CN111553000A - Intelligent construction method of tunnel by drilling and blasting method - Google Patents
Intelligent construction method of tunnel by drilling and blasting method Download PDFInfo
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Abstract
The application provides an intelligent construction method for a drilling and blasting tunnel, and belongs to the field of tunnel engineering. The tunnel construction method based on the drilling and blasting method integrates an intelligent prediction method for surrounding rock in front of a tunnel face of the tunnel based on the drilling and blasting method, an intelligent grading method for surrounding rock on the tunnel face, an intelligent design method, an intelligent construction method and an intelligent construction quality control method, realizes the integration and high-efficiency cooperative management of intelligent prediction for surrounding rock in front of the tunnel face, intelligent grading for surrounding rock on the tunnel face, intelligent design, intelligent construction and intelligent control for construction quality, can effectively reduce the investment of constructors, improves the construction quality and the construction efficiency, and reduces potential risks in the tunnel construction process.
Description
Technical Field
The application relates to the field of tunnel engineering, in particular to an intelligent construction method for a tunnel by a drilling and blasting method.
Background
At present, the fourth industrial revolution wave is rolled into the whole world, the deep integration of the internet, big data, manpower and entity economy is accelerated, a batch of concepts and systems of factories, cities, railways and the like are promoted, and the tunnel construction is a deep integration product of the emerging technology in the field of tunnels.
At present, only a single tunnel construction technology exists at home and abroad, such as a tunnel face digital imaging technology and a single-machine robot construction technology, and a tunnel construction technology system is not completely discussed and a unified construction site is not available.
Disclosure of Invention
In view of this, the embodiment of the application provides an intelligent construction method for a tunnel by a drilling and blasting method, and aims to provide a new construction mode for the tunnel by the drilling and blasting method, so that the investment of constructors is reduced, the construction quality and the construction efficiency are improved, and the potential risk in the tunnel construction process is reduced.
In a first aspect, the present embodiment provides an intelligent construction method for a tunnel by a drilling and blasting method, including
Acquiring a tunnel advanced geological prediction result based on the drilling parameter information, the advanced drilling information and the surrounding rock information;
acquiring a tunnel face surrounding rock grading result based on tunnel face digital imaging information, drilling parameter information and advanced drilling information;
acquiring the grade and the burial depth of the surrounding rock, performing simulation calculation based on a drilling and blasting tunnel theory, and determining tunnel design parameters;
acquiring data based on tunnel equipment, performing single machine construction of four operation work areas, namely advanced support, drilling and blasting excavation, primary support and secondary lining, and performing space distribution management of each single machine in the tunnel in different states during cluster operation;
and (4) carrying out classified management and control on the tunnel construction quality based on an analytic hierarchy process.
In combination with an embodiment of the first aspect, in some embodiments, the digital imaging information of the face comprises a face geological sketch.
In combination with an embodiment of the first aspect, in some embodiments, the tunnel design parameters include forepoling design parameters, drilling and blasting design parameters, primary support, and secondary lining design parameters.
In combination with an embodiment of the first aspect, in some embodiments the tunnel equipment comprises a grouting trolley, a rock drilling trolley, a bolting trolley, an arch trolley, a jet mixing trolley, a flashing trolley, a lining trolley and a maintenance trolley.
In combination with an embodiment of the first aspect, in some embodiments, the hierarchically-based management and control of the tunnel construction quality comprises
Acquiring construction quality information according to tunnel equipment;
classifying the tunnel construction quality according to the quantity, the size, the position and the performance, and carrying out classified control on the tunnel construction quality based on an analytic hierarchy process;
based on 4 items of basic index information of advanced support quality, drilling and blasting excavation quality, primary support quality and secondary lining quality, a tunnel construction quality classification management and control method is established, and tunnel construction quality is divided into SI (qualified), SII (basically qualified) and SIII (unqualified).
In combination with an embodiment of the first aspect, in some embodiments, further comprising
And evaluating the structure safety according to the stress-strain monitoring data and the deformation monitoring data of the tunnel structure.
With reference to the embodiments of the first aspect, in some embodiments, the safety management control method for monitoring structural deformation adopts a segmented control principle, and the following relevant standards are detailed in the following table:
deformation segment control standard
Note: b, tunnel excavation span; u shape0The initial support limit relative displacement value can be determined according to field measured data or railway tunnel monitoring and measuring technical regulation (Q/CR 9218).
In combination with an embodiment of the first aspect, in some embodiments, further comprising
And controlling the ventilation temperature control system according to the data of temperature, humidity, air pressure, oxygen concentration, dust concentration and harmful gas concentration in the tunnel.
In combination with an embodiment of the first aspect, in some embodiments, further comprising
And (4) judging potential safety hazards according to monitoring of block falling, collapse and gushing of water on the tunnel face, monitoring of support cracking and block falling and monitoring of construction channel barrier monitoring data.
The invention has the beneficial effects that: the method for building the tunnel by the drilling and blasting method integrates a method for predicting surrounding rock in front of the tunnel face of the tunnel by the drilling and blasting method, a method for grading surrounding rock on the tunnel face, a method for designing, a method for constructing and a method for controlling construction quality, realizes the integrated and efficient cooperative management of the prediction of surrounding rock on the front of the tunnel face, the grading, the designing, the constructing and the controlling of construction quality, can effectively reduce the investment of constructors, improves the construction quality and the construction efficiency and reduces potential risks in the tunnel construction process.
Drawings
In order to more clearly explain the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that for those skilled in the art, other related drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a flowchart of an intelligent building method for a tunnel by a drilling and blasting method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a face front surrounding rock level prediction based on drilling parameters using a spatial mapping relationship according to an embodiment of the present application;
fig. 3 is a schematic diagram illustrating a prediction result of surrounding rock in front of a tunnel face by using multivariate information according to an embodiment of the present application;
FIG. 4 is a schematic diagram of a tunnel face surrounding rock grading model based on drilling parameters by using a deep neural network technology according to an embodiment of the present application;
FIG. 5 is a flow chart of a method for grading surrounding rocks according to an embodiment of the invention;
FIG. 6 is a graph of feature borehole selections provided by an embodiment of the present invention;
fig. 7 is a schematic diagram of drilling parameter acquisition according to an embodiment of the present invention.
FIG. 8 is a schematic view of a process of grading and modifying a surrounding rock on a working face using multivariate information according to an embodiment of the present disclosure;
FIG. 9 is a schematic view of a computational model based on a palm-side three-dimensional extreme equilibrium stability theory provided by an embodiment of the present application;
FIG. 10 is a schematic diagram of a full-section method provided in an embodiment of the present application;
fig. 11 is a schematic process flow diagram of a full cross-section method provided in an embodiment of the present application;
FIG. 12 is a schematic view of a micro-step method provided in an embodiment of the present application;
FIG. 13 is a schematic process flow diagram of a micro-step method provided in an embodiment of the present application;
fig. 14 is a schematic view of a construction quality classification control flow provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be described clearly and completely with reference to the accompanying drawings of the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
Thus, the following detailed description of the embodiments of the present invention, presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", and the like, indicate orientations and positional relationships based on those shown in the drawings, and are used only for convenience of description and simplicity of description, and do not indicate or imply that the equipment or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be considered as limiting the present invention.
Furthermore, the terms "first", "second" and "first" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless specifically defined otherwise.
In the present invention, unless otherwise expressly stated or limited, the terms "mounted," "connected," "secured," and the like are to be construed broadly and can, for example, be fixedly connected, detachably connected, or integrally formed; either directly or indirectly through intervening media, either internally or in any other relationship. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the present invention, unless otherwise expressly stated or limited, "above" or "below" a first feature means that the first and second features are in direct contact, or that the first and second features are not in direct contact but are in contact with each other via another feature therebetween. Also, the first feature being "on," "above" and "over" the second feature includes the first feature being directly on and obliquely above the second feature, or merely indicating that the first feature is at a higher level than the second feature. A first feature being "under," "below," and "beneath" a second feature includes the first feature being directly under and obliquely below the second feature, or simply meaning that the first feature is at a lesser elevation than the second feature.
Examples
FIG. 1 shows a flow diagram of one embodiment of a method for intelligent construction of a drill-and-blast tunnel according to the present disclosure. The intelligent construction method of the tunnel by the drilling and blasting method can be applied to the construction of the tunnel by the drilling and blasting method. As shown in fig. 1, the intelligent construction method of the drilling and blasting tunnel comprises the following steps:
The drilling jumbo can be used for acquiring drilling parameter information, advanced drilling information by means of geophysical prospecting and multivariate geological information of surrounding rock information in a prospecting and designing stage. And comprehensively utilizing a computer vision technology and a graphic space mapping technology to realize the prediction of the surrounding rock in front of the tunnel face, wherein a tunnel advanced geological prediction result schematic diagram utilizing multivariate information is shown in the figures 2 and 3, and a three-dimensional real-time visual surrounding rock geological BIM model is established.
And 102, acquiring a surrounding rock grading result of the face based on the digital imaging information of the face, the drilling parameter information and the advanced drilling information. Namely, a drilling and blasting tunnel face surrounding rock intelligent grading method based on multivariate geological information fusion analysis is utilized.
Here, the face digital imaging information may be a face geological sketch. The tunnel face surrounding rock classification is realized by utilizing the multi-element geological information of face digital imaging information, drilling parameter information of a drill jumbo and advanced drilling information (assisted by geophysical prospecting information) and comprehensively utilizing a computer vision technology and a machine learning technology, and a three-dimensional real-time visual surrounding rock geological BIM model is established.
The tunnel face surrounding rock grading model schematic diagram based on the drilling parameters by using the deep learning technology is shown in fig. 4, and the tunnel face surrounding rock grading and changing process schematic diagram by using the multivariate information is shown in fig. 8.
The tunnel face surrounding rock grading method based on the drilling parameters specifically comprises the following steps:
s1: and constructing a sample library, wherein the sample library comprises drilling parameters and surrounding rock levels of corresponding positions.
The surrounding rock grading sample library is composed of drilling parameters (DP for short) and surrounding rock grades.
In some specific embodiments, the drilling parameters include thrust speed, percussion pressure, thrust pressure, rotary pressure, water pressure, and water flow.
Each set of drilling parameters includes thrust speed, percussion pressure, thrust pressure, water pressure, and water flow rate for a particular drilling depth. The surrounding rock grade of the specific depth is in one-to-one correspondence with the set of drilling parameters.
Wherein the drilling parameters may be collected by sensors of the drill jumbo. The surrounding rock grade can be judged by adopting an artificial geological sketch method. According to the relevant regulations of railway tunnel design specifications (TB10003-2016), the field judgment of the surrounding rock level can be determined according to the face geological sketch result.
S2: and constructing a surrounding rock grading model based on a neural network, and substituting a sample library into the surrounding rock grading model for training.
For ease of understanding, the principle of the neural network is briefly described first, specifically as follows:
the artificial neural network is a new subject after the large-area popularization of computers, and is a complex computing method for simulating human brain neurons and neuron connection structures. The artificial neural network does not need to determine a mathematical equation of a mapping relation between input and output in advance, only through self training, a certain rule is learned, and a result which is closest to an expected output value is obtained when an input value is given.
The neural network generally consists of an input layer, a hidden layer and an output layer, wherein the layers are all interconnected, nodes of each layer are not connected, the number of the hidden layers can be multiple, the neural network is reconstructed by continuously and repeatedly deducing and then the final result is obtained.
For the deep neural network of the surrounding rock classification model, the number of network layers is set to be 5, namely an input layer, 3 hidden layers and an output layer. Wherein the input layer corresponds 6 drilling parameters, so there are 6 nodes, and the output layer corresponds the country rock level, so there are 1 node, and the number of hidden layer nodes is determined through research. A tangent function or a logarithmic function is selected as the transfer function (activation function of hidden layer), see fig. 5.
After the neural network is established, a large number of sample libraries are input to train the neural network, and when the square error of the target value and the actual value is smaller than the expectation, an available surrounding rock grading model is obtained.
Through a large amount of sample base data training, and the surrounding rock classification model has the self-learning function, along with the increase of the sample base data that produce in the work progress, the rate of accuracy constantly improves, has the characteristics that the accuracy is high, intelligent degree is high. In specific implementation, the data of the sample library is not less than 500 groups. The tunnel face stability and the surrounding rock grade are closely related, so the sample collection should be carried out by considering different surrounding rock grades, different lithology and different geological characteristics, and in principle, the number of samples of each surrounding rock grade should not be lower than 100 parts. For example: I. class II, III, IV, V wall rock 100.
It should be noted that the classification of the tunnel surrounding rock is to evaluate the surrounding rock property and judge the stability of the tunnel surrounding rock, and is used as a basis for selecting the position and the support type of the tunnel and guiding the safe construction. Specifically, the grade of the surrounding rock is: I. II, III, IV, V and VI. However, the vi-level surrounding rock is very rare in the actual tunnel engineering, because the most serious influence of the surrounding rock structure of the level is that the structure of the junction of the full-strong weathering zone of the crushing zone, the weathering joint dense joint surface and the combination thereof are disordered to form a large number of broken block bodies, and most of the broken block bodies are argillaceous filling, even in a stone-included soil shape or a soil-included stone shape, and the tunnel face is unstable in a short time when excavation is carried out, so the vi-level surrounding rock is basically eliminated in the tunnel addressing, and therefore the vi-level surrounding rock is not considered in the application.
S3: and inputting drilling parameters into the trained surrounding rock grading model to obtain the surrounding rock grade of the corresponding position.
The method for acquiring the drilling parameters specifically comprises the following steps:
s31: the face is divided into blocks and characteristic holes are selected respectively.
The inventor finds that the surrounding rock of the tunnel face is in a state of soft top and hard bottom and hard top and soft bottom.
In order to evaluate the grade of the surrounding rock in a refined manner, the face is divided into blocks according to the soft and hard stratum boundary of the face surrounding rock to form an upper section and a lower section, and the surrounding rock is judged in a grading manner respectively. Namely, the drilling parameters of the upper section and the lower section are input into the trained surrounding rock grading model to obtain the surrounding rock grades of the upper section and the lower section, so as to guide the design of tunnel supporting measures.
Illustratively, 3 characteristic holes are selected in the upper half section of the face, and 2 characteristic holes are selected in the lower half section of the face, as shown in fig. 6.
In the five groups of drilling parameters of the drill holes 1-5, the average value of the drilling parameters of the drill holes 1-3 can be taken as the drilling parameter for representing the upper half section, and the values of the drilling parameters of the drill holes 4 and 5 can be taken as the drilling parameter for representing the lower half section.
S32: and collecting the drilling parameters of the characteristic drilling holes once per preset drilling depth in the drilling process (drilling holes by using the drill jumbo). For example, the drilling parameters are collected every 0.02m during drilling by the drill jumbo, see fig. 7.
And 103, acquiring the grade and the burial depth of the surrounding rock, performing simulation calculation based on the tunnel theory of the drilling and blasting method, and determining tunnel design parameters. Namely an intelligent design method based on a drilling and blasting method tunnel construction design theory.
The method specifically comprises the steps of automatically calling auxiliary design software (ANSYS, FLAC and the like) to carry out simulation calculation according to automatically acquired parameters such as the grade of the surrounding rock, the burial depth and the like by using a drilling and blasting method tunnel theory and adopting technologies such as parametric modeling and cloud calculation, determining tunnel design parameters and establishing a three-dimensional real-time visual design BIM.
Here, the tunnel design parameters include forepoling design parameters, drilling and blasting design parameters, preliminary shoring and secondary lining design parameters.
The drilling and blasting method tunnel theory comprises a tunnel forepoling design method based on a tunnel face three-dimensional ultimate balance stability theory, a tunnel drilling and blasting optimization design method based on a tunnel engineering blasting theory, and a tunnel primary support and secondary lining design method based on a rock quality index (BQ) method deformation pressure theory.
Wherein, the schematic diagram of the calculation model based on the palm face three-dimensional limit equilibrium stability theory is shown in figure 9. The calculation formula is as follows:
in the formula: k is the face stability factor;
[K] the design stability coefficient of the tunnel face is 1.15 by referring to technical specifications of rock-soil anchor rod and shotcrete support engineering;
α1-the pipe shed force transfer coefficient;
P1-tunnel face bolting force;
α2the cohesive force enhancement coefficient of surrounding rock is pre-grouted on the tunnel face;
β1、β2、β3-and
the relevant coefficients;
Fc-slip plane cohesion force (kN);
Fq-vertical deformation pressure resultant (kN) of the slider;
Fw-the slider dead weight (kN);
α0-vertical deformation pressure reduction factor above the palm face sliding body;
q-vertical deformation pressure (kPa);
Le-unsupported segment lengths (m);
b-face span (m);
d-the height of the tunnel face (m);
c-surrounding rock cohesion (kPa);
Gamma-Severe rock Severe (kN/m)3)；
λ -lateral pressure coefficient.
The deformation pressure calculation formula based on the rock quality index (BQ) method is as follows:
q＝0.33γ(0.2+0.1B)e-0.006BQ+4.2
e＝2.7e-0.0066BQq
BQ＝100+3Rc+250Kv
in the formula: q-vertical pressure;
e-vertical pressure;
gamma-the wall rock severity;
b-tunnel span;
BQ-basic quality index of rock mass;
Rc-uniaxial saturated compressive strength of rock;
Kv-rock mass integrity index.
The tunnel drilling and blasting optimization design method based on the rock blasting theory is detailed in the following table 1:
table 1: drilling and blasting design parameter optimization method
And 104, acquiring data based on tunnel equipment, constructing the single machine of four operation work areas according to advance support, drilling and blasting excavation, primary support and secondary lining, and managing the space distribution of the single machines in different states in the tunnel during cluster operation. Intelligent construction method of drilling and blasting tunnel based on intelligent equipment
The single-machine construction of four working areas, namely, advanced support, drilling explosion excavation, primary support and secondary support, can be realized by utilizing tunnel equipment, such as an intelligent grouting trolley, an intelligent rock drilling trolley, an intelligent anchor rod trolley, an intelligent arch frame trolley, an intelligent spraying and mixing trolley, a waterproof board trolley, an intelligent lining trolley, an intelligent maintenance trolley and the like, and combining a construction method and a process of a full section method (a micro-step method); when the machine group works, the computer vision, the robot kinematics and the space accurate navigation positioning technology are comprehensively utilized, mutual interference is avoided through the space distribution management of different states (working, stopping and advancing) of each single machine in the tunnel, the cooperative work is realized, a three-dimensional real-time visual construction BIM model is established, and the all-round and real-time display of the construction process information and the construction equipment information is realized.
Wherein, the main functions of each device are detailed in the following table 2.
Table 2: equip the main function
The tunnel construction method mainly comprises 2 types of full-section method and micro-step method.
Wherein, the full section method is as follows: the construction method of tunnel full section construction according to design section once excavation shaping, the tunnel face can be set as the inclined plane of certain slope rate.
The three-dimensional schematic diagram of the full-section method and the construction process schematic diagram of the full-section method refer to the following figures 10, 11, 12 and 13.
The tunnel micro-step construction method is a construction method in which a tunnel face is arranged to be step-shaped and is formed by once excavation according to a designed section, the upper section and the lower section are constructed simultaneously during excavation, the length of a step is generally 3-5 m, and the height of the upper step is generally 1/2-2/3 of the height of the designed section.
And 105, classifying and controlling the tunnel construction quality based on an analytic hierarchy process.
The method specifically comprises the steps of automatically acquiring main construction quality information of the tunnel by using equipment, realizing classification management and control of tunnel construction quality by using an analytic hierarchy process, and visually presenting corresponding quality information through a construction BIM model.
The tunnel construction quality can be divided into 4 parts of quantity (blast hole quantity, anchor rod quantity and the like), size (blast hole length, lining thickness), position (blast hole arrangement, steel frame spacing and the like), and performance (strength, compactness and the like) according to control types, wherein quality information of the quantity, the size and the position can be automatically collected and transmitted through construction equipment, and real-time quality evaluation and control are realized by establishing a three-dimensional real-time visual construction BIM model and comparing the three-dimensional real-time visual construction BIM model with a design model; the performance quality information is automatically acquired and transmitted through detection equipment, and time delay evaluation and dynamic management and control are carried out by adopting a manual method according to related design requirements.
Based on 4 items of basic index information of advance support quality, drilling and blasting excavation quality, primary support quality and secondary lining quality, a tunnel construction quality classification control method is established, namely the tunnel construction quality is divided into SI (qualified), SII (basically qualified) and SIII (unqualified), and the process can refer to fig. 14.
Specifically, after 4 basic indexes of forepoling quality, drilling and blasting excavation quality, primary support quality and secondary lining quality are evaluated, a hierarchical structure is established according to an analytic hierarchy process, a structural index judgment matrix is graded according to experts, and after the consistency of the matrix is judged to be qualified through inspection, the weight of each index can be determined, so that the multi-index comprehensive evaluation of the next step can be performed.
For the tunnel construction quality classified as SI grade (qualified), an optimized design drawing can be adopted for construction; for SII (basically qualified), construction can be carried out by adopting a general design drawing; for SIII class (fail) shutdown and reconditioning are required.
And 106, evaluating the structure safety according to the stress-strain monitoring data and the deformation monitoring data of the tunnel structure.
The method specifically comprises the steps of utilizing means such as Internet of things, a monitoring robot, big data and cloud computing to achieve tunnel structure monitoring, construction environment monitoring and special potential safety hazard monitoring, displaying corresponding monitoring information on line by constructing a real-time three-dimensional visual monitoring BIM model, and achieving real-time evaluation and feedback of the monitoring information according to a related safety management control method, wherein the monitoring information is used for guiding prediction of surrounding rock in front of a tunnel face, classification, design, construction, checking and correction of related parameters.
The tunnel structure monitoring comprises stress-strain monitoring and deformation monitoring, automatic information acquisition and transmission are achieved through a sensor, a three-dimensional laser scanner, a monitoring robot and the like, and the structure safety is evaluated in real time according to a supporting structure safety evaluation method.
The safety management control method for monitoring the structural deformation adopts a sectional control principle, and the related standards are detailed in the following table 3.
TABLE 3 deformation segment control Standard
Note: b, tunnel excavation span; u shape0The initial support limit relative displacement value can be determined according to field measured data or railway tunnel monitoring and measuring technical regulation (Q/CR 9218).
And step 107, controlling the ventilation temperature control system according to the data of the temperature, the humidity, the air pressure, the oxygen concentration, the dust concentration and the harmful gas concentration in the tunnel.
The construction environment monitoring, namely the temperature, the humidity, the air pressure, the oxygen concentration, the dust concentration, the harmful gas concentration and the like in the tunnel, realizes the automatic information acquisition and transmission through various sensors in the tunnel, and automatically adjusts a ventilation temperature control system according to the corresponding control standard to realize the construction environment control.
And 108, monitoring the falling blocks, the collapse and the gushing water of the tunnel face, monitoring the cracking and falling blocks of the support and judging potential safety hazards according to the monitoring data of the obstacles of the construction passage.
The monitoring of the special potential safety hazards comprises monitoring of tunnel face chipping, collapse and gushing water, monitoring of support cracking and chipping, monitoring of construction channel barriers and the like, and the potential safety hazards are discovered immediately and controlled quickly mainly through video monitoring, computer vision and man-machine interaction.
By integrating a drilling and blasting method tunnel face front surrounding rock prediction method, a face surrounding rock grading method, a design method, a construction quality control method, a construction safety monitoring method and the like, comprehensively applying the Internet of things, big data, cloud computing and GIS + BIM modeling technologies, analyzing information flow relations among all parts and a system control method, and realizing the integration and high-efficiency cooperative management of face front surrounding rock prediction, face surrounding rock grading, design, construction quality control and construction safety monitoring.
Compared with the prior art, the invention has the following advantages:
1. the invention provides a drilling and blasting method tunnel construction method, which integrates a drilling and blasting method tunnel face front surrounding rock prediction method, a face surrounding rock grading method, a design method, a construction quality control method, a construction safety monitoring method and the like.
2. The surrounding rock grading method, the construction method and the like provided by the invention are realized based on manual technology, have self-learning and self-optimization functions, and can continuously improve the automation and degree along with popularization and application and iterative updating of results.
The above is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and variations may be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (9)
1. An intelligent construction method for a tunnel by a drilling and blasting method is characterized by comprising
Acquiring a tunnel advanced geological prediction result based on the drilling parameter information, the advanced drilling information and the surrounding rock information;
acquiring a tunnel face surrounding rock grading result based on tunnel face digital imaging information, drilling parameter information and advanced drilling information;
acquiring the grade and the burial depth of the surrounding rock, performing simulation calculation based on a drilling and blasting tunnel theory, and determining tunnel design parameters;
acquiring data based on tunnel equipment, performing single machine construction of four operation work areas, namely advanced support, drilling and blasting excavation, primary support and secondary lining, and performing space distribution management of each single machine in the tunnel in different states during cluster operation;
and (4) carrying out classified management and control on the tunnel construction quality based on an analytic hierarchy process.
2. The intelligent construction method of a drill-and-blast tunnel according to claim 1, wherein the face digital imaging information comprises a face geological sketch.
3. The intelligent construction method of the drilling and blasting tunnel according to claim 1, wherein the tunnel design parameters comprise forepoling design parameters, drilling and blasting design parameters, primary support and secondary lining design parameters.
4. The intelligent construction method of the drilling and blasting tunnel according to claim 1, wherein the tunnel equipment comprises a grouting trolley, a rock drilling trolley, a rock bolting trolley, an arch trolley, a spraying and mixing trolley, a waterproof plate trolley, a lining trolley and a maintenance trolley.
5. The intelligent construction method of the drilling and blasting tunnel according to claim 1, wherein the classification management and control of the tunnel construction quality based on the analytic hierarchy process comprises
Acquiring construction quality information according to tunnel equipment;
classifying the tunnel construction quality according to the quantity, the size, the position and the performance, and carrying out classified control on the tunnel construction quality based on an analytic hierarchy process;
based on 4 items of basic index information of advanced support quality, drilling and blasting excavation quality, primary support quality and secondary lining quality, a tunnel construction quality classification control method is established, and tunnel construction quality is divided into qualified, basically qualified and unqualified.
6. The intelligent building method of the drilling and blasting tunnel according to claim 1, further comprising
And evaluating the structure safety according to the stress-strain monitoring data and the deformation monitoring data of the tunnel structure.
7. The intelligent construction method of the drilling and blasting tunnel according to claim 6, wherein the safety management control method for monitoring the structural deformation adopts a sectional control principle, and the relevant standards are detailed in the following table:
deformation segment control standard
Note: b, tunnel excavation span; u shape0The initial support limit relative displacement value can be determined according to field measured data or railway tunnel monitoring and measuring technical regulation (Q/CR 9218).
8. The intelligent building method of the drilling and blasting tunnel according to claim 1, further comprising
And controlling the ventilation temperature control system according to the data of temperature, humidity, air pressure, oxygen concentration, dust concentration and harmful gas concentration in the tunnel.
9. The intelligent building method of the drilling and blasting tunnel according to claim 1, further comprising
And (4) judging potential safety hazards according to monitoring of block falling, collapse and gushing of water on the tunnel face, monitoring of support cracking and block falling and monitoring of construction channel barrier monitoring data.
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| CN112878981A (en) * | 2021-01-28 | 2021-06-01 | 中国矿业大学 | Control system and control method of drill jumbo |
| CN113269713A (en) * | 2021-04-07 | 2021-08-17 | 西南交通大学 | Intelligent recognition method and determination device for tunnel face underground water outlet form |
| CN113446009A (en) * | 2021-06-01 | 2021-09-28 | 北京市政建设集团有限责任公司 | Intelligent shallow-buried underground excavation operation method and equipment and storage medium |
| CN113467315A (en) * | 2021-07-16 | 2021-10-01 | 中交投资南京有限公司 | BIM technology-based tunnel engineering automatic monitoring control method and system |
| CN113899268A (en) * | 2021-09-14 | 2022-01-07 | 中交路桥建设有限公司 | Optimized construction method for arrangement of blast holes on blasting section of tunnel |
| CN114352300A (en) * | 2021-12-07 | 2022-04-15 | 江苏徐工工程机械研究院有限公司 | Digital drilling and blasting excavation system and excavation method |
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| CN114547721A (en) * | 2021-12-21 | 2022-05-27 | 沈阳工业大学 | Blasting control method for differential directional fracture of local area of deep-buried tunnel |
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| CN112160767A (en) * | 2020-11-05 | 2021-01-01 | 重庆大学 | Tunneling construction method combining mechanical-chemical corrosion-hydraulic cutting of tunnel |
| CN112160767B (en) * | 2020-11-05 | 2022-05-27 | 重庆大学 | Tunneling construction method combining mechanical-chemical corrosion-hydraulic cutting of tunnel |
| CN112878981A (en) * | 2021-01-28 | 2021-06-01 | 中国矿业大学 | Control system and control method of drill jumbo |
| CN113269713A (en) * | 2021-04-07 | 2021-08-17 | 西南交通大学 | Intelligent recognition method and determination device for tunnel face underground water outlet form |
| CN113446009B (en) * | 2021-06-01 | 2023-06-27 | 北京市政建设集团有限责任公司 | Intelligent shallow buried underground excavation operation method, equipment and storage medium |
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| CN114352300A (en) * | 2021-12-07 | 2022-04-15 | 江苏徐工工程机械研究院有限公司 | Digital drilling and blasting excavation system and excavation method |
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| CN114439500B (en) * | 2021-12-16 | 2023-09-05 | 山东大学 | TBM (Tunnel boring machine) tunneling system and method for crossing unfavorable geology based on while-drilling test |
| CN114439500A (en) * | 2021-12-16 | 2022-05-06 | 山东大学 | TBM (tunnel boring machine) through unfavorable geology intelligent tunneling system and method based on while-drilling test |
| CN114547721B (en) * | 2021-12-21 | 2022-10-25 | 沈阳工业大学 | Blasting control method for differential directional fracture of local area of deep-buried tunnel |
| CN114547721A (en) * | 2021-12-21 | 2022-05-27 | 沈阳工业大学 | Blasting control method for differential directional fracture of local area of deep-buried tunnel |
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