Slope stability monitoring system and method for deep foundation pit excavation construction of ship lock main body in mudstone area

Abstract

The application discloses a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring system and method, the monitoring system comprises a remote sensing information acquisition module, an information transmission module, a data preprocessing module, a data analysis module, an image recognition module, a numerical simulation module, a grouting reinforcement module, a decision module and a data storage module; the monitoring method comprises the following steps: establishing a three-dimensional model of the surface shape of the slope, monitoring and controlling the shape of the slope, monitoring and controlling the deformation of the slope, identifying the image features, calculating the stability of the slope, predicting the control amount and grouting reinforcement; the three-dimensional model of the surface shape of the slope is established to analyze the geometric shape of the slope and the change amount thereof, the image recognition is performed on the construction geological conditions, the stratum physical and mechanical state data are acquired, the numerical simulation model is established, the stability of the slope is calculated in real time, then the grouting reinforcement control amount is predicted and controlled, and the automation, accuracy and high efficiency of the slope monitoring control operation of the deep foundation pit near water are realized.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of control system, and relates to a slope stability monitoring system and method for deep foundation pit excavation construction of a ship lock main body in a mudstone area. BACKGROUND

[0002] Due to the large scale of the ship lock main body structure, the need for cofferdam protection during water construction, and the need for slope excavation, the scale and excavation depth of the foundation pit required during the construction of the ship lock main body are large, and the shape of the foundation pit is complex. The temporary high slope of the foundation pit is prone to landslides, foundation pit water gushing, or cofferdam seepage damage under the action of rock and soil weight, construction excavation disturbance, groundwater seepage, and low-strength mudstone geological conditions, which seriously affects the construction quality and progress, and even causes loss of life and property of construction personnel. Therefore, the monitoring and control of the slope stability of the deep foundation pit excavation construction of the ship lock main body in the mudstone area is particularly important.

[0003] The mudstone stratum is formed by compaction and recrystallization of various types of clay materials or rock debris. The complex composition makes the mudstone stratum present geological structure inhomogeneity, mechanical property inhomogeneity, and permeability inhomogeneity. The inhomogeneity of the mudstone stratum is manifested in the appearance of various textures and colors. Current analysis of mudstone stratum conditions during water construction of deep foundation pits mainly relies on visual identification and experience judgment of technical personnel, which is difficult to objectively, accurately and efficiently quantitatively analyze the mudstone stratum conditions, and cannot provide guidance and reference for the slope stability of the deep foundation pit excavation construction of the ship lock main body in the mudstone area.

[0004] Limited by technical level and labor cost, the current temporary high slope monitoring method in deep foundation pit excavation construction focuses on observing the displacement of the slope surface or measuring the deformation of the slope interior through a limited number of drill holes. These monitoring methods can only collect simple, single and limited data, and are difficult to quantitatively and comprehensively reflect the slope stability and seepage stability.

[0005] In addition, the existing temporary high slope monitoring method mainly adopts manual regular inspection. Since manual regular inspection cannot continuously and comprehensively monitor the slope construction area, and is limited by the subjectivity, working accuracy and efficiency of technical personnel, it is difficult to guarantee the quality and efficiency of the temporary high slope monitoring and control of the deep foundation pit of the ship lock main body in the mudstone area. SUMMARY

[0006] In view of the deficiencies of the prior art, the present application provides a slope stability monitoring system and method for deep foundation pit excavation construction of a ship lock main body in a mudstone area, which is suitable for temporary high slope monitoring and control during water construction of deep foundation pits in mudstone stratum conditions, and is beneficial to improving the informatization construction level, construction efficiency and safety and reliability of the deep foundation pit excavation construction of the ship lock main body in the mudstone area.

[0007] The first aspect of the application discloses a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring system, which comprises a remote sensing information acquisition module, an information transmission module, a data preprocessing module, a data analysis module, an image recognition module, a numerical simulation module, a grouting reinforcement module, a decision module and a data storage module.

[0008] The remote sensing information acquisition module is mounted on a UAV; the remote sensing information acquisition module includes but is not limited to a distance measuring sensor, an optical camera sensor and an infrared camera sensor; the distance measuring sensor is used to obtain the surface geometric shape data of the temporary high slope of the ship lock main body deep foundation pit through a non-contact measurement means, the optical camera sensor is used to obtain high-precision image data, and the infrared camera sensor is used to indirectly obtain underground water level data by measuring temperature;

[0009] The information transmission module is used to establish remote connection and transmission of information between modules, and to send alarm information to construction technical personnel;

[0010] The data preprocessing module is used to preprocess the original data obtained by the remote sensing information acquisition module;

[0011] The data analysis module is used to operate the non-image data processed by the data preprocessing module and obtain a first analysis result; the first analysis result includes but is not limited to a slope surface shape three-dimensional model, a slope height, a slope gradient and seepage field data;

[0012] The image recognition module adopts a convolutional neural network model technology to recognize image features of the image data processed by the data preprocessing module, and the image features include but are not limited to mudstone stratigraphic layering conditions and mechanical property parameters of each layer, the shape and spatial distribution of rock and soil fissures, and the shape and spatial distribution of seepage;

[0013] The numerical simulation module is used to establish a numerical simulation model according to the slope surface shape three-dimensional model and the image features, and to obtain a second analysis result by calculating the numerical simulation model, the second analysis result includes but is not limited to a slope anti-sliding stability coefficient, a sudden gushing stability coefficient and a flow soil stability coefficient;

[0014] The grouting reinforcement module comprises a plurality of steel flower pipes, a cement slurry pool, a pumping device, a hose and cement slurry, the steel flower pipes are installed in the slope stratum through vertical drilling, the cement slurry pool is located around the slope construction area, the steel flower pipes are connected with the cement slurry pool through the hose, the pumping device is installed on the hose, and the cement slurry is prepared and stored in the cement slurry pool;

[0015] The decision module adopts a deep neural network model technology, and predicts a grouting reinforcement control quantity according to the slope surface shape three-dimensional model, the seepage field data and the second analysis result, and controls the grouting reinforcement module according to the grouting reinforcement control quantity; the grouting reinforcement control quantity includes but is not limited to the number of steel flower pipes needing grouting, the grouting pressure and the grouting quantity.

[0016] The data storage module is used for storing the data processed by the data preprocessing module, the first analysis result, the second analysis result and the grouting reinforcement control quantity.

[0017] The second aspect of the application discloses a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring method, comprising the following steps:

[0018] S100, the establishment of the slope surface shape three-dimensional model: the surface geometric shape data of the temporary high slope of the ship lock main body deep foundation pit is obtained by the distance measuring sensor, and after preprocessing by the data preprocessing module, the data analysis module establishes a slope surface shape three-dimensional model M n For [X n , Y n , Z n ], and then the slope height measured value and the slope gradient measured value are obtained;

[0019] S200, slope shape monitoring and control: when the deviation between the slope height measured value and the slope height design value exceeds the design requirement, or when the deviation between the slope gradient measured value and the slope gradient design value exceeds the design requirement, the information transmission module sends alarm information to the construction technical personnel, until the slope height measured value and the slope gradient measured value meet the design requirements through slope finishing operation;

[0020] S300, slope deformation monitoring and control: after t time, the slope surface shape three-dimensional model M n+t is updated to [X n+t , Y n+t , Z n+t ]; according to the relative relationship between M n and M n+t , the slope displacement amount ΔL, the displacement velocity V and the slope change amount Δα in the t time period are obtained; when the slope displacement amount ΔL, the displacement velocity V or the slope change amount Δα in the t time period exceeds the design requirement, the information transmission module sends alarm information to the construction technical personnel, until the slope displacement amount ΔL, the displacement velocity V and the slope change amount Δα in the t time period meet the design requirements;

[0021] S400, image feature recognition: image data of the temporary high slope of the ship lock main body deep foundation pit is acquired by the optical camera sensor, after pre-processing by the data preprocessing module, image features are acquired by the image recognition module, the image features include but are not limited to stratified condition of mudstone stratum and mechanical property parameters of each layer, form and spatial distribution of rock and soil fissure, form and spatial distribution of water seepage;

[0022] S500, slope stability calculation: groundwater level data is indirectly acquired by the infrared camera sensor, after pre-processing by the data preprocessing module, seepage field data is obtained by the data analysis module; according to the three-dimensional model of the slope surface shape, the seepage field data and the image features, a numerical simulation model is established by the numerical simulation module, a second analysis result is obtained by calculating the numerical simulation model, the second analysis result includes but is not limited to slope anti-sliding stability coefficient, sudden gushing stability coefficient and flow soil stability coefficient;

[0023] S600, prediction of control quantity: according to the three-dimensional model of the slope surface shape, the seepage field data and the second analysis result, the grouting reinforcement control quantity is predicted by the decision module; the grouting reinforcement control quantity includes but is not limited to the number of steel flower pipes that need to be grouted, grouting pressure and grouting quantity;

[0024] S700, grouting reinforcement: according to the grouting reinforcement control quantity, the grouting reinforcement module is controlled, so as to carry out grouting reinforcement operation.

[0025] Compared with the prior art, the beneficial effects of the present application are: for the temporary high slope monitoring and control in the deep foundation pit excavation construction process of the ship lock main body in the mudstone area, a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring system is disclosed, which comprises a remote sensing information acquisition module, an information transmission module, a data preprocessing module, a data analysis module, an image recognition module, a numerical simulation module, a grouting reinforcement module, a decision module and a data storage module; wherein, the surface geometric shape data, image data and underground water level data of the temporary high slope of the ship lock main body deep foundation pit are obtained through the remote sensing information acquisition module, the image recognition module is used to identify the image and obtain the physical and mechanical state data of the slope stratum, the data analysis module and the numerical simulation module are used to quantitatively analyze the slope shape, deformation and stability, and finally the reasonable grouting reinforcement control amount is predicted according to the analysis result through the decision module, so as to realize the accurate control of the grouting reinforcement module; in addition, the mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring method is also disclosed, which comprises the establishment of the three-dimensional model of the slope surface shape, the slope shape monitoring and control, the slope deformation monitoring and control, the identification of the image features, the slope stability calculation, the control amount prediction and the grouting reinforcement; the three-dimensional model of the slope surface shape is established according to the data obtained by the remote sensing information acquisition module to analyze the geometric shape of the slope and its change amount, so as to realize the automation, real-time and high efficiency of the slope shape and deformation monitoring and control; the image recognition is carried out on the construction geological conditions to obtain the physical and mechanical state data of the stratum, then the numerical simulation model is established and the slope stability is calculated in real time, then the neural network technology is used to predict the grouting reinforcement control amount, and then the grouting reinforcement module is controlled and the automation and accuracy of the slope grouting reinforcement operation are realized, and finally the automation, accuracy and high efficiency of the mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring and control operation are realized. BRIEF DESCRIPTION OF DRAWINGS

[0026] Fig. 1 It is a connection diagram of the mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring system of the present application;

[0027] Fig. 2 It is a flow chart of the mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring method of the present application;

[0028] Fig. 3 It is a cross-sectional view of the temporary high slope of the mudstone area ship lock main body deep foundation pit shown in the embodiment of the present application;

[0029] Reference numerals: 11-Remote sensing information acquisition module, 111-Distance sensor, 112-Optical camera sensor, 113-Infrared camera sensor, 12-Information transmission module, 13-Data preprocessing module, 14-Data analysis module, 15-Image recognition module, 16-Numerical simulation module, 17-Decision module, 18-Grouting reinforcement module, 181-Steel pipe, 182-Cement slurry pool, 183-Pumping device, 184-Hose, 185-Cement slurry, 19-Data storage module, 21-Slope, 22-Cofferdam, 23-Water surface, 24-Ship lock body. Detailed Implementation

[0030] The embodiments of the present invention will be described in more detail below with reference to the accompanying drawings and reference numerals, so that those skilled in the art can implement them after reading this specification. It should be understood that the specific embodiments described herein are only for explaining the present invention and are not intended to limit the present invention.

[0031] The first aspect of this application discloses as follows: Figs. 1-3 The system shown is a monitoring system for slope stability during the excavation of the deep foundation pit of the main body of the ship lock in the mudstone area. The system includes a remote sensing information acquisition module 11, an information transmission module 12, a data preprocessing module 13, a data analysis module 14, an image recognition module 15, a numerical simulation module 16, a grouting reinforcement module 18, a decision-making module 17, and a data storage module 19.

[0032] The remote sensing information acquisition module 11 is mounted on a UAV; the remote sensing information acquisition module 11 includes, but is not limited to, a ranging sensor 111, an optical camera sensor 112, and an infrared camera sensor 113; the ranging sensor 111 is used to acquire surface geometric data of the temporary high slope 21 of the deep foundation pit of the lock body through non-contact measurement means, the optical camera sensor 112 is used to acquire high-precision image data, and the infrared camera sensor 113 is used to indirectly acquire groundwater level data by measuring temperature;

[0033] The information transmission module 12 is used to establish remote connections and transmission of information between modules, and to send alarm information to construction technicians;

[0034] The data preprocessing module 13 is used to preprocess the raw data acquired by the remote sensing information acquisition module 11;

[0035] The data analysis module 14 is used to perform calculations on the non-image data processed by the data preprocessing module 13 and obtain a first analysis result; the first analysis result includes, but is not limited to, a three-dimensional model of the slope surface shape, slope height, slope gradient, and seepage field data;

[0036] The image recognition module 15 adopts a convolutional neural network model technology to recognize image features of the image data processed by the data preprocessing module 13, and the image features include but are not limited to the layered state of the mudstone formation, the mechanical property parameters of each layer, the shape and spatial distribution of the rock and soil fissures, and the shape and spatial distribution of the water seepage.

[0037] The numerical simulation module 16 is configured to establish a numerical simulation model according to the three-dimensional model of the slope surface shape and the image features, and obtain a second analysis result by calculating the numerical simulation model, wherein the second analysis result includes but is not limited to the slope anti-sliding stability coefficient, the sudden gushing stability coefficient, and the soil flow stability coefficient.

[0038] The grouting reinforcement module 18 includes a plurality of steel flower pipes 181, a cement slurry pool 182, a pumping device 183, a hose 184, and cement slurry 185. The steel flower pipes 181 are installed in the formation of the slope 21 through vertical drilling. The cement slurry pool 182 is located around the slope construction area. The steel flower pipes 181 are connected to the cement slurry pool 182 through the hose 184. The pumping device 184 is installed on the hose. The cement slurry 185 is prepared and stored in the cement slurry pool 182.

[0039] The decision module 17 adopts a deep neural network model technology to predict the grouting reinforcement control amount according to the three-dimensional model of the slope surface shape, the seepage field data, and the second analysis result, and controls the grouting reinforcement module 18 according to the grouting reinforcement control amount. The grouting reinforcement control amount includes but is not limited to the number of steel flower pipes that need to be grouted, the grouting pressure, and the grouting amount.

[0040] The data storage module 19 is configured to store the data processed by the data preprocessing module 13, the first analysis result, the second analysis result, and the grouting reinforcement control amount.

[0041] The second aspect of the present application discloses a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring method as shown in the accompanying drawings, which comprises the following steps: Figs. 2-3 The second aspect of the present application discloses a mudstone area ship lock main body deep foundation pit excavation construction slope stability monitoring method as shown in the accompanying drawings, which comprises the following steps:

[0042] S100, the three-dimensional model of the slope surface shape is established: the surface geometric shape data of the temporary high slope 21 of the ship lock main body deep foundation pit is acquired by the distance measuring sensor 111, and after being preprocessed by the data preprocessing module, the three-dimensional model M of the slope surface shape is established by the data analysis module 14. n For [X n , Y n , Z n ], and then the measured value of the slope height and the measured value of the slope gradient are obtained.

[0043] S200, slope shape monitoring and control: when the deviation between the measured value of the slope height and the design value of the slope height exceeds the design requirement, or when the deviation between the measured value of the slope gradient and the design value of the slope gradient exceeds the design requirement, an alarm information is sent to the construction technical personnel through the information transmission module 12 until the measured value of the slope height and the measured value of the slope gradient meet the design requirements through slope trimming operation;

[0044] S300, slope deformation monitoring and control: after t time, the three-dimensional model M n+t of the slope surface shape is updated to [X n+t , Y n+t , Z n+t ]; according to the relative relationship between M n and M n+t , the slope displacement ΔL, the displacement velocity V and the slope change Δα in the t period are obtained; when the slope displacement ΔL, the displacement velocity V or the slope change Δα in the t period exceeds the design requirement, an alarm information is sent to the construction technical personnel through the information transmission module 12 until the slope displacement ΔL, the displacement velocity V and the slope change Δα in the t period meet the design requirements;

[0045] S400, image feature recognition: the image data of the temporary high slope 21 of the ship lock main body deep foundation pit is obtained through the optical camera sensor 112, and after preprocessing by the data preprocessing module 13, the image features are obtained by the image recognition module 15, which include but are not limited to the stratification condition of mudstone stratum and the mechanical property parameters of each layer, the shape and spatial distribution of rock and soil fissure, and the shape and spatial distribution of water seepage;

[0046] S500, slope stability calculation: the underground water level data is indirectly obtained through the infrared camera sensor 113, and after preprocessing by the data preprocessing module 13, the seepage field data is obtained by the data analysis module 14; according to the three-dimensional model of the slope surface shape, the seepage field data and the image features, the numerical simulation model is established by the numerical simulation module 16, and the second analysis result is obtained by calculating the numerical simulation model, which includes but is not limited to the slope anti-sliding stability coefficient, the sudden gushing stability coefficient and the flow soil stability coefficient;

[0047] S600, prediction of control amount: according to the three-dimensional model of the slope surface shape, the seepage field data and the second analysis result, the grouting reinforcement control amount is predicted by the decision module 17; the grouting reinforcement control amount includes but is not limited to the number of steel flower pipes that need to be grouted, the grouting pressure and the grouting amount;

[0048] S700, grouting reinforcement: according to the grouting reinforcement control quantity, the grouting reinforcement module 18 is controlled, so as to carry out grouting reinforcement work.

[0049] It can be seen that the three-dimensional model of the slope surface shape is established according to the data obtained by the remote sensing information acquisition module to analyze the geometric shape of the slope and the change amount, realize the automation, real-time and high efficiency of the slope shape and deformation monitoring and control; the image recognition is carried out on the construction geological conditions, the stratum physical and mechanical state data is obtained, then the numerical simulation model is established and the real-time calculation of the slope stability is carried out, then the neural network technology is used to predict the grouting reinforcement control quantity, and the grouting reinforcement module is controlled and the automation and precision of the slope grouting reinforcement work are realized, and finally the automation, precision and high efficiency of the slope stability monitoring and control work of the mudstone area ship lock main body deep foundation pit excavation construction are realized.

[0050] The above is one or more embodiments of the present application, which is described in more detail and in detail, but cannot be understood as a limitation on the scope of the patent of the present application. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of protection of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

Claims

1. A slope stability monitoring system for the excavation of a deep foundation pit for a ship lock main body in a mudstone area, characterized in that, The system comprises a remote sensing information acquisition module, an information transmission module, a data preprocessing module, a data analysis module, an image recognition module, a numerical simulation module, a grouting reinforcement module, a decision module and a data storage module. The remote sensing information acquisition module is mounted on the unmanned aerial vehicle; the remote sensing information acquisition module comprises but is not limited to a ranging sensor, an optical camera sensor and an infrared camera sensor; the ranging sensor is used to obtain the surface geometric shape data of the temporary high side slope of the ship lock main body deep foundation pit by non-contact measurement means, the optical camera sensor is used to obtain high-precision image data, and the infrared camera sensor is used to indirectly obtain underground water level data by measuring temperature. The information transmission module is used to establish remote connection and transmission of information between modules, and to send alarm information to construction technical personnel. The data preprocessing module is used to preprocess the original data obtained by the remote sensing information acquisition module. The data analysis module is used to operate the non-image data processed by the data preprocessing module and obtain a first analysis result; the first analysis result comprises but is not limited to a side slope surface shape three-dimensional model, a side slope height, a side slope gradient and seepage field data. The image recognition module adopts a convolutional neural network model technology to recognize image features of the image data processed by the data preprocessing module. The numerical simulation module is used to establish a numerical simulation model according to the side slope surface shape three-dimensional model and the image features, and to obtain a second analysis result by calculating the numerical simulation model. The grouting reinforcement module comprises a plurality of steel flower pipes, a cement slurry pool, a pumping device, a hose and cement slurry; the steel flower pipes are installed in the side slope stratum through vertical drilling, the cement slurry pool is located around the side slope construction area, the steel flower pipes are connected with the cement slurry pool through the hose, the pumping device is installed on the hose, and the cement slurry is prepared and stored in the cement slurry pool. The decision module adopts a deep neural network model technology to predict the grouting reinforcement control quantity according to the side slope surface shape three-dimensional model, the seepage field data and the second analysis result, and controls the grouting reinforcement module according to the grouting reinforcement control quantity. The data storage module is used to store the data processed by the data preprocessing module, the first analysis result, the second analysis result and the grouting reinforcement control quantity.

2. The slope stability monitoring system for the main body deep foundation pit excavation construction of the ship lock in the mudstone area according to claim 1, characterized in that: The image features comprise but are not limited to the stratification condition of mudstone stratum and the mechanical property parameters of each layer, the shape and spatial distribution of rock and soil cracks, and the shape and spatial distribution of seepage.

3. The slope stability monitoring system for the main body deep foundation pit excavation construction of the ship lock in the mudstone area according to claim 1, characterized in that: The second analysis result comprises but is not limited to a side slope anti-sliding stability coefficient, a sudden gushing stability coefficient and a flow soil stability coefficient.

4. The mudstone area ship lock body deep foundation pit excavation construction slope stability monitoring system according to claim 1, characterized in that: The grouting reinforcement control quantity comprises but is not limited to the number of steel flower pipes that need to be grouted, the grouting pressure and the grouting amount.

5. A monitoring method characterized by, The monitoring method for the mudstone area ship lock main body deep foundation pit excavation construction side slope stability monitoring system according to any one of claims 1-4 comprises the following steps: S100, the three-dimensional model of the slope surface shape is established: the surface geometric shape data of the temporary high slope of the ship lock main body deep foundation pit is acquired by the ranging sensor, and after being preprocessed by the data preprocessing module, the three-dimensional model M of the slope surface shape is established by the data analysis module n to [X n , Y n , Z n ], and then the measured value of the slope height and the measured value of the slope gradient are acquired; S200, slope shape monitoring and control: when the deviation between the measured value of the slope height and the design value of the slope height exceeds the design requirement, or when the deviation between the measured value of the slope gradient and the design value of the slope gradient exceeds the design requirement, an alarm information is sent to the construction technical personnel through the information transmission module until the measured value of the slope height and the measured value of the slope gradient meet the design requirements through slope trimming operation; S300, slope deformation monitoring and control: after t time, the three-dimensional model M of the slope surface shape n+t is updated to [X n+t , Y n+t , Z n+t ]; according to the relative relationship between M n and M n+t , the slope displacement ΔL, displacement velocity V and slope change Δα in the t time period are obtained; when the slope displacement ΔL, displacement velocity V or slope change Δα in the t time period exceeds the design requirement, the information transmission module sends an alarm information to the construction technical personnel, until the slope displacement ΔL, displacement velocity V and slope change Δα in the t time period meet the design requirement. S400, image feature recognition: image data of the temporary high slope of the ship lock main body deep foundation pit is obtained through the optical camera sensor, and after preprocessing by the data preprocessing module, the image feature is obtained by the image recognition module; S500, slope stability calculation: groundwater level data is indirectly obtained through the infrared camera sensor, and after preprocessing by the data preprocessing module, seepage field data is obtained by the data analysis module; according to the three-dimensional model of the slope surface shape, the seepage field data and the image feature, a numerical simulation model is established by the numerical simulation module, and a second analysis result is obtained by calculating the numerical simulation model; S600, prediction of control quantity: according to the three-dimensional model of the slope surface shape, the seepage field data and the second analysis result, the grouting reinforcement control quantity is predicted by the decision module; S700, grouting reinforcement: the grouting reinforcement module is controlled according to the grouting reinforcement control quantity, so as to carry out grouting reinforcement operation.

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