rock deformation threshold according to the optimized value of the correction coefficient.

[0014] Furthermore, based on the comparison result that the real-time lithology parameter data of the flood discharge tunnel to be excavated and the matching degree of the lithology-excavation model is less than the preset matching degree, the section of the flood discharge tunnel to be excavated is determined to be the risk section of the machine getting stuck, and based on the comparison result that the surrounding rock deformation value of the risk section of the machine getting stuck is less than or equal to the surrounding rock deformation threshold, the expansion rate of the surrounding rock of the excavated risk section of the machine getting stuck is monitored.

[0015] Furthermore, based on the comparison result that the surrounding rock deformation value of the machine-stuck risk section is greater than the surrounding rock deformation threshold, the expansion rate and porosity of the surrounding rock of the excavated machine-stuck risk section are monitored.

[0016] Further, under the condition of monitoring the expansion rate of the surrounding rock of the excavated machine stuck risk section, it is determined that the corresponding machine stuck risk warning strategy is unqualified based on the comparison result that the expansion rate is greater than the expansion rate threshold.

[0017] Further, based on the comparison result that the difference between the expansion rate and the expansion rate threshold is less than or equal to the preset difference, it is determined to reduce the cutter disc rotation speed by the preset rotation speed adjustment coefficient.

[0018] Further, based on the comparison result that the difference between the expansion rate and the expansion rate threshold is greater than the preset difference, it is determined that the cutter disc inclination angle is increased by a preset cutter disc inclination angle adjustment coefficient.

[0019] Furthermore, based on the comparison result that the porosity of the surrounding rock is greater than the preset porosity, the fluctuation of the monitored pore distribution is determined, and the warning threshold correction coefficient is optimized according to the surrounding rock movement direction vector to obtain the correction coefficient optimization value.

[0020] Furthermore, based on the comparison result that the deformation change rate of the stuck machine risk section is greater than the preset deformation change rate, it is determined that the stuck machine risk warning strategy classification is unqualified, and based on the comparison result that the correction coefficient optimization value is less than or equal to the preset correction coefficient optimization value, it is determined to reduce the surrounding rock deformation threshold with the first preset correction adjustment coefficient.

[0021] Furthermore, based on the comparison result that the optimized value of the correction coefficient is greater than the optimized value of the preset correction coefficient, it is determined that the surrounding rock deformation threshold is reduced by a second preset correction adjustment coefficient.

[0022] On the other hand, the present invention also provides a machine jam risk warning system during TBM excavation of a flood discharge tunnel, comprising:

[0023] A data acquisition module, which is used to obtain lithology parameter data and excavation parameter data of several flood discharge tunnels that have been excavated and have no risk of jamming, and to collect real-time lithology parameter data of the flood discharge tunnels to be excavated;

[0024] A model building module, connected to the data acquisition module, for building a lithology-excavation model based on the lithology parameter data and the excavation parameter data;

[0025] A risk division module, which is connected to the data acquisition module and the model building module respectively, and is used to divide the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model;

[0026] A strategy division module, which is connected to the risk division module, is used to determine a machine jam risk warning strategy based on the surrounding rock deformation value of the machine jam risk section, including monitoring the expansion rate or expansion rate and porosity of the surrounding rock of the excavated machine jam risk section;

[0027] a parameter adjustment module, connected to the strategy division module, for determining whether to reduce the cutter head rotation speed or increase the cutter head inclination angle based on the difference between the expansion rate and the expansion rate threshold;

[0028] An adjustment model building module, which is connected to the parameter adjustment module, is used to establish a machine jam risk warning adjustment model based on a number of excavation parameters and surrounding rock deformation values ​​before and after adjustment, and determine a warning threshold correction coefficient;

[0029] A correction coefficient optimization module, which is connected to the adjustment model building module, is used to determine whether to monitor the fluctuation of the surrounding rock pore distribution based on the surrounding rock porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value;

[0030] A threshold adjustment module is connected to the correction coefficient optimization module and the strategy division module respectively, and is used to determine a threshold value for reducing the surrounding rock deformation based on the correction coefficient optimization value.

[0031] Compared with the prior art, the beneficial effect of the present invention lies in that, by establishing a lithology-excavation model, and dividing the jamming risk sections of the flood discharge tunnel according to real-time lithology parameters, a TBM jamming risk warning strategy is formulated for the jamming risk sections, a jamming risk warning adjustment model is established after adjusting the TBM excavation parameters, and the warning threshold is corrected after evaluating the eligibility of the warning strategy, thereby reducing the jamming risk and improving the excavation efficiency. By correcting the warning threshold, the adaptability and accuracy of the model are improved, thereby improving the warning accuracy of the jamming risk during TBM excavation.

[0032] Furthermore, the present invention constructs a lithology-tunneling model, uses real-time lithology parameter data to input the model to obtain the initial TBM tunneling parameters, and divides the tunnels to be tunneled according to the degree of matching, thereby improving data quality and model accuracy, enhancing the stability and predictive ability of the model, and improving tunneling efficiency, thereby improving the accurate early warning of the risk of machine jams.

[0033] Furthermore, the present invention divides the risk of machine jamming in the flood discharge tunnel section being excavated, adopts corresponding TBM excavation parameters for excavation, and adopts different risk warning strategies in the machine jam risk section according to the surrounding rock deformation value, thereby reducing construction risks, optimizing excavation efficiency, reducing unnecessary downtime, and improving construction efficiency.

[0034] Furthermore, the present invention adjusts TBM excavation parameters by the difference between the surrounding rock expansion rate and the expansion rate threshold, establishes a machine jam risk warning adjustment model, and obtains the warning threshold correction coefficient, adjusts the excavation parameters in real time, reduces the machine jam risk, and improves the safety and efficiency of TBM excavation.

[0035] Furthermore, the present invention determines whether to monitor pore distribution fluctuations based on the porosity of the surrounding rock and determines the fluctuation value, thereby optimizing the warning threshold correction coefficient, accurately evaluating the stability of the surrounding rock, and improving the accuracy of risk warning during TBM excavation by adjusting the warning threshold.

[0036] Furthermore, the present invention establishes a machine stuck risk warning adjustment model by adjusting the surrounding rock deformation value after the initial TBM excavation parameters, and determines the warning threshold correction coefficient to adjust the surrounding rock deformation threshold, dynamically adjusts the TBM excavation parameters, improves the accuracy and effectiveness of the machine stuck risk warning strategy, reduces the machine stuck risk during the excavation process, and thus improves the accuracy of the warning for the machine stuck risk. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1It is a flow chart of a method for early warning of machine jam risk during TBM excavation of a flood discharge tunnel according to an embodiment of the present invention;

[0038] Figure 2 It is a structural schematic diagram of a machine jam risk warning system during TBM excavation of a flood discharge tunnel according to an embodiment of the present invention;

[0039] Figure 3 A flow chart for determining the division of flood discharge tunnel sections to be excavated for an embodiment of the present invention;

[0040] Figure 4 The present invention is a flowchart for determining the eligibility of the TBM card machine risk warning strategy classification according to an embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0042] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0043] It should be pointed out that the data in this embodiment are obtained by comprehensive analysis and evaluation of the historical test data and the corresponding historical test results of the present invention in the three months before this test. It can be understood by those skilled in the art that the present invention can determine the above parameters for a single item by selecting the highest proportion of values ​​as the preset standard parameters according to the data distribution, using weighted summation to use the obtained values ​​as the preset standard parameters, substituting each historical data into a specific formula and using the values ​​obtained by the formula as the preset standard parameters or other selection methods, as long as the present invention can clearly define different specific situations in the single determination process through the obtained values.

[0044] See also Figure 1 The flowchart of the early warning method for the risk of machine jam during TBM excavation of flood discharge tunnel is shown in the figure.

[0045] The embodiment of the present invention provides a method for early warning of machine jam risk during TBM excavation in a flood discharge tunnel, including:

[0046] Step S1, obtaining lithology parameter data and excavation parameter data of a number of flood discharge tunnels that have completed excavation and have no risk of jamming, so as to establish a lithology-excavation model;

[0047] Step S2, acquiring real-time lithology parameter data of the flood discharge tunnel to be excavated, and dividing the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model;

[0048] Step S3, determining a machine-stuck risk warning strategy based on the surrounding rock deformation value of the machine-stuck risk section, including monitoring the expansion rate and / or porosity of the surrounding rock of the excavated machine-stuck risk section;

[0049] Step S4 determines whether the corresponding machine jam risk warning strategy is qualified based on the expansion rate, so as to determine an adjustment method of reducing the cutter disc speed or increasing the cutter disc inclination angle according to the difference between the expansion rate and the expansion rate threshold;

[0050] Step S5, establishing a machine jam risk warning adjustment model based on a number of excavation parameters and surrounding rock deformation values ​​before and after adjustment, and determining a warning threshold correction coefficient;

[0051] Step S6, determining whether to monitor the fluctuation of the pore distribution of the surrounding rock based on the porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value;

[0052] Step S7, determining the eligibility of the machine jam risk warning strategy division based on the deformation change rate of the machine jam risk section, so as to reduce the surrounding rock deformation threshold according to the correction coefficient optimization value.

[0053] In the embodiment of the present invention, the rock property parameter data includes but is not limited to the uniaxial compressive strength, tensile strength, elastic modulus, surrounding rock volume, surrounding rock volume and surrounding rock stress.

[0054] In the embodiment of the present invention, the TBM excavation parameter data includes but is not limited to cutter head rotation speed, cutter head thrust, cutter head torque, cutter head rotation speed, penetration and cutter head inclination.

[0055] See also Figure 2 The structural diagram of the machine jam risk warning system during the TBM excavation process of the flood discharge tunnel is shown in the figure.

[0056] On the other hand, the present invention also provides a machine jam risk warning system during TBM excavation of a flood discharge tunnel, comprising:

[0057] A data acquisition module, which is used to obtain lithology parameter data and excavation parameter data of several flood discharge tunnels that have been excavated and have no risk of jamming, and to collect real-time lithology parameter data of the flood discharge tunnels to be excavated;

[0058] A model building module, connected to the data acquisition module, for building a lithology-excavation model based on the lithology parameter data and the excavation parameter data;

[0059] A risk division module, which is connected to the data acquisition module and the model building module respectively, and is used to divide the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model;

[0060] A strategy division module, which is connected to the risk division module, is used to determine a machine jam risk warning strategy based on the surrounding rock deformation value of the machine jam risk section, including monitoring the expansion rate or expansion rate and porosity of the surrounding rock of the excavated machine jam risk section;

[0061] a parameter adjustment module, connected to the strategy division module, for determining whether to reduce the cutter head rotation speed or increase the cutter head inclination angle based on the difference between the expansion rate and the expansion rate threshold;

[0062] An adjustment model building module, which is connected to the parameter adjustment module, is used to establish a machine jam risk warning adjustment model based on a number of excavation parameters and surrounding rock deformation values ​​before and after adjustment, and determine a warning threshold correction coefficient;

[0063] A correction coefficient optimization module, which is connected to the adjustment model building module, is used to determine whether to monitor the fluctuation of the surrounding rock pore distribution based on the surrounding rock porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value;

[0064] A threshold adjustment module is connected to the correction coefficient optimization module and the strategy division module respectively, and is used to determine a threshold value for reducing the surrounding rock deformation based on the correction coefficient optimization value.

[0065] Specifically, the present invention establishes a lithology-excavation model, divides the jamming risk sections of the flood discharge tunnel according to real-time lithology parameters, formulates a TBM jamming risk warning strategy for the jamming risk sections, establishes a jamming risk warning adjustment model after adjusting the TBM excavation parameters, and corrects the warning threshold after evaluating the eligibility of the warning strategy, thereby reducing the jamming risk and improving the excavation efficiency. The warning threshold is corrected, the adaptability and accuracy of the model are improved, and thus the warning accuracy of the jamming risk during TBM excavation is improved.

[0066] Specifically, after obtaining the lithology parameter data and TBM excavation parameter data of several flood discharge tunnels excavated by the same TBM, the embodiment of the present invention performs data preprocessing on the lithology parameter data and the TBM excavation parameter data, processes the two types of data using linear interpolation, and then uses Z-score normalization processing on the lithology parameter data and Min-Max normalization processing on the TBM excavation parameter data, and uses a random forest regression model as a model of the lithology-excavation model architecture.

[0067] Specifically, real-time lithology parameter data of the flood discharge tunnel to be excavated are obtained, and the real-time lithology parameter data are input into the lithology-excavation model to obtain the initial excavation parameters of the TBM. The initial excavation parameters of the TBM are set to a cutterhead speed of 45 mm / min, a cutterhead torque of 1800 kN·m, a cutterhead speed of 5 rpm, a penetration of 12 mm / rev, and a cutterhead inclination of 2.5°.

[0068] In the embodiment of the present invention, the real-time lithology parameter data is acquired in real time, including but not limited to uniaxial compressive strength, tensile strength, porosity, volume and length of surrounding rock.

[0069] In the embodiment of the present invention, the real-time lithology parameter data is obtained by disposing fiber grating sensors inside the surrounding rock and utilizing fiber grating sensing technology.

[0070] Specifically, the embodiment of the present invention divides the flood discharge tunnel to be excavated into several sections according to the matching degree between the real-time lithology parameter data and the lithology-excavation model. The embodiment of the present invention sets the section length of the flood discharge tunnel to be excavated to 10m / section, and the number of sections is the ratio of the total length of the flood discharge tunnel to be excavated to the section length.

[0071] See also Figure 3 The flow chart for determining the division of flood discharge tunnel sections to be excavated is shown in the figure.

[0072] Specifically, the embodiment of the present invention determines the division of the flood discharge tunnel section to be excavated according to the comparison result of the real-time lithology parameter data of the flood discharge tunnel to be excavated and the matching degree of the lithology-excavation model with the preset matching degree of 0.85;

[0073] When the matching degree is less than the preset matching degree, it is determined that the flood discharge tunnel section to be excavated is divided into a machine jam risk section;

[0074] When the matching degree is greater than or equal to the preset matching degree, it is determined that the flood discharge tunnel section to be excavated is divided into a non-stuck machine risk section.

[0075] In the embodiment of the present invention, the preset matching degree is 0.85, and the preset matching degree is obtained by taking the average matching degree of several historical non-card machine risk segments, but the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0076] Specifically, the embodiment of the present invention calculates the matching degree according to the following formula, setting:

[0077]

[0078] Among them, P represents the matching degree, n is the number of lithology parameter data, X m is the value of the mth real-time lithology parameter, Y m is the value of the lithology parameter in the mth lithology-tunneling model, σ m is the standard deviation of the mth lithological parameter data.

[0079] Specifically, the present invention constructs a lithology-excavation model, uses real-time lithology parameter data to input the model to obtain the initial excavation parameters of the TBM, and divides the tunnels to be excavated according to the degree of matching, thereby improving the data quality and model accuracy, enhancing the stability and predictive ability of the model, and improving the excavation efficiency, thereby improving the accurate early warning of the risk of machine jams.

[0080] Specifically, under the condition that the flood discharge tunnel section to be excavated is determined to be divided into a non-stuck machine risk section, the embodiment of the present invention excavates the flood discharge tunnel section to be excavated according to the TBM initial excavation parameters determined by the lithology-excavation model.

[0081] Specifically, under the condition that the flood discharge tunnel section to be excavated is determined to be a TBM stuck risk section, the embodiment of the present invention determines a TBM stuck risk warning strategy according to the comparison result of the surrounding rock deformation value of the TBM stuck risk section with the surrounding rock deformation threshold of 1.5%;

[0082] When the surrounding rock deformation value is less than or equal to the surrounding rock deformation threshold, the expansion rate of the surrounding rock in the risk section of the excavated machine stuck is determined;

[0083] When the surrounding rock deformation value is greater than the surrounding rock deformation threshold, the expansion rate and porosity of the surrounding rock in the risk section of the excavated machine being stuck are determined and monitored.

[0084] In the embodiment of the present invention, the surrounding rock deformation threshold is 1.5%, which is the maximum value of the surrounding rock deformation values ​​of several non-risk sections of the machine jam, but the above value is not limited to this, and technicians in this field can also adjust the value according to actual needs.

[0085] In an embodiment of the present invention, the surrounding rock deformation value is the deformation rate of the surrounding rock volume of the TBM stuck risk section before excavation and the surrounding rock volume of the TBM stuck risk section after excavation; in the specific implementation process, the surrounding rock volume is obtained by fiber optic Bragg grating sensing technology, and the absolute difference between the surrounding rock volume before and after excavation and the percentage of the surrounding rock volume before excavation are calculated to determine the deformation rate of the surrounding rock volume.

[0086] In specific implementation, the surrounding rock deformation value can be calculated according to the following formula:

[0087]

[0088] Among them, Q represents the deformation value of surrounding rock, V 0 V is the initial surrounding rock volume before excavation of the risk section of the machine jam, r It is the volume of surrounding rock after excavation.

[0089] Specifically, the embodiment of the present invention determines whether the corresponding TBM stuck risk warning strategy is qualified according to the comparison result between the expansion rate and the expansion rate threshold under the condition of monitoring the expansion rate of the surrounding rock of the excavated machine stuck risk section;

[0090] When the expansion rate is less than or equal to the expansion rate threshold, it is determined that the corresponding TBM machine jam risk warning strategy is qualified;

[0091] When the expansion rate is greater than the expansion rate threshold, it is determined that the corresponding TBM jam risk warning strategy is unqualified.

[0092] In the embodiment of the present invention, the expansion rate threshold is 0.8%, which is obtained by taking the average of the expansion rates of several historical card machine risk warning strategies that are qualified. However, the above value is not limited to this, and those skilled in the art can also adjust the value according to actual needs.

[0093] In an embodiment of the present invention, the expansion rate is the rate of change of the surrounding rock length of the risk section of the TBM getting stuck before excavation and the surrounding rock length of the risk section of the TBM getting stuck after excavation; in the specific implementation process, the surrounding rock length is obtained by fiber optic Bragg grating sensing technology, and the absolute difference between the surrounding rock length before and after excavation and the percentage of the surrounding rock length before excavation are calculated to determine the deformation rate of the surrounding rock volume.

[0094] In specific implementation, the expansion rate can be calculated according to the following formula:

[0095]

[0096] Among them, Z represents the expansion rate, L 0 is the initial surrounding rock length before excavation of the risk section of the machine jam, L t It is the length of surrounding rock after excavation.

[0097] Specifically, the present invention divides the risk of machine jamming in the flood discharge tunnel section being excavated, adopts corresponding TBM excavation parameters for excavation, and adopts different risk warning strategies in the machine jam risk section according to the surrounding rock deformation value, thereby reducing construction risks, optimizing excavation efficiency, reducing unnecessary downtime, and improving construction efficiency.

[0098] It can be understood that, under the condition that the TBM stuck risk warning strategy for monitoring the expansion rate of the surrounding rock of the risky section of the stuck machine that has been excavated is qualified, this warning strategy is applied to the excavation process of the flood discharge tunnel to be excavated.

[0099] Specifically, under the condition that the TBM stuck risk warning strategy for monitoring the expansion rate of the surrounding rock of the excavated stuck risk section is determined to be unqualified, the embodiment of the present invention determines to adjust the TBM initial excavation parameters according to the comparison result of the difference between the expansion rate and the expansion rate threshold and the preset difference of 0.2%;

[0100] When the difference is less than or equal to the preset difference, it is determined to reduce the TBM cutter head speed to a corresponding value by a preset speed adjustment coefficient of 0.95;

[0101] When the difference is greater than the preset difference, it is determined that the TBM cutter head inclination angle is increased to a corresponding value by using a preset cutter head inclination angle adjustment coefficient of 1.05;

[0102] The difference is a difference between the expansion rate and the expansion rate threshold.

[0103] In the embodiment of the present invention, the preset difference value is 0.2%, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0104] In the embodiment of the present invention, the reduced cutter disc speed is the product of the cutter disc speed and a preset speed adjustment coefficient of 0.95; the increased cutter disc inclination angle is the product of the cutter disc inclination angle and a preset cutter disc inclination angle adjustment coefficient of 1.05.

[0105] Specifically, the surrounding rock deformation values ​​after adjusting the initial TBM excavation parameters are collected, and a machine stuck risk warning adjustment model is established based on several TBM excavation parameters and surrounding rock deformation values ​​before and after the adjustments. The establishment process of the machine stuck risk warning adjustment model is the same as the establishment process of the lithology-excavation model, and the above process will not be repeated here.

[0106] Specifically, under the condition of determining to establish a machine jam risk warning adjustment model, the embodiment of the present invention can calculate the warning threshold correction coefficient according to the ratio of the cutter disc inclination angle after adjustment to the cutter disc inclination angle before adjustment, multiplied by the ratio of the cutter disc speed after adjustment to the cutter disc speed before adjustment, and then multiplied by the ratio of the surrounding rock deformation value after adjustment to the surrounding rock deformation value before adjustment.

[0107] Specifically, the present invention adjusts TBM excavation parameters through the difference between the surrounding rock expansion rate and the expansion rate threshold, establishes a machine jam risk warning adjustment model, and obtains the warning threshold correction coefficient, adjusts the excavation parameters in real time, reduces the risk of machine jam, and improves the safety and efficiency of TBM excavation.

[0108] Specifically, the embodiment of the present invention determines whether to monitor the fluctuation of the porosity distribution of the surrounding rock based on the comparison result between the porosity and the preset porosity of 10%, under the condition of determining the expansion rate and porosity of the surrounding rock of the risk section of the excavated machine stuck.

[0109] When the porosity is less than or equal to the preset porosity, it is determined that the fluctuation of the pore distribution is not monitored;

[0110] When the porosity is greater than the preset porosity, it is determined to monitor the fluctuation of the pore distribution.

[0111] In the embodiment of the present invention, the preset porosity value is 10%, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0112] Specifically, under the condition that it is determined not to monitor the fluctuation of pore distribution, there is no need to further optimize the correction coefficient of the warning threshold.

[0113] Specifically, the embodiment of the present invention determines the fluctuation value according to the fluctuation of the pore distribution under the condition of determining the fluctuation of the pore distribution to be monitored; in the specific implementation process, the standard deviation of several porosities is calculated by the degree of dispersion of the porosity distributed on the surrounding rock to determine the fluctuation value.

[0114] Specifically, under the condition of determining the fluctuation value, the embodiment of the present invention determines the influence range of the fluctuation value on the pore distribution change of the surrounding rock with the center of mass of the cutterhead as the center of the sphere; in the specific implementation process, the determination of the influence range is based on the semivariogram model, and the fitting parameters of the semivariogram model are related to the fluctuation value. The larger the fluctuation value and the larger the fitting parameters, the larger the radius of the influence range.

[0115] Specifically, under the condition of determining the influence range of the fluctuation value on the pore distribution change of the surrounding rock, the embodiment of the present invention determines the length of the surrounding rock movement direction vector according to the change of the lithological parameters and the expansion rate within the influence range. In specific implementation, the product of the direction vector length of the lithological parameters in the influence range and the direction vector length of the expansion rate in the influence range is calculated to obtain the length of the surrounding rock movement direction vector.

[0116] Specifically, under the condition of obtaining the length of the surrounding rock movement direction vector, the warning threshold correction coefficient is optimized according to the surrounding rock movement direction vector to obtain the optimized value of the correction coefficient. In the specific implementation, the ratio of the mean length of the surrounding rock movement direction vector to the maximum length of the surrounding rock movement direction vector is calculated to obtain the optimized value of the correction coefficient.

[0117] Specifically, the present invention determines whether to monitor pore distribution fluctuations based on the porosity of the surrounding rock and determines the fluctuation value, thereby optimizing the warning threshold correction coefficient, accurately evaluating the stability of the surrounding rock, and improving the accuracy of risk warning during TBM excavation by adjusting the warning threshold.

[0118] See also Figure 4 The flowchart for determining the eligibility of the TBM machine risk warning strategy classification is shown in the figure.

[0119] Specifically, under the condition of determining the optimal value of the correction coefficient, the embodiment of the present invention determines the eligibility of the TBM machine risk warning strategy division according to the comparison result of the deformation change rate of the risk segment of the machine and the preset deformation change rate of 0.3%;

[0120] When the deformation change rate is less than or equal to the preset deformation change rate, it is determined that the TBM jam risk warning strategy classification is qualified;

[0121] When the deformation change rate is greater than the preset deformation change rate, it is determined that the TBM jam risk warning strategy classification is unqualified.

[0122] In an embodiment of the present invention, the preset deformation change rate is 0.3%, and the preset deformation change rate is obtained by taking the average value of the deformation change rates that are qualified according to several historical card machine risk warning strategies. However, the above value is not limited to this, and technical personnel in this field can also adjust the value according to actual needs.

[0123] Specifically, the embodiment of the present invention calculates the deformation change rate according to the following formula, setting:

[0124]

[0125] Among them, S represents the deformation change rate, Q is the surrounding rock deformation value, and Q t is the surrounding rock deformation value at the tth time, and t is set to 10min.

[0126] Specifically, in the embodiment of the present invention, under the condition that the TBM jam risk warning strategy classification is determined to be unqualified, the surrounding rock deformation threshold is determined to be adjusted according to the comparison result between the correction coefficient optimization value and the preset correction coefficient optimization value;

[0127] When the correction coefficient optimization value is less than or equal to the preset correction coefficient optimization value, it is determined to reduce the surrounding rock deformation threshold to a corresponding value using a first preset correction adjustment coefficient of 0.97;

[0128] When the correction coefficient optimization value is greater than the preset correction coefficient optimization value, it is determined that the surrounding rock deformation threshold is reduced to a corresponding value using a second preset correction adjustment coefficient of 0.94.

[0129] In the embodiment of the present invention, the preset optimization value of the correction coefficient is 0.68, but the above value is not limited thereto, and those skilled in the art may also adjust the value according to actual needs.

[0130] In the embodiment of the present invention, the reduced surrounding rock deformation threshold is the product of the surrounding rock deformation threshold and the kth preset correction adjustment coefficient, where k is 1 or 2, G1 is the first preset correction adjustment coefficient 0.97, and G2 is the second preset correction adjustment coefficient 0.94.

[0131] Specifically, the present invention judges the eligibility of the TBM stuck risk warning strategy through the deformation change rate. When it is unqualified, the surrounding rock deformation threshold is adjusted according to the optimized value of the correction coefficient. The deformation change rate is monitored in real time and the warning strategy is adjusted. This improves the risk warning accuracy during TBM excavation. The surrounding rock deformation threshold is adjusted according to the optimized value of the correction coefficient, which reduces the risk of stuck machine, thereby improving the warning accuracy of the risk of stuck machine during TBM excavation.

[0132] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0133] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for early warning of machine jam risk during TBM excavation in a flood discharge tunnel, characterized in that: include: Obtain lithology parameter data and excavation parameter data of several flood discharge tunnels that have completed excavation and have no risk of jamming, so as to establish a lithology-excavation model; Acquire real-time lithology parameter data of the flood discharge tunnel to be excavated, and divide the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model; Determine the early warning strategy for the risk of machine jamming based on the deformation value of the surrounding rock in the risk section of machine jamming, including monitoring the expansion rate and / or porosity of the surrounding rock in the risk section of machine jamming that has been excavated; Determine whether the corresponding machine jam risk warning strategy is qualified based on the expansion rate, and determine the adjustment method of reducing the cutter disc rotation speed or increasing the cutter disc inclination angle according to the difference between the expansion rate and the expansion rate threshold; Based on several excavation parameters and surrounding rock deformation values ​​before and after adjustment, a machine jam risk warning adjustment model is established, and the warning threshold correction coefficient is determined; Determining whether to monitor the fluctuation of the pore distribution of the surrounding rock based on the porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value; The eligibility of the machine jam risk warning strategy division is determined based on the deformation change rate of the machine jam risk section, so as to reduce the surrounding rock deformation threshold according to the optimized value of the correction coefficient.

2. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 1, characterized in that: Based on the comparison result that the real-time lithology parameter data of the flood discharge tunnel to be excavated and the matching degree of the lithology-excavation model is less than the preset matching degree, the section of the flood discharge tunnel to be excavated is determined to be the risk section of the machine getting stuck, and based on the comparison result that the surrounding rock deformation value of the risk section of the machine getting stuck is less than or equal to the surrounding rock deformation threshold, the expansion rate of the surrounding rock of the excavated risk section of the machine getting stuck is monitored.

3. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 2, characterized in that: Based on the comparison result that the surrounding rock deformation value of the machine-stuck risk section is greater than the surrounding rock deformation threshold, the expansion rate and porosity of the surrounding rock of the excavated machine-stuck risk section are monitored.

4. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 2, characterized in that: Under the condition of monitoring the expansion rate of the surrounding rock of the excavated machine jam risk section, it is determined that the corresponding machine jam risk warning strategy is unqualified based on the comparison result that the expansion rate is greater than the expansion rate threshold.

5. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 4 is characterized in that: Based on the comparison result that the difference between the expansion rate and the expansion rate threshold is less than or equal to the preset difference, it is determined to reduce the cutter disc rotation speed by the preset rotation speed adjustment coefficient.

6. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 4, characterized in that: Based on the comparison result that the difference between the expansion rate and the expansion rate threshold is greater than the preset difference, it is determined to increase the cutter disc inclination angle by a preset cutter disc inclination angle adjustment coefficient.

7. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 3, characterized in that: The fluctuation of the monitored pore distribution is determined based on the comparison result that the porosity of the surrounding rock is greater than the preset porosity, and the correction coefficient of the warning threshold is optimized according to the moving direction vector of the surrounding rock to obtain the optimized value of the correction coefficient.

8. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 1, characterized in that: Based on the comparison result that the deformation change rate of the stuck machine risk section is greater than the preset deformation change rate, it is determined that the stuck machine risk warning strategy classification is unqualified, and based on the comparison result that the correction coefficient optimization value is less than or equal to the preset correction coefficient optimization value, it is determined to reduce the surrounding rock deformation threshold with the first preset correction adjustment coefficient.

9. The method for early warning of machine jam risk during TBM excavation of flood discharge tunnel according to claim 8, characterized in that: Based on the comparison result that the correction coefficient optimization value is greater than the preset correction coefficient optimization value, it is determined to reduce the surrounding rock deformation threshold by a second preset correction adjustment coefficient.

10. A machine jam risk warning system for a flood discharge tunnel TBM excavation process using any one of claims 1 to 9, characterized in that: include: A data acquisition module, which is used to obtain lithology parameter data and excavation parameter data of several flood discharge tunnels that have been excavated and have no risk of jamming, and to collect real-time lithology parameter data of the flood discharge tunnels to be excavated; A model building module, connected to the data acquisition module, for building a lithology-excavation model based on the lithology parameter data and the excavation parameter data; A risk division module, which is connected to the data acquisition module and the model building module respectively, and is used to divide the flood discharge tunnel sections to be excavated based on the matching degree between the real-time lithology parameter data and the lithology-excavation model; A strategy division module, which is connected to the risk division module, is used to determine a machine jam risk warning strategy based on the surrounding rock deformation value of the machine jam risk section, including monitoring the expansion rate or expansion rate and porosity of the surrounding rock of the excavated machine jam risk section; a parameter adjustment module, connected to the strategy division module, for determining whether to reduce the cutter head rotation speed or increase the cutter head inclination angle based on the difference between the expansion rate and the expansion rate threshold; An adjustment model building module, which is connected to the parameter adjustment module, is used to establish a machine jam risk warning adjustment model based on a number of excavation parameters and surrounding rock deformation values ​​before and after adjustment, and determine a warning threshold correction coefficient; A correction coefficient optimization module, which is connected to the adjustment model building module, is used to determine whether to monitor the fluctuation of the surrounding rock pore distribution based on the surrounding rock porosity, so as to optimize the correction coefficient of the early warning threshold according to the correction coefficient optimization value; A threshold adjustment module is connected to the correction coefficient optimization module and the strategy division module respectively, and is used to determine a threshold value for reducing the surrounding rock deformation based on the correction coefficient optimization value.

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