TBM card machine risk comprehensive identification method

Abstract

The invention discloses a TBM card machine risk comprehensive identification method. The method comprises the following steps: S1, defining a TBM card machine risk level; s2, constructing a TBM card machine risk prediction system; s3, advanced judgment and identification of TBM card machine risks are carried out; s4, TBM card machine risk approaching identification is carried out; s5, drilling and coring; and S6, thrust and torque analysis. According to the method, a surrounding rock detection method for a long distance and a short distance is established, TBM jamming risk comprehensive judgment combining multiple modes of advanced geological forecast, tunneling parameter judgment, slag state judgment, drilling and coring judgment and escape critical state judgment is achieved, the number of times of drilling and coring development is reduced while the prediction precision is guaranteed, and the prediction efficiency is improved. The probability of misjudgment and missed judgment is reduced to the maximum extent, and the method has wide popularization value and remarkable economic and social benefits.

Description

Technical Field

[0001] The invention relates to the technical field of tunnel engineering, and in particular to a comprehensive risk identification method for a TBM stuck machine. Background Art

[0002] Although TBM has made significant progress in technology, methods and equipment in recent years, compared with the drilling and blasting method, which is more adaptable to complex geology, TBM still has higher requirements for geological conditions. In the process of tunnel construction, especially mountain tunnels, unfavorable geological conditions such as loose and weak surrounding rock, water-bearing sand strata, and broken rock areas are almost inevitable. In such a geological environment, excavation is more likely to cause surrounding rock damage or even collapse, and TBMs often cannot be freed due to problems such as insufficient thrust and cutterhead locking, resulting in shutdown. When TBM passes through broken strata, if advanced support is continuously used to reinforce the surrounding rock in front of the face, the risk of machine jam can be greatly reduced, but the cost will also increase significantly and the construction efficiency will be greatly reduced. Therefore, it is necessary to identify the risk of machine jam ahead during excavation, so as to take corresponding measures. The current TBM jam risk prediction method considers relatively single factors, which is prone to missed judgments and misjudgments. Summary of the invention

[0003] The purpose of the present invention is to provide a comprehensive identification method for the risk of TBM jamming in order to solve the above-mentioned problem. By combining advanced identification with proximity identification, the surrounding rock state and TBM excavation parameters are comprehensively considered to identify the risk of TBM jamming, which greatly improves the prediction accuracy and reduces the possibility of missed identification and misjudgment.

[0004] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0005] A comprehensive identification method for TBM jam risk, including:

[0006] Definition of TBM card machine risk level;

[0007] TBM card machine risk prediction system architecture;

[0008] Advanced identification of TBM jam risk, including horizontal sound profile (HSP) and seismic wave reflection (TSP);

[0009] Identification of the imminent risk of TBM jamming;

[0010] Drilling and coring;

[0011] Thrust and torque analysis.

[0012] Preferably: the specific steps are:

[0013] Step S1: First, perform a preliminary detection of the surrounding rock through HSP at a distant location. If the surrounding rock is not broken, no further advanced geological prediction is performed. However, the excavation parameters are still used to identify the risk of TBM jam to avoid missed judgments. If HSP detects that the surrounding rock is broken, further detection is performed through TSP to avoid misjudgment.

[0014] Step S2: If HSP does not detect surrounding rock crushing or TSP supplementary detection does not detect surrounding rock crushing, the risk of machine jamming is greatly reduced. However, during the excavation process, critical identification needs to be performed in real time based on the excavation parameters to avoid missed identification. If no warning information appears, it indicates that the risk is low and the excavator can pass directly. Otherwise, it is necessary to further determine the surrounding rock status through core drilling.

[0015] Step S3: If the results of the advanced geological prediction or the proximity identification of the tunneling parameters show that there is a medium or high risk, further verification is required through drilling. If the coring results show that the surrounding rock is not broken, the results are output to evaluate that there is a medium risk in the current section; if the coring results show that the surrounding rock is broken, the thrust and torque are verified according to the range of surrounding rock crushing.

[0016] Step S4: reserve a safety factor K. If the thrust and torque calculation results show that K times the maximum thrust and torque of the TBM when it passes through the broken zone does not exceed the maximum thrust and torque of the equipment, it is judged as medium risk, otherwise it is judged as high risk.

[0017] Preferred: TBM machine jam risk is divided into three levels:

[0018] (1) Low risk:

[0019] No action is required, you can pass directly;

[0020] (2) Medium risk:

[0021] The main driver can pass smoothly by relying on his experience, and there is no need to take advance support measures. However, the main driver needs to pay attention to adjusting the excavation parameters in real time and appropriately reduce the excavation speed. At the same time, after the surrounding rock has left the shield, the arch spacing should be reduced or a higher specification of steel arch should be used to avoid collapse and shutdown.

[0022] (3) High risk:

[0023] It is necessary to take advance support measures, reduce the arch spacing or use higher specification steel arches.

[0024] Preferably, the TBM machine risk advance identification specifically includes the following steps:

[0025] First, a preliminary detection is carried out at a long distance through HSP. During the test, a low-frequency sound wave signal is emitted at one point and a reflected wave signal is received at another point. When the wave impedance of the surrounding rock changes, part of the seismic wave will be reflected back, and the other part of the seismic wave will continue to propagate forward. If a reflected wave signal is received, it indicates that there is an obvious interface in the rock. When there is an obvious interface at a position of several consecutive meters, it is considered that the surrounding rock in this area is broken, otherwise the surrounding rock is not broken.

[0026] The principle of TSP is the same as that of HSP. It also determines whether the surrounding rock is broken by receiving reflected waves. However, it fully recognizes the complexity of the three-dimensional wave field and can perform directional filtering to retain only the echo in front of the face, avoiding technical defects such as high false alarm rates. Therefore, it has higher accuracy. When the HSP method detects the existence of a broken zone in front, the TSP method is used for supplementary measurement.

[0027] Preferably, the TBM jam risk approaching identification includes excavation parameter identification, slag feature identification and algorithm architecture.

[0028] Preferably: the coring is specifically performed by drilling with an advance drill, and then the degree and range of crushing of the surrounding rock are analyzed based on the core taken out and the imaging analysis in the hole, and the rock quality index (RQD) is used as a judgment index. RQD refers to the ratio of the cumulative length of columnar cores greater than 10 cm in each footage to the footage of each drilling round. If RQD>50%, it is considered that the surrounding rock is not crushed, and if RQD<50%, it is considered that the surrounding rock is crushed.

[0029] Preferably, the thrust and torque analysis is specifically that the calculated thrust and torque must both meet the escape condition to be judged as medium risk, and as long as one reaches the critical condition of the machine being stuck, it is judged as high risk.

[0030] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention establishes surrounding rock detection methods for long distances and short distances, thereby realizing comprehensive identification of TBM stuck risks by combining multiple methods such as advanced geological prediction, tunneling parameter identification, slag state identification, drilling coring identification, and critical state identification for escape. While ensuring prediction accuracy, the number of drilling and coring operations is reduced, thereby minimizing the probability of misjudgment and missed judgment, and has broad promotion value and significant economic and social benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0032] Figure 1 It is a TBM card machine risk identification system architecture diagram of a TBM card machine risk comprehensive identification method described in the present invention.

[0033] Figure 2 It is a diagram of the proximity identification algorithm architecture of a TBM card machine risk comprehensive identification method described in the present invention.

[0034] Figure 3 It is a diagram illustrating shield calculation parameters of a comprehensive TBM jam risk identification method described in the present invention. DETAILED DESCRIPTION

[0035] The specific implementation of the present invention is described below with reference to embodiments.

[0036] Example 1

[0037] A comprehensive identification method for TBM jam risk includes the following steps:

[0038] Step S1, definition of TBM card risk level:

[0039] The TBM machine jam risk prediction system needs to first quantify the risk level and formulate corresponding treatment measures for different risk levels; the machine jam risk is divided into three levels:

[0040] (1) Low risk:

[0041] No action is required, you can pass directly;

[0042] (2) Medium risk:

[0043] The main driver can pass smoothly by relying on his experience, and there is no need to take advance support measures. However, the main driver needs to pay attention to adjusting the excavation parameters in real time and appropriately reduce the excavation speed. At the same time, after the surrounding rock has left the shield, the arch spacing should be reduced or a higher specification of steel arch should be used to avoid collapse and shutdown.

[0044] (3) High risk:

[0045] It is necessary to take advance support measures, reduce the arch spacing or use higher specification steel arches.

[0046] Step S2, TBM machine jam risk prediction system architecture:

[0047] Establish a TBM stuck risk prediction system architecture that combines advanced TBM stuck risk identification, TBM stuck risk identification, drilling coring, thrust and torque analysis methods to avoid misjudgment and missed judgments that may occur when using a single prediction method. The overall architecture is as follows Figure 1 As shown; the operation steps are:

[0048] (1) First, use HSP to preliminarily detect the surrounding rock at a distant location. If the surrounding rock is not broken, no further advanced geological prediction is performed. However, the tunneling parameters are still used to identify the approaching risk of TBM jam to avoid missed judgments. If HSP detects that the surrounding rock is broken, further detection is performed through TSP to avoid misjudgment.

[0049] (2) If HSP fails to detect surrounding rock crushing or TSP supplementary detection fails to detect surrounding rock crushing, the risk of machine jam is greatly reduced. However, during the excavation process, critical identification needs to be performed in real time based on the excavation parameters to avoid missed identification. If no warning information is displayed, it indicates that the risk is low and the excavator can proceed directly. Otherwise, it is necessary to further determine the surrounding rock status through core drilling.

[0050] (3) If the results of the advanced geological prediction or the identification of the proximity of the excavation parameters show that there is a medium or high risk, further verification is required through drilling. If the results of the coring of the boreholes show that the surrounding rock is not broken, the results are output to evaluate that there is a medium risk in the current section; if the results of the coring of the boreholes show that the surrounding rock is broken, the thrust and torque are verified according to the range of the surrounding rock breaking;

[0051] (4) A safety factor K is reserved. If the thrust and torque calculation results show that K times the maximum thrust and torque of the TBM when it passes through the broken zone does not exceed the maximum thrust and torque of the equipment, it is judged as medium risk. Otherwise, it is judged as high risk.

[0052] Step S3: Advance identification of TBM jam risk:

[0053] Advanced identification includes: horizontal sonic profiling (HSP) and seismic wave reflection (TSP), both of which belong to elastic wave reflection methods, but the TSP method requires drilling, which is more accurate and takes longer time. Therefore, it is used as a supplement to the HSP method;

[0054] First, the HSP method is used for preliminary detection at a long distance. During the test, a low-frequency sound wave signal is emitted at one point and a reflected wave signal is received at another point. When the wave impedance of the surrounding rock changes (for example, when encountering the interface of karst, fault or rock layer), part of the seismic wave will be reflected back, and the other part of the seismic wave will continue to propagate forward. If the reflected wave signal is received, it indicates that there is an obvious interface in the rock. When there is an obvious interface at a position of several consecutive meters, it is considered that the surrounding rock in this area is broken, otherwise the surrounding rock is not broken.

[0055] The principle of TSP is the same as that of HSP, which also determines whether the surrounding rock is broken by receiving reflected waves. However, it fully understands the complexity of the three-dimensional wave field and can perform directional filtering, retaining only the echo in front of the tunnel face, avoiding the technical defects of high false alarm rate, so the accuracy is higher. When the HSP method detects the existence of a broken zone in front, the TSP method is used for supplementary measurement.

[0056] Step S4: Identification of the risk of TBM jam:

[0057] 1. Identification of excavation parameters:

[0058] The parameters that have a strong correlation with the risk of machine jamming include the thrust of TBM, cutter head torque, shield pressure and shield displacement; when TBM passes through the broken zone, if there is a risk of collapse of the surrounding rock, the TBM shield will be squeezed, so that the shield pressure increases significantly, the shield displacement increases inward, and the TBM resistance increases, resulting in the thrust and cutter head torque being maintained at a large value; the TBM shield consists of three parts, namely the top shield, the left shield and the right shield; according to statistics, the maximum shield pressure at three positions, the average shield pressure at three positions, the maximum negative displacement of the shield at three positions (displacement caused by surrounding rock pressure), the maximum change in shield displacement values ​​at three positions within 10m, the maximum thrust of TBM, and the maximum torque of the cutter head are the six parameters with the strongest correlation with the risk of machine jamming, so these six parameters are selected as indicators for evaluating the risk of machine jamming;

[0059] 2. Identification of slag characteristics:

[0060] The characteristics of the slag can be obtained in real time through the monitoring video of the belt conveyor on the TBM. When excavating in a broken stratum, there is a significant difference between the state of the belt conveyor slag and that in the non-broken zone. In the non-broken zone, the slag is mostly muddy, while in the broken zone, the slag is mostly blocky. Therefore, it can be used as a criterion for evaluating the surrounding rock crushing situation. Taking into account the propulsion force, cutter torque, shield pressure and shield displacement of the TBM, and the state of the belt conveyor slag, the accuracy of the prediction can be greatly improved. If the surrounding rock is broken, a large amount of block slag will appear. If the surrounding rock conditions are good, the slag will be muddy. The slag characteristics are now quantified, and a coefficient is defined as the slag characteristic coefficient, which takes values ​​of 0 and 1. The block slag can be identified by machine vision. A certain critical value is selected. When a large amount of block slag appears and its proportion exceeds the critical value, the slag characteristic coefficient takes 1, otherwise it takes 0.

[0061] 3. Algorithm architecture:

[0062] By using machine learning algorithms, the excavation data of the broken zone collected on site was used for machine learning training to obtain a TBM jam prediction model, and an integrated algorithm including random forest and neural network was constructed, such as Figure 2 As shown;

[0063] The input parameters include the maximum shield pressure, the average shield pressure, the maximum shield negative displacement, the maximum change of shield displacement, the maximum thrust of TBM, the maximum torque of cutter head, the slag characteristic coefficient, and 7 parameters. The output parameter is the machine jam risk, and its value is 0 (no warning) and 1 (warning).

[0064] Table 1 Description of relevant parameters

[0065]

[0066]

[0067] The models trained by random forest and neural network will respectively give prediction results of the risk of machine jamming. Only when the prediction results of the two prediction models are both 0, no warning signal will be issued. In other cases, a warning signal will be issued; that is, a warning signal will be issued when one of the two prediction results is 0 and the other is 1, or when both are 1.

[0068] Step S5, drilling and coring:

[0069] Drilling is carried out by an advance drilling rig, and then the degree and range of crushing of the surrounding rock are analyzed based on the core taken out and in-hole imaging analysis. Compared with the physical detection method, the accuracy is greatly improved, but it is time-consuming and expensive, and is not suitable for routine implementation. Therefore, as a supplementary detection method for risk prediction, for locations where risks may exist, it is necessary to drill and coring the surrounding rock as a supplementary identification to minimize the possibility of misjudgment; the rock quality index (RQD) is used as a judgment index. RQD refers to the ratio of the cumulative length of columnar cores greater than 10 cm in each footage to the footage of each drilling round (expressed as a percentage). If RQD>50%, the surrounding rock is considered to be not crushed, and if RQD<50%, the surrounding rock is considered to be crushed.

[0070] Step S6: Thrust and torque analysis:

[0071] When passing through loose and broken rock formations, the surrounding rock will collapse on the shield as the TBM advances. If the weight of the collapsed surrounding rock exceeds the shield's bearing limit, it will cause the shield to shrink or the shield tail to deform. At the same time, the collapsed surrounding rock will act on the shield to produce huge friction resistance, making it difficult for the TBM to advance. If the thrust or torque at this time is not enough to get out of trouble, the speed will decrease until the machine stops. Therefore, the key parameters for TBM to get out of trouble are thrust and torque. A comprehensive analysis of thrust and torque can further determine the risk of machine jamming. The calculated thrust and torque must both meet the conditions for getting out of trouble to be judged as medium risk. As long as one of them reaches the critical condition for machine jamming, it will be judged as high risk.

[0072] 1. Thrust;

[0073] The thrust of TBM mainly includes the cutterhead propulsion reaction force F1 and the rear supporting resistance F2. When the surrounding rock is broken, the squeezing of the loose rock mass on the shield will produce additional resistance F3. Assuming that the surrounding rock at the current position has not broken or collapsed and acts on the shield, the current TBM propulsion force F = F1 + F2. If the maximum propulsion force that the TBM equipment can provide is F max ; Then the card machine's judgment criteria are:

[0074] K(F+F3)≥F max —(1)

[0075] F1 will change due to the influence of surrounding rock conditions and can be calculated by the following formula:

[0076]

[0077] F3=μ h p-(3)

[0078] Where: p is the loose body load acting on the shield, μ h is the friction coefficient between the surrounding rock and the shield, γ is the weight of the loose body, h is the thickness of the loose body, d is the arc length of the loose body in the circumferential direction, θ is the circumferential angle of the loose body, D is the tunnel diameter, and L r is the longitudinal length of the loose body. When the longitudinal length L of the loose body r When it is greater than the shield length L, its value is equal to the shield length L in the calculation. The relevant parameters are as follows Figure 3 As shown;

[0079] 2. Torque;

[0080] The cutterhead torque mainly includes the rolling resistance torque T1 of the cutterhead, the torque T2 required for rock slag mixing, and the torque T3 required to overcome the cutterhead's own weight. When the surrounding rock is broken, pressure will also be generated on the cutterhead, thereby forming an additional torque T4. Assuming that the surrounding rock at the current position has not broken or collapsed and acts on the cutterhead, the current cutterhead torque T = T1 + T2 + T3. The maximum torque that the TBM equipment can provide is T max ; Then the card machine's judgment criteria are:

[0081] K(T+T4)≥T max -(4)

[0082] The torque T4 generated by surrounding rock extrusion can be calculated by the following formula:

[0083]

[0084] Where: μ d is the friction coefficient between the surrounding rock and the cutterhead, γ is the weight of the loose mass, h is the thickness of the loose mass, θ is the circumferential angle of the loose mass, D is the tunnel diameter, and L d is the thickness of the cutter head panel.

[0085] The basic principles, main features and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for illustrating the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.

Claims

1. A comprehensive TBM machine jam risk identification method, characterized by: include Definition of TBM card machine risk level; TBM card machine risk prediction system architecture; Advanced identification of TBM jam risk, including horizontal sound profile (HSP) and seismic wave reflection (TSP); Identification of the imminent risk of TBM jamming; Drilling and coring; Thrust and torque analysis.

2. A TBM machine jam risk comprehensive identification method according to claim 1, characterized in that: The specific steps are: Step S1: First, perform a preliminary detection of the surrounding rock through HSP at a distant location. If the surrounding rock is not broken, no further advanced geological prediction is performed. However, the excavation parameters are still used to identify the risk of TBM jam to avoid missed judgments. If HSP detects that the surrounding rock is broken, further detection is performed through TSP to avoid misjudgment. Step S2: If HSP does not detect surrounding rock crushing or TSP supplementary detection does not detect surrounding rock crushing, the risk of machine jamming is greatly reduced. However, during the excavation process, critical identification needs to be performed in real time based on the excavation parameters to avoid missed identification. If no warning information appears, it indicates that the risk is low and the excavator can pass directly. Otherwise, it is necessary to further determine the surrounding rock status through core drilling. Step S3: If the results of the advanced geological prediction or the proximity identification of the tunneling parameters show that there is a medium or high risk, further verification is required through drilling. If the coring results show that the surrounding rock is not broken, the results are output to evaluate that there is a medium risk in the current section; if the coring results show that the surrounding rock is broken, the thrust and torque are verified according to the range of surrounding rock crushing. Step S4: reserve a safety factor K. If the thrust and torque calculation results show that K times the maximum thrust and torque of the TBM when it passes through the broken zone does not exceed the maximum thrust and torque of the equipment, it is judged as medium risk, otherwise it is judged as high risk.

3. A TBM machine jam risk comprehensive identification method according to claim 1, characterized in that: The risk of TBM jamming is divided into three levels: (1) Low risk: No action is required, you can pass directly; (2) Medium risk: The main driver can pass smoothly by relying on his experience, and there is no need to take advance support measures. However, the main driver needs to pay attention to adjusting the excavation parameters in real time and appropriately reduce the excavation speed. At the same time, after the surrounding rock has left the shield, the arch spacing should be reduced or a higher specification of steel arch should be used to avoid collapse and shutdown. (3) High risk: It is necessary to take advance support measures, reduce the arch spacing or use higher specification steel arches.

4. A TBM machine jam risk comprehensive identification method according to claim 1, characterized in that: The TBM machine jam risk advanced identification specifically includes the following steps: First, a preliminary detection is carried out at a long distance through HSP. During the test, a low-frequency sound wave signal is emitted at one point and a reflected wave signal is received at another point. When the wave impedance of the surrounding rock changes, part of the seismic wave will be reflected back, and the other part of the seismic wave will continue to propagate forward. If a reflected wave signal is received, it indicates that there is an obvious interface in the rock. When there is an obvious interface at a position of several consecutive meters, it is considered that the surrounding rock in this area is broken, otherwise the surrounding rock is not broken. The principle of TSP is the same as that of HSP. It also determines whether the surrounding rock is broken by receiving reflected waves. However, it fully recognizes the complexity of the three-dimensional wave field and can perform directional filtering to retain only the echo in front of the face, avoiding technical defects such as high false alarm rates. Therefore, it has higher accuracy. When the HSP method detects the existence of a broken zone in front, the TSP method is used for supplementary measurement.

5. The method for comprehensive identification of TBM jam risk according to claim 1 is characterized by: The TBM jam risk identification includes excavation parameter identification, slag feature identification and algorithm architecture.

6. A TBM machine jam risk comprehensive identification method according to claim 1, characterized in that: The coring is specifically performed by drilling with an advance drill, and then the crushing degree and crushing range of the surrounding rock are analyzed based on the core taken out and the imaging analysis in the hole, and the rock quality index (RQD) is used as a judgment index. RQD refers to the ratio of the cumulative length of columnar cores greater than 10 cm in each footage to the footage of each drilling round. If RQD>50%, it is considered that the surrounding rock is not crushed, and if RQD<50%, it is considered that the surrounding rock is crushed.

7. A TBM machine jam risk comprehensive identification method according to claim 1, characterized in that: The thrust and torque analysis specifically states that the calculated thrust and torque must both meet the escape conditions to be judged as medium risk. As long as one of them reaches the critical condition of the machine being stuck, it is judged as high risk.

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