A relay automatic drainage system for reverse slope excavation of tunnels

Abstract

The present invention relates to the technical field of tunnel drainage systems, and in particular to a tunnel reverse slope excavation relay automatic drainage system, comprising a monitoring platform, and a multi-level drainage unit and a plurality of spare drainage units respectively controlled by the monitoring platform and arranged in the tunnel, wherein the monitoring platform comprises an algorithm module, a switching control module, a data acquisition control module and a learning module; the algorithm module is used to calculate the data uploaded by the data acquisition control module, respectively evaluate the working state and working trend of each drainage unit, and then according to the plurality of working states and working trends, the algorithm module respectively calculates a risk factor for each drainage unit, sorts the plurality of risk factors from large to small, predicts the drainage unit that will have problems according to the size of the risk factor, switches the drainage unit whose risk factor exceeds the risk threshold to the spare drainage unit, realizes the prediction of the risk, and ensures the safety and progress of the reverse slope construction.

Description

Technical Field

[0001] The invention belongs to the technical field of tunnel drainage, and in particular relates to a tunnel reverse slope excavation relay type automatic drainage system. Background Art

[0002] The reverse slope drainage system is a drainage system set up during tunnel construction to drain wastewater generated by construction in the tunnel or natural water encountered in the mountains during construction. The drainage slope of this system is opposite to the construction slope of the tunnel itself, that is, the accumulated water in the tunnel needs to be lifted and discharged from the tunnel with the help of graded mechanical drainage equipment (such as submersible pumps, drainage pumps, etc.).

[0003] However, because of the cooperation of multiple drainage units, the effective operation and coordination of each drainage system become particularly important. In the multi-level drainage architecture, the performance status of each drainage unit directly affects the efficiency and reliability of the entire drainage system. For example, if a drainage unit (such as a water collection well, drainage pipe or pump) at a certain level is blocked, leaked or fails, it will not only directly affect the drainage effect at this level, but may also cause the upper drainage system to overload due to rising water levels, and even trigger a chain reaction, paralyzing the entire drainage system, seriously threatening the safety and progress of the reverse slope construction.

[0004] In view of this, the prior art attempts to use monitoring means to identify the drainage unit with problems and then use spare drainage units to replace the drainage units with problems for subsequent drainage. However, the existing monitoring means mostly focus on monitoring the operating status of a single drainage unit, such as by installing sensors to monitor water level changes, pump working status, etc., but this decentralized monitoring method is difficult to achieve efficient overall management of the entire multi-level drainage system. Therefore, it is often necessary to manually check and replace the drainage units with problems one by one, and the response speed is slow. If the construction environment of the face encounters mountain water or fountains, the drainage pressure inside the tunnel will be extremely high in a very short time, and the manual switching of the spare drainage unit has a slow response, and it is difficult to complete the short-time switching, which greatly reduces the emergency handling capacity and overall operation efficiency of the drainage system. In the reverse slope relay drainage method of the tunnel, there are differences in the damage frequency of drainage units at different heights, and as the tunnel is constructed forward, the pressure on the drainage unit will also change. The prior art cannot carry out targeted monitoring of drainage units at different terrain heights, and thus cannot timely discover the drainage units with problems for adjustment.

[0005] Therefore, a tunnel reverse slope excavation relay type automatic drainage system is needed to solve the above problems. Summary of the invention

[0006] In order to solve the above problems existing in the prior art, the present invention provides a tunnel reverse slope excavation relay type automatic drainage system.

[0007] The purpose of the present invention can be achieved through the following technical solutions:

[0008] A tunnel reverse slope excavation relay type automatic drainage system, comprising a monitoring platform, and a multi-stage drainage unit and a plurality of spare drainage units respectively controlled by the monitoring platform and arranged in the tunnel, wherein the monitoring platform comprises an algorithm module and a switching control module, a data acquisition control module and a learning module respectively electrically connected to the algorithm module;

[0009] The data acquisition control module is used to collect environmental parameters, operating parameters of each drainage unit, operating parameters of connection nodes between drainage units, and construction parameters of the tunnel face;

[0010] The algorithm module is used to calculate the data uploaded by the data acquisition control module, evaluate the working status and working trend of each drainage unit respectively, and then calculate the risk factor of each drainage unit according to the multiple working statuses and working trends, and sort the multiple risk factors from large to small;

[0011] The data acquisition control module adjusts the acquisition frequency of the operating parameters of different drainage units according to the size of the risk factor;

[0012] The algorithm module is also used to switch the drainage unit instruction switching control module whose risk factor is greater than the risk factor threshold;

[0013] The switching control module is used to respond to the instruction of the monitoring platform to switch the drainage unit that needs to be switched to the standby drainage unit;

[0014] The learning module is used to update the drainage unit, and the update content of the learning module includes the newly added drainage unit and the update of the drainage path generated after the switching control module controls the switching.

[0015] Preferably, the monitoring platform also includes monitoring the status of the switched original drainage unit, and restoring the repaired original drainage unit instruction switching control module, and the learning module updates the drainage path again.

[0016] Preferably, the operating parameters of the plurality of drainage units include drainage pipe pressure data, flow data, water level data and component status data;

[0017] The environmental parameters include location data, topographic data, and the construction angle of the tunnel construction surface compared to the horizontal plane;

[0018] The construction parameters include construction water, a three-dimensional laser scanning image of the tunnel face, construction progress and the volume of construction water. The three-dimensional laser scanning image of the tunnel face includes the location and volume of mountain water appearing on the tunnel face.

[0019] Preferably, the method for the algorithm module to estimate the risk factor of each drainage unit includes the following steps:

[0020] Clean, standardize and supplement the data uploaded by the data acquisition control module;

[0021] Combine environmental parameters to establish an environmental model that reflects the environmental characteristics of the area where the drainage system is located, and combine the equipment structure parameters of the drainage system to generate a drainage system model;

[0022] Inputting the operation parameters of each drainage unit and the operation parameters of the connection nodes between the drainage units into the drainage system model to generate the simulation prediction results of the drainage system model;

[0023] Analyze the simulation prediction results and generate the hazard coefficients of multiple drainage units respectively;

[0024] Optimize and analyze the simulation prediction results.

[0025] Preferably, the algorithm module inputs a drainage model according to the volume and position of mountain water in combination with the construction progress of the tunnel face to obtain simulation results, and the algorithm module optimizes the drainage path according to the simulation results.

[0026] Preferably, it also includes a correction module, which is used to correct the data uploaded by the data acquisition control module.

[0027] Preferably, the data acquisition control module also includes measurement of water quality parameters, and the algorithm module substitutes the water quality parameters into the risk coefficient for calculation.

[0028] Preferably, the monitoring platform also includes an alarm module, which is arranged at the lower end of the tunnel face and is used to detect the water flow of the first-level drainage unit in real time. The alarm module is provided with a flow threshold. If the water flow of the first-level drainage unit is greater than the flow threshold, the monitoring platform adjusts the drainage path.

[0029] The beneficial effects of the present invention are:

[0030] By using the data acquisition control module and the coordination of the switching control module and the algorithm module, multiple drainage units are sorted from large to small according to the risk factor, and the drainage unit that is about to have problems is instructed to switch the control module to avoid the danger that will occur. First, the multi-level drainage units are monitored at different frequencies according to the ranking of the risk factors, and then the centralized monitoring and intelligent management of the entire drainage system are carried out to improve the drainage efficiency and ensure the safety and progress of the reverse slope construction. This system realizes real-time monitoring, fault warning, automatic switching and remote control of drainage units at all levels through an integrated monitoring platform, intelligent sensor network, automatic switching device and remote control center. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0032] Figure 1 This is a system block diagram of the monitoring platform of the present invention. DETAILED DESCRIPTION

[0033] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation methods, structures, features and effects of the present invention are described in detail below in conjunction with the accompanying drawings and preferred embodiments.

[0034] The same or similar numbers in the drawings of the embodiments of the present invention correspond to the same or similar parts; in the description of the present invention, it should be understood that if the terms "upper", "lower", "left", "right", "front", "back" and the like indicate directions or positional relationships based on the directions or positional relationships shown in the drawings, they are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and cannot be understood as limiting the present invention. For those skilled in the art, the specific meanings of the above terms can be understood according to specific circumstances.

[0035] Since the damage frequency of different drainage units is different, and as the tunnel is constructed forward, the pressure on the drainage unit will also change. Therefore, this embodiment provides a tunnel reverse slope excavation relay type automatic drainage system, which includes a monitoring platform, and multi-level drainage units and multiple spare drainage units arranged in the tunnel respectively controlled by the monitoring platform, each drainage unit includes a water collection tank and a drainage pipe, the monitoring platform includes an algorithm module and a switching control module, a data acquisition control module and a learning module electrically connected to the algorithm module respectively, and the switching control module is used to respond to the command of the monitoring platform to switch the specific drainage unit that needs to be switched to the spare drainage unit.

[0036] The data acquisition control module is used to collect environmental parameters, operating parameters of each drainage unit, operating parameters of the connection nodes between each drainage unit, and construction parameters of the face. The connection node parameters between multiple drainage units are the operating status parameters of the key node parameters of the drainage pipes or transfer stations between multiple upper and lower drainage units.

[0037] The algorithm module is used to calculate and evaluate the data uploaded by the data acquisition control module: the algorithm module uses statistical analysis and machine learning algorithms (such as time series analysis, regression model, etc.) to evaluate the working status of each drainage unit. Then, by comparing historical data with current data, the working trend of each drainage unit is predicted, including possible performance degradation or failure.

[0038] The algorithm module uses a weighted algorithm or an exponential function algorithm based on the evaluation results of the working status and working trend of multiple drainage units to calculate a risk factor for each drainage unit; the algorithm module then uses a reduction sort or a heap sort to sort the multiple drainage units from large to small according to the risk factor. The risk factor is a comprehensive indicator that takes into account multiple factors, such as drainage efficiency, performance of the drainage unit, failure rate, and maintenance history. The higher the risk factor, the greater the possibility of danger in the drainage unit.

[0039] According to the ranking results of the risk factors, the algorithm module can estimate the performance of each drainage unit. A risk factor threshold is preset in the monitoring platform. Once the risk factor of a drainage unit is greater than the risk factor threshold, the algorithm module determines that the drainage unit is very likely to be dangerous. In this case, the algorithm module will instruct the switching control module to switch to the backup drainage unit and send the operating parameters and position parameters of the drainage unit to the operator through the platform.

[0040] In addition, the algorithm module instructs the data acquisition control module to adjust the measurement frequency of different drainage units according to the risk factor of each drainage unit. For drainage units with higher risk factors, the measurement frequency can be increased to monitor their status more closely. For drainage units with lower risk factors, the measurement frequency can be appropriately reduced to save resources.

[0041] The learning module is used to update the drainage unit. The updated content of the learning module includes the newly added drainage unit and the update of the drainage path generated after the switching control module controls the switching.

[0042] In order to reduce the redundancy of the drainage system and improve the reliability of the entire drainage system, for example, when a drainage unit fails, more spare or recoverable drainage units can be quickly replaced to increase the response speed of the system. In addition, the original drainage path is generally the optimal drainage path, so it is necessary to monitor the status of the original drainage unit that has been switched so as to switch back the original drainage unit that has been restored after maintenance to ensure drainage efficiency. In one embodiment, the monitoring platform also includes monitoring the status of the original drainage unit that has been switched, and instructs the switching module to restore the original drainage unit that can be put into use. The switching control module switches the spare drainage unit back to the original drainage unit according to the instruction, and disconnects the access of the spare unit at the same time.

[0043] At the same time, the monitoring platform must also evaluate the status of multiple standby drainage units in order to meet the subsequent switching needs. The learning module updates the drainage path again. As the tunnel face construction progresses and the face conditions change, the drainage path may need to be adjusted continuously. By updating the drainage path, the learning module can ensure that the system always drains according to the optimal path and improves drainage efficiency. At the same time, the interface between multiple drainage units and the standby drainage unit for manual intervention should also be retained so that when the automation mechanism of the monitoring platform fails or special operations are required, the operator can manually adjust the status of the drainage unit and the drainage path to deal with emergencies.

[0044] In one embodiment, the data acquisition control module includes a water level sensor, a pressure sensor, a vibration sensor, a flow sensor, a position sensor and an image acquisition sensor. Multiple water level sensors and flow sensors respectively monitor the water levels of multiple drainage units, so that the monitoring platform can estimate the water flow and carrying capacity of different drainage units. Multiple position sensors respectively measure the positions of multiple drainage units, so that the monitoring platform can better estimate the positions of drainage units with problems. The image acquisition sensor is used to collect images of multiple drainage units and the entire drainage system for subsequent construction of the drainage system model and to facilitate subsequent inspections by operators.

[0045] In one embodiment, the operation parameters of the drainage unit include drainage pipe pressure data, flow data, water level data and component status data; the environmental parameters include location data, terrain data, and the construction angle of the tunnel construction surface compared to the horizontal plane and other environmental parameters that can affect the data of the three-dimensional model of the drainage system. The angle of the tunnel construction surface compared to the horizontal plane is used to calculate the drainage pressure of the pipes of each drainage unit, because the size of the inclination angle will affect the water pressure of the drainage unit pipe and thus affect the life of the pipe;

[0046] The construction parameters include construction water, three-dimensional laser scanning images of the tunnel face and construction progress. The three-dimensional laser scanning images of the tunnel face include the location and volume of mountain water on the tunnel face. The appearance time and volume of mountain water are obtained in combination with the construction progress. The algorithm module calculates the drainage volume that the drainage system needs to bear based on the appearance time and volume of mountain water, the construction water at each time and the parameters uploaded by the data acquisition control module, and then estimates the drainage system's bearing capacity based on the drainage system's bearing capacity, and then makes subsequent adjustments and optimizations, such as adding drainage units when the drainage volume exceeds 80% of the drainage system's bearing capacity.

[0047] In one embodiment, the method for the algorithm module to estimate the risk factor of each drainage unit includes the following steps:

[0048] Clean the data uploaded by the data acquisition control module to remove outliers and erroneous data; standardize the data to ensure that data from different sources have consistent units and dimensions; use data interpolation or fitting methods to supplement missing data;

[0049] Combine environmental parameters and system equipment parameters to establish an environmental model that reflects the environmental characteristics of the area where the drainage system is located, and combine the system equipment structure parameters to generate a complete drainage model based on the environmental model. The system equipment structure parameters here need to be input by operators on the monitoring platform. The system equipment structure parameters include equipment parameters of multiple parts of the drainage system, such as the overall layout of the drainage system, the shape, material and direction of the pipeline, and other parts equipment parameters used to build a three-dimensional model of the drainage system.

[0050] In the drainage system model, the operating parameters of each drainage unit and the operating parameters of the connection nodes between the drainage units are input to generate the simulation prediction results of the drainage system model. The simulation prediction results here can be displayed through animated graphs;

[0051] Analyze the simulation prediction results and generate the hazard coefficients of multiple drainage units respectively;

[0052] Optimize analysis results and optimize prediction results through historical data and field measurement data.

[0053] Since the construction environment in the tunnel is extremely complex, and the data of the monitoring platform mostly depends on the collection of the data acquisition control module, under the influence of the complex construction environment, the authenticity of the data uploaded by the data acquisition control module needs to be detected in real time, so verification data is needed to verify the data of the data acquisition control module. Therefore, in one embodiment, the monitoring platform also includes a correction module, which is used to correct the data uploaded by the data acquisition control module. The correction of the correction module includes judging the authenticity of the data uploaded by the data acquisition control module. The correction module collects a large amount of historical data as training samples, selects machine learning algorithms (such as support vector machines, decision trees, etc.) for training, and constructs a data authenticity judgment model. The trained model is used to predict and judge the data uploaded by the data acquisition control module. This method can automatically adapt to data changes and improve the accuracy of authenticity judgment. Of course, it is also necessary to set up a control group and a corresponding judgment program to make judgments in order to timely discover problems with the data uploaded by the data acquisition control module and make timely adjustments.

[0054] Since acidic or alkaline substances may be used in tunnel construction, these substances will change the pH value of wastewater. Acidic and alkaline substances are corrosive to the pipes and valves of the drainage system, shortening their service life. In addition, the building materials and geological conditions used in tunnel construction may cause heavy metal ions such as lead, mercury, and cadmium to be contained in the wastewater. These heavy metals will also corrode the pipes of the drainage system, thereby affecting the life of the drainage unit. Therefore, the algorithm module needs to consider the water quality when calculating the hazard factor. Therefore, in one embodiment, the data acquisition control module also includes the measurement of water quality parameters, including pH acidity and alkalinity and the content of specific heavy metal ions. The algorithm module substitutes the water quality parameters into the calculation of the hazard factor.

[0055] Because the mountain water data of the face collected by the data acquisition control module may be undetectable or a large amount of construction wastewater may be generated due to emergencies encountered during the construction of the face, the drainage pressure of the drainage system increases dramatically in a short period of time. In order for the monitoring platform to detect and make corresponding adjustments in the first time, in one implementation mode, the monitoring platform also includes an alarm module, which is disposed at the lower end of the face and is used to detect the water flow of the first-level drainage unit in real time. The alarm module is provided with a threshold. If the water flow of the first-level drainage unit is greater than the threshold, the monitoring platform activates an alternative transportation path and may use a flow meter or a water level meter to monitor the water volume at the face.

[0056] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A tunnel reverse slope excavation relay type automatic drainage system, comprising a monitoring platform, and a multi-stage drainage unit and a plurality of spare drainage units respectively controlled by the monitoring platform and arranged in the tunnel, characterized in that: The monitoring platform includes an algorithm module and a switching control module, a data acquisition control module and a learning module which are electrically connected to the algorithm module respectively; The data acquisition control module is used to collect environmental parameters, operating parameters of each drainage unit, operating parameters of connection nodes between each drainage unit, and construction parameters of the tunnel face; The algorithm module is used to calculate the data uploaded by the data acquisition control module, evaluate the working status and working trend of each drainage unit respectively, and then calculate the risk factor of each drainage unit according to the multiple working statuses and working trends, and sort the multiple risk factors from large to small; The data acquisition control module adjusts the acquisition frequency of the operating parameters of different drainage units according to the size of the risk factor; The algorithm module is also used to switch the drainage unit instruction switching control module whose risk factor is greater than the risk factor threshold; The switching control module is used to respond to the instruction of the monitoring platform to switch the drainage unit that needs to be switched to the standby drainage unit; The learning module is used to update the drainage unit, and the updated content of the learning module includes the newly added drainage unit and the update of the drainage path generated after the switching control module controls the switching.

2. The tunnel reverse slope excavation relay type automatic drainage system according to claim 1 is characterized in that: The monitoring platform also includes monitoring the status of the switched original drainage unit, and restoring the repaired original drainage unit instruction switching control module, and the learning module updates the drainage path again.

3. The tunnel reverse slope excavation relay type automatic drainage system according to claim 2 is characterized in that: The operating parameters of the plurality of drainage units include drainage pipe pressure data, flow data, water level data and component status data; The environmental parameters include location data, topographic data, and the construction angle of the tunnel construction surface compared to the horizontal plane; The construction parameters include construction water, a three-dimensional laser scanning image of the tunnel face, construction progress and the volume of construction water. The three-dimensional laser scanning image of the tunnel face includes the location and volume of mountain water appearing on the tunnel face.

4. The tunnel reverse slope excavation relay type automatic drainage system according to claim 3 is characterized in that: The method for the algorithm module to estimate the risk factor of each drainage unit includes the following steps: Clean, standardize and supplement the data uploaded by the data acquisition control module; Combine environmental parameters to establish an environmental model that reflects the environmental characteristics of the area where the drainage system is located, and combine the equipment structure parameters of the drainage system to generate a drainage system model; Inputting the operation parameters of each drainage unit and the operation parameters of the connection nodes between the drainage units into the drainage system model to generate the simulation prediction results of the drainage system model; Analyze the simulation prediction results and generate the hazard coefficients of multiple drainage units respectively; Optimize and analyze the simulation prediction results.

5. The tunnel reverse slope excavation relay type automatic drainage system according to claim 4 is characterized in that: The algorithm module inputs the drainage model into the volume and position of the mountain water in combination with the construction progress of the tunnel face to obtain simulation results, and the algorithm module optimizes the drainage path according to the simulation results.

6. The tunnel reverse slope excavation relay type automatic drainage system according to claim 1 is characterized in that: It also includes a correction module, which is used to correct the data uploaded by the data acquisition control module.

7. The tunnel reverse slope excavation relay type automatic drainage system according to claim 6 is characterized in that: The data collected by the data collection control module also includes water quality parameters, and the algorithm module substitutes the water quality parameters into the risk coefficient for calculation.

8. The tunnel reverse slope excavation relay type automatic drainage system according to claim 1 is characterized in that: The monitoring platform also includes an alarm module, which is arranged at the lower end of the tunnel face and is used to detect the water flow of the first-level drainage unit in real time. The alarm module is provided with a flow threshold. If the water flow of the first-level drainage unit is greater than the flow threshold, the monitoring platform adjusts the drainage path.

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