CN114495433A - Tunnel boring machine surrounding rock collapse early warning method and device and terminal equipment - Google Patents
Tunnel boring machine surrounding rock collapse early warning method and device and terminal equipment Download PDFInfo
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Abstract
The invention is suitable for the technical field of tunneling, and provides a method, a device and terminal equipment for early warning collapse of surrounding rocks of a tunneling machine, wherein the method comprises the following steps: calculating a predicted penetration index of the current section based on the historical penetration index, wherein the historical penetration index is determined based on historical operating parameters of the tunnel boring machine; calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, wherein the historical tunneling disturbance degree is determined based on the historical operating parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine; calculating a first collapse probability based on the predicted penetration index, calculating a second collapse probability based on the predicted tunneling disturbance degree, calculating the current collapse probability of the surrounding rock based on the first and second collapse probabilities, and generating collapse early warning information based on the current collapse probability. The method for warning collapse of surrounding rocks of the tunnel boring machine can calculate the collapse probability of the surrounding rocks based on the operation parameters of the tunnel boring machine, avoid collapse accidents and guarantee construction safety.
Description
Technical Field
The invention belongs to the technical field of tunneling, and particularly relates to a method and a device for early warning collapse of surrounding rocks of a tunneling machine and terminal equipment.
Background
The Tunnel Boring Machine (TBM) is a large-scale comprehensive Tunnel construction device, can integrate drilling, digging and protecting into a whole, and effectively realizes the industrialized operation of long and large Tunnel construction. Compared with the traditional drilling and blasting method, the tunnel boring machine has the advantages of high construction speed, no blasting, extremely small tunneling and overexcavation amount, small disturbance to surrounding rocks, good working environment, safe construction and the like. In the excavation process of long and large tunnels, TBM construction is a development trend.
However, in the excavation of weak surrounding rock sections, collapse disasters are the most common disaster types with the highest occurrence frequency. On one hand, the collapse disaster of the surrounding rock can cause that the tunneling must be constructed by adopting measures such as short footage, low rotating speed, low torque and the like, so that the construction process is complicated and the tunneling efficiency is low. On the other hand, the collapse of the surrounding rock needs manual removal of a large amount of low slag, and the collapse backfill amount is large.
The frequent occurrence of collapse disasters can increase the construction cost and reduce the construction efficiency. However, conventionally, the risk of the collapse of the surrounding rock of the TBM can only be predicted based on the experience of the constructors, and it is difficult to take preventive measures reliably in time.
Disclosure of Invention
In view of this, the embodiment of the invention provides a method and a device for warning collapse of surrounding rocks of a tunnel boring machine and terminal equipment, which can reliably warn the collapse condition of the surrounding rocks.
The first aspect of the embodiment of the invention provides a method for early warning collapse of surrounding rocks of a tunnel boring machine, which comprises the following steps:
calculating a predicted penetration index of the current section based on a historical penetration index, wherein the historical penetration index is determined based on historical operating parameters of the tunnel boring machine;
calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, wherein the historical tunneling disturbance degree is determined based on the historical operation parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine;
calculating a first collapse probability based on the predicted penetration index, and calculating a second collapse probability based on the predicted tunneling disturbance degree;
calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability, and generating collapse early warning information based on the current collapse probability.
A second aspect of the embodiments of the present invention provides a tunnel boring machine surrounding rock collapse early warning device, including:
the predicted penetration index calculation module is used for calculating a predicted penetration index of the current section based on a historical penetration index, and the historical penetration index is determined based on historical operating parameters of the tunnel boring machine;
the predicted tunneling disturbance degree calculating module is used for calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, and the historical tunneling disturbance degree is determined based on the historical operating parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine;
the collapse probability calculation module is used for calculating a first collapse probability based on the predicted penetration index and calculating a second collapse probability based on the predicted tunneling disturbance degree;
and the collapse early warning information generating module is used for calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability and generating collapse early warning information based on the current collapse probability.
A third aspect of the embodiments of the present invention provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method when executing the computer program.
A fourth aspect of embodiments of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method as described above.
A fifth aspect of embodiments of the present invention provides a computer program product, which, when run on a terminal device, causes the electronic device to perform the steps of the method according to any one of the first aspect.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: the embodiment of the invention provides a tunnel boring machine surrounding rock collapse early warning method which comprises the steps of calculating a predicted penetration index of a current section based on a historical penetration index, wherein the historical penetration index is determined based on historical operating parameters of a tunnel boring machine; calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, wherein the historical tunneling disturbance degree is determined based on the historical operating parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine; calculating a first collapse probability based on the predicted penetration index, calculating a second collapse probability based on the predicted tunneling disturbance degree, calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability, and generating collapse early warning information based on the current collapse probability. The method for warning collapse of surrounding rocks of the tunnel boring machine provided by the embodiment of the invention can calculate the collapse probability of the surrounding rocks based on the operating parameters of the tunnel boring machine, so that collapse accidents are avoided, and the construction safety is ensured.
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In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flow chart illustrating an implementation process of a tunnel boring machine surrounding rock collapse early warning method according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an early warning system applied to the tunnel boring machine surrounding rock collapse early warning method provided by the embodiment of the invention;
fig. 3 is a schematic structural diagram of a surrounding rock collapse early warning device of a tunnel boring machine according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
In the TBM construction process, different TBM equipment adopts different support systems and different advanced reinforcement measures. For the construction process of a certain tunnel, the TBM is usually not replaced, namely, the parameters of the TBM are not changed in one construction process.
In some embodiments, the main factors causing the collapse of the surrounding rock when the TBM is tunneling include the lithology of the surrounding rock and the tunneling disturbance condition. Namely, the poorer the lithology of the surrounding rock, the larger the tunneling disturbance, and the more easily the collapse occurs.
Fig. 1 shows a schematic flow chart of an implementation of the method for warning collapse of surrounding rock of a tunnel boring machine according to the embodiment of the invention. Referring to fig. 1, the method for warning collapse of surrounding rock of a tunnel boring machine according to the embodiment of the present invention may include steps S101 to S104.
S101: and calculating a predicted penetration index of the current section based on the historical penetration index, wherein the historical penetration index is determined based on historical operating parameters of the tunnel boring machine.
The penetration index FPI may reflect the compressive strength of the surrounding rock.
In some embodiments, the historical operating parameters include hob average thrust and cutter disc penetration. Before S101, the method may further include:
and calculating the historical penetration index based on a penetration index formula, the average thrust of the hob and the penetration of the cutter head. The penetration index formula comprises: FPI is F/P; wherein, FPI is penetration index, F is hob average thrust on a cutter head of the tunnel boring machine, and P is cutter head penetration of the tunnel boring machine.
In some embodiments, F is the average thrust of a single hob on a TBM cutterhead in kN; p is the penetration degree of a TBM cutter head, and the unit is mm/r. In particular, F ═ F0/n，F0＝0.8F1；F0The unit is kN of the thrust of the whole cutter head of the TBM; n is the total number of hob cutters on a TBM cutter head, F1TBM total propulsive force in kN. The total number n of the hobs is determined by TBM design and production and can be directly obtained; penetration P and total thrust F1Can be directly read by a data acquisition system of the TBM equipment. Based on the data, the penetration index value of the tunnel boring machine can be calculated in real time.
In some embodiments, S101 specifically includes: and acquiring the historical penetration indexes of the preset number with the minimum time difference with the current moment, and numbering the historical penetration indexes of the preset number according to the time sequence. And fitting the preset number of historical penetration indexes based on a Lagrange interpolation method to obtain a penetration index interpolation polynomial. And calculating the predicted penetration index of the current section based on the penetration index interpolation polynomial.
In some embodiments, a Lagrange interpolation-based method is used for fitting a preset number of historical penetration indexes, and calculating a predicted penetration index of the current section.
In a specific example, fitting the first 21 historical penetration indexes to obtain a fitting formula includes:
wherein, let xk＝k。
Obtaining a fitted interpolation polynomial:
substituting x into 21 into the fitted difference polynomial, and calculating to obtain a predicted penetration index FPI of the current sectionp。
S102: and calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, wherein the historical tunneling disturbance degree is determined based on the historical operation parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine.
In some embodiments, the historical surrounding rock parameters include rock strength and geological indicators, and the historical operating parameters include tunneling speed. Before S102, the method may further include: and calculating the historical tunneling disturbance degree based on a tunneling disturbance degree formula, the rock strength, the geological index and the tunneling speed. The tunneling disturbance degree formula comprises:
EXP (-0.017UCS-0.007GSI-0.019ROP + 1.923). Wherein D is the tunneling disturbance degree, UCS is the rock strength, GSI is the geological index, and ROP is the tunneling speed.
In some embodiments, during the tunneling process of the tunnel boring machine, the disturbance of the tunneling is affected by the excavation method, the tunnel dimensions, the rock-soil body parameters, and the tunneling parameters.
In some embodiments, S103 specifically includes: and acquiring the historical tunneling disturbance degrees of the preset number with the minimum time difference with the current moment, and numbering the historical tunneling disturbance degrees of the preset number according to the time sequence. And fitting the historical tunneling disturbance degrees of the preset number by using a Lagrange difference value-based method to obtain a tunneling disturbance degree interpolation polynomial. And calculating the predicted tunneling disturbance degree of the current section based on the tunneling disturbance degree interpolation polynomial.
In some embodiments, a Lagrange interpolation-based method is used for fitting a preset number of historical tunneling disturbance degrees, and calculating the predicted disturbance degree of the current section.
In a specific example, fitting the previous 21 historical excavation disturbance degrees to obtain a fitting formula, including:
wherein, let xk＝k。
Obtaining a fitted difference polynomial:
substituting x into 21 into the fitted difference polynomial, and calculating to obtain the predicted tunneling disturbance degree D of the current sectionp。
S103: and calculating a first collapse probability based on the predicted penetration index, and calculating a second collapse probability based on the predicted tunneling disturbance degree.
In some embodiments, S103 comprises: calculating the first collapse probability based on a first collapse probability formula and the predicted penetration index.
And calculating the second collapse probability based on a second collapse probability formula and the predicted tunneling disturbance degree.
The first collapse probability formula comprises:
wherein P (FPI) is the first collapse probability, FPImaxIs the maximum value of the historical penetration index in a preset time period, FPIminIs the minimum value of the historical penetration index in a preset time period, FPIpTo predict penetration index.
The second collapse probability formula comprises:
wherein P (D) isProbability of secondary collapse, DmaxIs the maximum value of the historical tunneling disturbance degree D in a preset time periodminIs the minimum value of the disturbance degree of the historical tunneling in a preset time period, DpTo predict the degree of disturbance of the drive.
S104: calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability, and generating collapse early warning information based on the current collapse probability.
In some embodiments, S104 comprises: calculating a current collapse probability of the surrounding rock based on a current collapse probability formula, the first collapse probability, and the second collapse probability.
The current collapse probability formula comprises: p ═ 0.538 × P (fpi) +0.462 × P (d); wherein P is the current probability of collapse, P (FPI) is the first probability of collapse, and P (D) is the second probability of collapse.
In a specific example, the collapse early warning information is generated based on the current collapse probability, and when the collapse probability of the surrounding rock is smaller than 0.1, the safety of the surrounding rock is judged, and the warning indicator lamp is controlled to be a green lamp. And when the collapse probability of the surrounding rock is more than or equal to 0.1 and less than or equal to 0.3, judging that the surrounding rock is normal, and controlling the alarm indicator lamp to be a yellow lamp. And when the collapse probability of the surrounding rock is more than 0.3, judging that the surrounding rock has a collapse danger, and controlling the alarm indicator lamp to be a red lamp.
The method for warning collapse of surrounding rocks of the tunnel boring machine can quantitatively analyze the collapse accident of the surrounding rocks based on the requirements of information and data in the tunnel construction process of the TBM and on a large number of TBM tunneling parameters, and quantitatively analyze the collapse risk of the surrounding rocks by adopting a probability statistics method and a numerical analysis method so as to accurately obtain the collapse probability of the surrounding rocks. On the other hand, the calculation process of the method is easy to operate and implement. The method for warning collapse of the surrounding rock of the tunnel boring machine can prejudge the risk of collapse of the surrounding rock, know the risk in advance and send warning, prevent collapse accidents from happening even if workers take measures, and accurately and intelligently improve the safety control level of tunneling construction.
Fig. 2 shows a system structure schematic diagram of the application of the tunnel boring machine surrounding rock collapse early warning method provided by the embodiment of the invention. Referring to fig. 2, a user can acquire the situation of the collapse early warning by using the TBM tunneling surrounding rock collapse early warning system. The early warning system can comprise a data reading module, a data processing module, a data display module, a graphic display module and an indicator light module.
Specifically, the data reading device is used for collecting dynamic tunneling parameters generated in the tunneling process of the TBM in real time. The dynamic tunneling parameters comprise the current pile number, the total thrust, the penetration degree, the tunneling speed, the cutter head torque and the cutter head rotating speed.
The data processing module is provided with a parameter monitoring module for extracting abnormal change parameters in the tunneling parameters, the data processing device can delete the abnormal parameters with mutation, extract the average value of multiple groups of historical data, and substitute the read dynamic values of the tunneling parameters into the calculation formula to predict the collapse probability of the surrounding rock.
And the data display module is used for explicitly displaying the real-time tunneling parameters, the penetration index FPI value and the surrounding rock collapse probability predicted by the data processing module. The graph display module is used for displaying the penetration index FPI and the change trend of the collapse probability of the surrounding rock, so that constructors can clearly and definitely make prejudgment on the collapse risk of the surrounding rock, and take measures in time to avoid the collapse risk of the surrounding rock.
The indicating lamp module can be provided with green, yellow and red indicating lamps, and the indicating lamps are controlled according to the collapse probability of the surrounding rock. Specifically, when the collapse probability of the surrounding rock is greater than 0.3, the red light is on; when the collapse probability of the surrounding rock is less than or equal to 0.3 and more than or equal to 0.1, the yellow lamp is on; and when the collapse probability of the surrounding rock is less than 0.1, the green light is on. It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Fig. 3 shows a schematic structural diagram of the tunnel boring machine surrounding rock collapse early warning device provided by the embodiment of the invention. Referring to fig. 3, the device 30 for warning collapse of surrounding rock of a tunnel boring machine according to the embodiment of the present invention may include a predicted penetration index calculation module 310, a predicted boring disturbance degree calculation module 320, a collapse probability calculation module 330, and a collapse warning information calculation module 340.
And a predicted penetration index calculation module 310, configured to calculate a predicted penetration index of the current section based on a historical penetration index, where the historical penetration index is determined based on historical operating parameters of the tunnel boring machine.
And the predicted tunneling disturbance degree calculating module 320 is used for calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, and the historical tunneling disturbance degree is determined based on the historical operating parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine.
And the collapse probability calculation module 330 is configured to calculate a first collapse probability based on the predicted penetration index, and calculate a second collapse probability based on the predicted tunneling disturbance degree.
And the collapse early warning information generating module 340 is configured to calculate a current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability, and generate collapse early warning information based on the current collapse probability.
The surrounding rock collapse early warning device of the tunnel boring machine provided by the invention can calculate the collapse probability of the surrounding rock based on the operation parameters of the tunnel boring machine, so that the collapse accident is avoided, and the construction safety is ensured.
In some embodiments, the historical operating parameters include hob average thrust and cutter disc penetration. The device for early warning of collapse of surrounding rock of the tunnel boring machine provided by the embodiment of the invention can also comprise a historical penetration index calculation module, wherein the historical penetration index calculation module is used for calculating the historical penetration index based on a penetration index formula, the average thrust of the hob and the penetration of the cutter head. The penetration index formula comprises: FPI is F/P; wherein FPI is the penetration index, F is the average thrust of a hob on a cutterhead of the tunnel boring machine, and P is the penetration of the cutterhead of the tunnel boring machine.
In some embodiments, the predicted penetration index calculating module 310 is specifically configured to obtain a preset number of historical penetration indexes with a smallest time difference from the current time, and number the preset number of historical penetration indexes in a time sequence. And fitting the preset number of historical penetration indexes based on a Lagrange interpolation method to obtain a penetration index interpolation polynomial. And calculating the predicted penetration index of the current section based on the penetration index interpolation polynomial.
In some embodiments, the historical surrounding rock parameters include rock strength and geological indicators, and the historical operating parameters include tunneling speed. The device for early warning of collapse of surrounding rock of the tunnel boring machine provided by the embodiment of the invention can also comprise a historical tunneling disturbance degree calculation module, wherein the historical tunneling disturbance degree calculation module is used before the predicted tunneling disturbance degree of the current section is calculated based on the historical tunneling disturbance degree. And calculating the historical tunneling disturbance degree based on a tunneling disturbance degree formula, the rock strength, the geological index and the tunneling speed. The tunneling disturbance degree formula comprises: EXP (-0.017UCS-0.007GSI-0.019ROP + 1.923). Wherein D is the tunneling disturbance degree, UCS is the rock strength, GSI is the geological index, and ROP is the tunneling speed.
In some embodiments, the predicted tunneling disturbance degree calculation module 320 is specifically configured to obtain a preset number of historical tunneling disturbance degrees with a smallest time difference from the current time, and number the preset number of historical tunneling disturbance degrees according to a time sequence. And fitting the historical tunneling disturbance degrees of the preset number by using a Lagrange difference value-based method to obtain a tunneling disturbance degree interpolation polynomial. And calculating the predicted tunneling disturbance degree of the current section based on the tunneling disturbance degree interpolation polynomial.
In some embodiments, the collapse probability calculation module 330 is specifically configured to: calculating the first collapse probability based on a first collapse probability formula and the predicted penetration index.
And calculating the second collapse probability based on a second collapse probability formula and the predicted tunneling disturbance degree.
The first collapse probability formula comprises:
wherein P (FPI) is the first collapse probability, FPImaxIs the maximum value of the historical penetration index in a preset time period, FPIminIs the minimum value of the historical penetration index in a preset time period, FPIpTo predict penetration index.
The second collapse probability formula comprises:
wherein P (D) is the second collapse probability, DmaxIs the maximum value of the historical tunneling disturbance degree D in a preset time periodminIs the minimum value of the disturbance degree of the historical tunneling in a preset time period, DpTo predict the degree of disturbance of the drive.
In some embodiments, the collapse warning information generating module 340 is specifically configured to: calculating a current collapse probability of the surrounding rock based on a current collapse probability formula, the first collapse probability, and the second collapse probability.
The current collapse probability formula comprises: p ═ 0.538 × P (fpi) +0.462 × P (d); wherein P is the current probability of collapse, P (FPI) is the first probability of collapse, and P (D) is the second probability of collapse.
Fig. 4 is a schematic diagram of a terminal device according to an embodiment of the present invention. As shown in fig. 4, the terminal device 40 of this embodiment includes: a processor 400, a memory 410 and a computer program 420, such as a tunnel boring machine wall rock collapse warning program, stored in the memory 410 and operable on the processor 400. The processor 40, when executing the computer program 420, implements the steps in the above-mentioned various embodiments of the method for warning collapse of surrounding rock of a tunnel boring machine, such as the steps S101 to S104 shown in fig. 1. Alternatively, the processor 400, when executing the computer program 420, implements the functions of the modules/units in the above-mentioned device embodiments, such as the functions of the modules 310 to 340 shown in fig. 3.
Illustratively, the computer program 420 may be partitioned into one or more modules/units that are stored in the memory 410 and executed by the processor 400 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of the computer program 420 in the terminal device 40. For example, the computer program 420 may be divided into a predicted penetration index calculation module, a predicted tunneling disturbance degree calculation module, a collapse probability calculation module, and a collapse warning information calculation module.
The terminal device 40 may be a computing device such as a desktop computer, a notebook, a palm computer, and a cloud server. The terminal device may include, but is not limited to, a processor 400, a memory 410. Those skilled in the art will appreciate that fig. 4 is merely an example of a terminal device 40 and does not constitute a limitation of terminal device 40 and may include more or fewer components than shown, or some components may be combined, or different components, for example, the terminal device may also include input output devices, network access devices, buses, etc.
The Processor 400 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 410 may be an internal storage unit of the terminal device 40, such as a hard disk or a memory of the terminal device 40. The memory 410 may also be an external storage device of the terminal device 40, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on the terminal device 40. Further, the memory 410 may also include both an internal storage unit and an external storage device of the terminal device 40. The memory 410 is used for storing the computer programs and other programs and data required by the terminal device. The memory 410 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the flow of the method according to the embodiments of the present invention may also be implemented by a computer program, which may be stored in a computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method embodiments described above may be implemented. . Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U.S. disk, removable hard disk, magnetic diskette, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signal, telecommunications signal, and software distribution medium, etc. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A tunnel boring machine surrounding rock collapse early warning method is characterized by comprising the following steps:
calculating a predicted penetration index of the current section based on a historical penetration index, wherein the historical penetration index is determined based on historical operating parameters of the tunnel boring machine;
calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, wherein the historical tunneling disturbance degree is determined based on the historical operation parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine;
calculating a first collapse probability based on the predicted penetration index, and calculating a second collapse probability based on the predicted tunneling disturbance degree;
calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability, and generating collapse early warning information based on the current collapse probability.
2. The method for warning collapse of surrounding rocks of a tunnel boring machine according to claim 1, wherein the historical operating parameters include average thrust of a hob and penetration of a cutter head;
before the calculating the predicted penetration index of the current section based on the historical penetration index, the method further comprises:
calculating the historical penetration index based on a penetration index formula, the average thrust of the hob and the penetration of the cutter head;
the penetration index formula comprises: FPI is F/P; wherein FPI is the penetration index, F is the average thrust of a hob on a cutterhead of the tunnel boring machine, and P is the penetration of the cutterhead of the tunnel boring machine.
3. The method for warning collapse of surrounding rocks of a tunnel boring machine according to claim 1, wherein the step of calculating the predicted penetration index of the current section based on the historical penetration index comprises the steps of:
acquiring a preset number of historical penetration indexes with the minimum time difference with the current moment, and numbering the preset number of historical penetration indexes according to a time sequence;
fitting the preset number of historical penetration indexes based on a Lagrange interpolation method to obtain a penetration index interpolation polynomial;
and calculating the predicted penetration index of the current section based on the penetration index interpolation polynomial.
4. The method for warning collapse of surrounding rocks of a tunnel boring machine according to claim 1, wherein the historical surrounding rock parameters comprise rock strength and geological indexes, and the historical operating parameters comprise a boring speed;
before the calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, the method further comprises the following steps:
calculating the historical tunneling disturbance degree based on a tunneling disturbance degree formula, the rock strength, the geological index and the tunneling speed;
the tunneling disturbance degree formula comprises: and D is EXP (-0.017UCS-0.007GSI-0.019ROP +1.923), wherein D is the tunneling disturbance degree, UCS is the rock strength, GSI is the geological index, and ROP is the tunneling speed.
5. The method for warning collapse of surrounding rocks of a tunnel boring machine according to claim 1, wherein the step of calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree comprises the steps of:
acquiring historical tunneling disturbance degrees of a preset number with the minimum time difference with the current moment, and numbering the historical tunneling disturbance degrees of the preset number according to a time sequence;
fitting the historical tunneling disturbance degrees of the preset number by a Lagrange difference value-based method to obtain a tunneling disturbance degree interpolation polynomial;
and calculating the predicted tunneling disturbance degree of the current section based on the tunneling disturbance degree interpolation polynomial.
6. The method for early warning of collapse of surrounding rocks of a tunnel boring machine according to any one of claims 1 to 5, wherein the step of calculating a first collapse probability based on the index of predicted penetration and calculating a second collapse probability based on the degree of predicted boring disturbance comprises the steps of:
calculating the first collapse probability based on a first collapse probability formula and the predicted penetration index;
calculating a second collapse probability based on a second collapse probability formula and the predicted tunneling disturbance degree;
the first collapse probability formula comprises:
wherein P (FPI) is the first collapse probability, FPImaxIs the maximum value of the historical penetration index in a preset time period, FPIminIs the minimum value of the historical penetration index in a preset time period, FPIpIs a predicted penetration index;
the second collapse probability formula comprises:
wherein P (D) is the second collapse probability, DmaxIs the maximum value of the historical tunneling disturbance degree D in a preset time periodminIs the minimum value of the disturbance degree of the historical tunneling in a preset time period, DpTo predict the degree of disturbance of the drive.
7. The method for warning collapse of surrounding rocks of a tunnel boring machine according to any one of claims 1 to 5, wherein the calculating of the current collapse probability of the surrounding rocks based on the first collapse probability and the second collapse probability comprises:
calculating a current collapse probability of the surrounding rock based on a current collapse probability formula, the first collapse probability, and the second collapse probability;
the current collapse probability formula comprises: p ═ 0.538 × P (fpi) +0.462 × P (d); wherein P is the current probability of collapse, P (FPI) is the first probability of collapse, and P (D) is the second probability of collapse.
8. The utility model provides a tunnel boring machine country rock early warning device that collapses which characterized in that includes:
the predicted penetration index calculation module is used for calculating a predicted penetration index of the current section based on a historical penetration index, and the historical penetration index is determined based on historical operating parameters of the tunnel boring machine;
the predicted tunneling disturbance degree calculating module is used for calculating the predicted tunneling disturbance degree of the current section based on the historical tunneling disturbance degree, and the historical tunneling disturbance degree is determined based on the historical operating parameters and the historical surrounding rock parameters of the operation of the tunnel boring machine;
the collapse probability calculation module is used for calculating a first collapse probability based on the predicted penetration index and calculating a second collapse probability based on the predicted tunneling disturbance degree;
and the collapse early warning information generating module is used for calculating the current collapse probability of the surrounding rock based on the first collapse probability and the second collapse probability and generating collapse early warning information based on the current collapse probability.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
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