Tunnel micro-deformation real-time monitoring system and method

Abstract

The invention discloses a tunnel micro-deformation real-time monitoring system and method, and the method comprises the steps: monitoring the deformation condition of a tunnel section through employing a micro-deformation radar monitor installed in a tunnel in cooperation with a target, and generating deformation detection data; the deformation detection data is transmitted to a communication gateway located at a tunnel portal in a wireless transmission mode, and the communication gateway is in communication connection with the micro-deformation radar monitor through an Internet of Things ad hoc network communication system and transmits the deformation detection data to a tunnel monitoring system cloud platform; and the tunnel monitoring system cloud platform has a set classification and grading risk early warning mechanism, analyzes and processes the received deformation detection data, and triggers a corresponding early warning response according to an analysis result and the classification and grading risk early warning mechanism. According to the application, the millimeter-wave radar and Internet of Things communication technology is adopted, and the millimeter-wave radar phase interference measurement technology can be utilized to monitor vault settlement and peripheral displacement data of the tunnel section in an all-weather, full-automatic and real-time manner.

Description

Technical Field

[0001] The present invention relates to the technical field of tunnel engineering safety monitoring. In particular, it relates to a tunnel micro-deformation real-time monitoring system and method. Background Art

[0002] As an important part of underground traffic infrastructure, the structural safety of tunnel engineering is directly related to operation safety. Due to factors such as complex geological conditions, load changes, and construction disturbances, the surrounding rock and support structure of the tunnel may undergo small deformations. If not detected in time, it may lead to major accidents such as collapses and leaks. Traditional deformation monitoring means (such as total stations, laser scanners, etc.) have the following problems: Low efficiency of manual monitoring: Using equipment such as total stations and convergence meters requires manual regular measurements, which cannot achieve continuous monitoring and there are data blind spots; Poor reliability of data transmission: Wired devices such as fiber optic sensors and strain gauges are easily damaged by construction interference, and the wiring is complex and the maintenance cost is high; Wireless transmission methods based on broadband base stations or network bridges will also cause the transmission link to fail due to the failure or power outage of a certain device; Insufficient accuracy of micro-deformation detection: Traditional laser ranging technology has insufficient sensitivity to detect deformations below the millimeter level and is difficult to capture early micro-deformations; Optical equipment monitoring requires sufficient lighting conditions, while the harsh construction tunnels cannot meet such usage requirements; Single warning mechanism: Existing systems mostly use fixed threshold alarms, lacking comprehensive analysis of deformation rates, durations, and coordinated changes of multiple parameters, and are prone to false alarms or missed alarms.

[0003] In view of the above problems, the present invention proposes a tunnel deformation monitoring and warning that can achieve high precision, all-weather, and hierarchical. Summary of the Invention

[0004] The embodiments of the present application provide a tunnel micro-deformation real-time monitoring system and method. By using millimeter-wave radar and Internet of Things communication technology, it can utilize millimeter-wave radar phase interference measurement technology to monitor the crown settlement and peripheral displacement data of the tunnel section all-weather, fully automatically, and in real time.

[0005] In a first aspect, the embodiments of the present application provide a tunnel micro-deformation real-time monitoring system, which includes: a micro-deformation radar monitor, a target, a communication gateway, and a tunnel monitoring system cloud platform; The micro-deformation radar monitor installed in the tunnel cooperates with the target to monitor the deformation of the tunnel section and generate deformation detection data; The deformation detection data is transmitted to the communication gateway located at the tunnel entrance through wireless transmission. The communication gateway is communicatively connected to the micro-deformation radar monitor through an Internet of Things self-organizing communication system, and transmits the deformation detection data to the tunnel monitoring system cloud platform; The tunnel monitoring system cloud platform has a set classification and grading risk warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding warning responses according to the analysis results and the classification and grading risk warning mechanism.

[0006] Furthermore, the deformation detection data includes the vault settlement displacement data of the tunnel, and / or the horizontal displacement data, and / or the peripheral displacement data. The micro-deformation radar monitor uses millimeter-wave radar phase interference measurement technology to monitor the tunnel and generate the deformation detection data in real time.

[0007] Furthermore, there are multiple targets, and they have trihedral corner reflectors for cooperating with the micro-deformation radar monitor. The targets are respectively installed at different positions to collect different displacement data, including: the target installed at the vault settlement point is used to monitor the vault settlement displacement data, the target installed at the horizontal displacement point is used to monitor the horizontal displacement data, and the target installed at the peripheral displacement point is used to monitor the peripheral displacement data.

[0008] Furthermore, the micro-deformation radar monitor is installed on the side wall of the monitored tunnel, is horizontally opposite to the target installed at the horizontal displacement point, and can monitor the reflection signal of the target installed at the vault settlement point.

[0009] Furthermore, the Internet of Things self-organizing communication system adopts a narrowband Internet of Things Mesh self-organizing communication system with a Wi-sun architecture. The communication gateway accesses the Internet using LAN, and / or WIFI, and / or 4G modes, and transmits the deformation detection data sent by the micro-deformation radar monitor to the tunnel monitoring system cloud platform.

[0010] Furthermore, the Internet of Things self-organizing communication system also includes communication relay equipment. The communication relay equipment is installed in the tunnel and has a data forwarding function, which is used to enhance the health of the Internet of Things self-organizing communication system.

[0011] Furthermore, the micro-deformation radar monitor, and / or the communication gateway, and / or the communication relay equipment have self-provided power supplies and can work normally without relying on external power supplies.

[0012] Furthermore, the tunnel monitoring system cloud platform has a display module. The display module displays the analysis and processing results of the received deformation detection data in real time. The results include: the stability of the tunnel surrounding rock and / or the dynamic information of the mechanical form change of the support system.

[0013] Furthermore, the cloud platform of the tunnel monitoring system uses the displacement rate and displacement data of the tunnel cross-section reflected by the deformation detection data as the basis for the warning standard, and filters the warning situation and conducts hierarchical response according to the duration of the warning situation and the number of points where the warning appears.

[0014] In a second aspect, an embodiment of the present application provides a method for real-time monitoring of tunnel micro-deformation, including the following main steps: Deformation monitoring data acquisition: The micro-deformation radar monitor installed in the tunnel cooperates with the target to monitor the deformation of the tunnel cross-section and generate deformation detection data; Deformation monitoring data transmission: The deformation detection data is transmitted to the communication gateway located at the tunnel entrance by wireless transmission. The communication gateway is communicatively connected with the micro-deformation radar monitor through an Internet of Things self-organizing network communication system, and transmits the deformation detection data to the cloud platform of the tunnel monitoring system; Deformation warning response: The cloud platform of the tunnel monitoring system has a set classification and grading risk warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding warning responses according to the analysis results and the classification and grading risk warning mechanism.

[0015] It can be understood that the beneficial effects of the second aspect can be referred to the relevant descriptions in the first aspect above, and will not be elaborated here.

[0016] The beneficial effects of the embodiment of the present application compared with the prior art are as follows: The real-time monitoring system for tunnel micro-deformation of the present application uses a micro-deformation radar monitor based on millimeter-wave radar phase interference measurement technology, which is not affected by light conditions and has strong penetration ability in a dusty environment. It can monitor the crown settlement and peripheral displacement data of the tunnel cross-section all-weather, fully automatically and in real time. The micro-deformation radar monitor is installed on the side wall of the tunnel in cooperation with the target, which can ensure accurate measurement of the crown settlement of the tunnel even when there is material transmission in the tunnel. The data communication system of the narrowband Internet of Things Mesh self-organizing network using the Wi-sun architecture has the characteristics of low energy consumption and self-repair, and can realize real-time and accurate data transmission, solving the potential uncertainties caused by any potential factors such as broken wires, power outages, and occasional equipment failures in the transmission channel to the data transmission network. The cloud platform of the tunnel monitoring system with a display module can filter the warning situation and conduct hierarchical response according to the duration of the warning situation and the number of points where the warning appears, which helps to respond to and handle tunnel disasters in a timely and effective manner. Description of the Drawings

[0017] To more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings required for use in the embodiments or the description of the prior art. Obviously, the accompanying drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a schematic diagram of the composition of a real-time tunnel micro-deformation monitoring system provided by an embodiment of the present application; Figure 2 It is a schematic diagram of the installation position of the micro-deformation radar monitor and the monitoring electromagnetic wave radiation range provided by an embodiment of the present application; Figure 3 It is a schematic diagram of the crown settlement and horizontal displacement monitoring of the micro-deformation radar monitor provided by an embodiment of the present application; Figure 4 It is a schematic diagram of the crown settlement, horizontal displacement, and peripheral displacement monitoring of the micro-deformation radar monitor provided by an embodiment of the present application; Figure 5 It is an example diagram of the layout of the micro-deformation radar monitor of a real-time tunnel micro-deformation monitoring system provided by an embodiment of the present application; Figure 6 It is a schematic diagram of the micro-deformation radar monitor and the target provided by an embodiment of the present application; Figure 7 It is a schematic diagram of the network topology provided by an embodiment of the present application.

[0019] In the figure: 1. Internet of Things antenna of the micro-deformation radar monitor; 2. Transparent cover of the micro-deformation radar monitor; 3. Power interface; 4. Debugging interface; 5. Target; 6. Micro-deformation radar monitor; 7. Crown settlement point (target); 8. Horizontal displacement point (target); 9. Communication relay; 10. Communication gateway; 11. Broadband router; 12. Cloud platform; 13. Alarm system. Detailed implementation manners

[0020] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented to thoroughly understand the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0021] It should be understood that when used in the specification of this application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0022] It should also be understood that the term "and / or" used in the specification of this application and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0023] As used in the specification of this application and the appended claims, the term "if" can be interpreted according to the context as "when", "once", "in response to determining", or "in response to detecting". Similarly, the phrases "if determined" or "if [the described condition or event] is detected" can be interpreted according to the context as meaning "once determined", "in response to determining", "once [the described condition or event] is detected", or "in response to detecting [the described condition or event]".

[0024] In addition, in the description of the specification of this application and the appended claims, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0025] The reference to "one embodiment" or "some embodiments" etc. described in the specification of this application means that in one or more embodiments of this application, the specific features, structures, or characteristics described in connection with that embodiment are included. Thus, statements such as "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification do not necessarily all refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0026] The embodiment of this application provides a real-time monitoring system for tunnel micro-deformation, which consists of the following core modules: Front-end perception layer: including a micro-deformation radar monitor and a target array, responsible for collecting tunnel deformation data in real time.

[0027] Network transmission layer: a communication system based on the Internet of Things self-organizing network, including a communication gateway and relay devices, to achieve reliable data transmission.

[0028] Cloud processing layer: a data analysis and early warning platform deployed on a cloud server, supporting multi-dimensional data processing and intelligent decision-making.

[0029] In one embodiment, specifically as Figures 1 to 7 shown, the detection system includes: a micro-deformation radar monitor 6, targets (vault settlement point (target) 7, horizontal displacement point (target) 8), a communication gateway 10, and a tunnel monitoring system cloud platform 12.

[0030] Among them, the micro-deformation radar monitor 6 installed in the tunnel is used in conjunction with the targets to monitor the deformation of the tunnel section and generate deformation detection data. Specifically as follows: In one embodiment, as Figure 6 shown, the micro-deformation radar monitor 6 adopts millimeter-wave radar phase interference measurement technology, with a working frequency band of 76 - 81 GHz, an accuracy of ±0.01 mm, installed at a height of 1.5 m from the ground on the tunnel sidewall, with a longitudinal monitoring angle of 90° and a horizontal angle of 15°, covering a radius range of 50 m.

[0031] To meet the working requirements of the micro-deformation radar monitor 6, the target 5 has a trihedral corner reflector, and its surface is coated with a metal film to enhance the radar reflection signal. At the same time, there are multiple targets, which are installed at different positions to collect displacement data in different directions. As shown in the figure, the vault settlement point (target) 7 is installed at the vault settlement point, and the target installed at the vault settlement point is used to monitor the vault settlement displacement data; the horizontal displacement point (target) 8 is installed at the horizontal displacement point, and the target installed at the horizontal displacement point is used to monitor the horizontal displacement data; in addition, in other embodiments, there are also targets installed at the peripheral displacement points to monitor the peripheral displacement data. The following takes an embodiment to specifically illustrate the installation methods of the target and the micro-deformation radar monitor.

[0032] As shown in the figure, the monitoring range of the micro-deformation radar monitor 6 used in this application is 90 degrees longitudinally and 15 degrees horizontally. It is installed on the sidewall of the monitored tunnel, horizontally opposite to the horizontal displacement point (target) 8 installed at the horizontal displacement point, and can monitor the reflection signal of the vault settlement point (target) 7 installed at the vault settlement point. In such a measurement method, the horizontal displacement of the tunnel can be directly measured through the combination of the micro-deformation radar monitor 6 and the horizontal displacement point (target) 8, while the settlement value in the vertical direction of the tunnel is obtained indirectly through geometric operation relationships. For example, in one embodiment: In an ideal situation, as Figure 3 shown, when the tunnel has no bias pressure, the vault settlement point (target) will only produce displacement changes in the vertical direction. At this time, there are two solutions: 1. Isosceles triangle algorithm: Note: This algorithm is related to the real-time ranging a' with the horizontal displacement point (target):

[0033] 2. Sine algorithm (the displacement change of the vault settlement point has a very small impact on the horizontal angle, approximately considered ( ): Remark: This algorithm has nothing to do with the real-time ranging a' of the horizontal displacement point (target).

[0034] Since the tunnel has irregular deformation and the crown settlement is closely related to the peripheral displacement. If the horizontal displacement point (target) of the peripheral displacement is damaged or blocked, the real-time ranging a' data at the same time will be distorted. Therefore, in practical applications, in order to weaken the above adverse effects, the above two algorithms are combined and applied, and the following algorithm is used to comprehensively calculate the vertical displacement change value:

[0035] In the measurement of the above vertical displacement change value, the installation designs of the target and the micro-deformation radar monitor fully consider the working requirements of the tunnel. That is, since the tunnel generally has the need to convey objects, the bottom of the tunnel will be blocked by objects, so it is not convenient to set up a radar monitor to directly measure the vertical displacement change value. Using this method of indirectly obtaining the vertical displacement through the horizontal displacement can not only accurately measure the displacement change, but also does not affect the normal operation of the tunnel, and the installation position is also more convenient for the daily maintenance and repair of the radar monitor.

[0036] In one embodiment, as Figure 1 and Figure 7 shown, a communication gateway 10 is set at the tunnel entrance. The deformation detection data monitored by the micro radar monitor 6 is transmitted to the communication gateway 10 by wireless transmission. The communication gateway 10 is communicatively connected to the micro-deformation radar monitor 6 through an Internet of Things self-organizing network communication system, and transmits the deformation detection data to the tunnel monitoring system cloud platform 12.

[0037] In this embodiment, the Internet of Things self-organizing network communication system adopts a narrowband Internet of Things Mesh self-organizing network communication system with a Wi-sun architecture. The communication gateway accesses the Internet in the LAN, and / or WIFI, and / or 4G mode, and transmits the deformation detection data sent by the micro-deformation radar monitor to the tunnel monitoring system cloud platform.

[0038] In one embodiment, the power interface of the micro radar monitor 6 is connected to a DC 12V DC power supply or an energy storage power supply (polymer lithium battery pack), and the power interface provides an external power supply for the millimeter-wave radar phase interference measurement work. Three D-type batteries (Li-SOCl2 3.6V) are installed inside the micro deformation radar monitor 6, and this group of D-type batteries provides a working power supply for the Internet of Things self-organizing communication system. Therefore, the Internet of Things communication system can work normally without relying on any external power supply. At the same time, the Internet of Things communication system of the micro deformation radar monitor 6 can reversely monitor the millimeter-wave radar phase interference measurement work. When the external DC 12V DC power supply or the energy storage power supply (polymer lithium battery pack) stops working, the Internet of Things communication system can identify and give an early warning.

[0039] The communication gateway 10 is installed at the tunnel entrance. The main power supply is a DC 12V 3A DC power supply, and a solar power supply method can be adopted. One D-type battery (Li-SOCl2 3.6V) is installed inside the communication gateway 10 as a backup power supply. When the DC 12V main power supply is unavailable, the communication gateway 10 operates in a unique low-power mode, continues to receive the monitoring data of the micro deformation radar monitor 6 and stores it in the local on-board flash memory until the main power supply is restored. The communication gateway 10 supports access to the Internet in LAN, WIFI, and 4G modes, and uploads the tunnel automation monitoring data to the cloud platform 12.

[0040] In one embodiment, as Figure 1 and Figure 7 shown, in order to enhance the health of the Internet of Things self-organizing communication system, a communication relay 9 is also set in the tunnel for data forwarding. Two D-type batteries (Li-SOCl2 3.6V) are installed inside the communication relay 9, and this group of D-type batteries provides a working power supply for the Internet of Things self-organizing communication system. Therefore, the Internet of Things communication system of this application can work normally without relying on any external power supply.

[0041] It can be seen that the micro deformation radar monitor, and / or the communication gateway, and / or the communication relay device of this application has a self-provided power supply (the target adopts a passive design and does not require power supply), and can work normally without relying on an external power supply. This application constructs a tunnel Internet of Things self-organizing communication system with low power consumption, adapted battery life, Mesh self-repair and multi-hop routing structure. This communication system uses the Wi-Sun architecture to solve the uncertainties and hidden dangers caused by any potential factors such as disconnection, power failure, and occasional device failures in the transmission channel to the traditional data transmission network.

[0042] In an embodiment of the present application, the cloud platform of the tunnel monitoring system has a display module, which displays in real time the analysis and processing results of the received deformation detection data. The results include: the stability of the tunnel surrounding rock and / or the dynamic information of the mechanical form change of the support system. The visualization interface provides a dynamic display of the three-dimensional tunnel model, supports the display of displacement heat maps, and historical data can be exported in CSV format. By displaying the monitoring results in real time through the display module, the real-time performance of the monitoring is improved.

[0043] In an embodiment, the cloud platform of the tunnel monitoring system is built based on Alibaba Cloud, with a built-in data analysis engine and an early warning rule library, supports multi-level permission access, has a set classification and grading risk early warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding early warning responses according to the analysis results and the classification and grading risk early warning mechanism. The cloud platform of the tunnel monitoring system classifies the alarm conditions into different levels according to the duration of the alarm, and triggers different response mechanisms, including: instantaneous interference alarm conditions and continuous real alarm conditions, where high-level real alarm conditions trigger the SMS alarm response mechanism.

[0044] In an embodiment, the grading early warning mechanism is as follows (including alarm level: judgment conditions, response actions;): Level 1 alarm: single-point displacement rate > 2mm / h, platform pop-up alarm; Level 2 alarm: three-point continuous displacement > 5mm / 24h, SMS notification to the technical person in charge; Level 3 alarm: RSI ≥ 0.6 and continuous for 30 minutes, start the audible and visual alarm and link with the emergency system.

[0045] In another embodiment, the cloud platform of the tunnel monitoring system uses the displacement rate and displacement amount data of the tunnel section reflected by the deformation detection data as the basis for the early warning standard, and filters and classifies the alarm conditions and responds according to the duration of the early warning alarm condition and the number of points where the early warning appears. Although the tunnel monitoring method of the total station also uses the displacement rate and displacement amount as the basis for early warning, due to the limitations of the acquisition means, the monitoring method based on the total station has defects such as slow acquisition speed, long acquisition time interval, small amount of acquired data, inability to monitor in real time, high operation risk, high labor intensity, many human factors, and lack of value in in-depth data analysis, making it difficult to detect deformation in time and achieve early warning. This embodiment analyzes the two alarm conditions of displacement rate and displacement amount respectively, and uses different colors to distinguish different levels of alarm conditions (blue, yellow, orange, red). In view of the situation that the alarm condition can be caused by instantaneous interference factors (construction machinery driving vibration, blasting vibration) and can be quickly restored, this application also distinguishes between interference false alarm conditions and continuous real alarm conditions by the duration and the number of points where the early warning appears. Specifically as follows: Early warning standard: 1. Displacement rate: Define the thresholds for different warning criteria to classify the warning criteria. In this implementation, the displacement rate in 24 hours (mm / d) is used as the warning criterion, which is divided into four levels from low to high: (blue, yellow, orange, red). The blue and yellow levels are mainly for color prompts, while the orange and red levels will have alarm announcements while giving color prompts. When the displacement rate is lower than the lowest-level warning (blue) criterion, it will be prompted in green, and when the echo signal of the monitoring point (target) is lower than the threshold value, it will be prompted in gray.

[0046] In the display module of the tunnel monitoring system cloud platform, different rules are used for display in different monitoring interfaces. For example, in the monitoring interface of tunnel cross-section monitoring, the displacement rate of the monitoring point (target) is displayed in color grading. In the tunnel monitoring deployment model diagram, it is displayed in the color of the highest-level displacement rate in the current cross-section monitoring. This can help the monitor quickly grasp the core warning information and reduce the decision-making time.

[0047] 2. Displacement management: Use the custom reserved deformation amount (provided by the tunnel design unit) as the basis for the warning criterion. In this embodiment:

Level A

Level B

Level C

[0048] Similarly, in the display module of the tunnel monitoring system cloud platform, different rules are used for display in different monitoring interfaces. For example, when the displacement is in the normal state - Level A, the monitoring point is not displayed. In the monitoring interface of tunnel cross-section monitoring, the displacement of the monitoring point (target) is displayed in color grading with "!". In the tunnel monitoring deployment model diagram, it is displayed with "!" in the color of the highest-level displacement in the current cross-section monitoring.

[0049] As described above, this embodiment also comprehensively uses the duration of the warning and the number of points where the warning appears to achieve warning filtering and hierarchical response, as follows: This example performs warning filtering and classification announcements for the warning situations that trigger the orange and red level warning criteria of displacement rate and displacement: 1. Warning duration: Used to distinguish instantaneous interference warnings and continuous real warnings. Only when the following criteria are met will it be confirmed as a real warning, otherwise only color reminders will be given without alarm announcements.

[0050] For example: Taking the deformation detection data transmission frequency as an example (once every 5 minutes), the continuous duration (number of times) of receiving the warning without interruption is used as the determination factor for warning filtering. (Note: The data transmission frequency and warning duration (number of times) are only for illustrative purposes and not for limitation.) For instance: Displacement rate alarm (orange, red): Orange warning: If the orange threshold is exceeded for 60 consecutive minutes (12 times), an orange alarm broadcast will be triggered.

[0051] Red warning: If the red threshold is exceeded for 30 consecutive minutes (6 times), a red alarm broadcast will be triggered.

[0052] Displacement amount alarm (orange, red): Orange warning: If the orange threshold is exceeded for 30 consecutive minutes (6 times), an orange alarm broadcast will be triggered.

[0053] Red warning: If the red threshold is exceeded for 15 consecutive minutes (3 times), a red alarm broadcast will be triggered.

[0054] 2. Number of points where warnings occur: That is, different levels of responses are made according to whether the cross-section monitoring warning is a single-point or multi-point warning: ① When a single-point alarm in the cross-section monitoring is triggered, the level is relatively low, and a "risk warning reminder" is used to broadcast the warning.

[0055] ② When a multi-point orange alarm in the cross-section monitoring is triggered, the level is relatively high, and an "emergency warning reminder" is used to broadcast the warning.

[0056] ③ When a multi-point red alarm in the cross-section monitoring is triggered, the level is even higher, and an "emergency warning alert" is used to broadcast the warning.

[0057] In one embodiment, the data acquisition and transmission process of the present application is as follows: Deformation data generation: The radar monitor emits a frequency-modulated continuous wave (FMCW) to the target at a frequency of 10 Hz, and calculates the displacement amount through the phase difference interference method to generate a deformation data packet including crown settlement, horizontal displacement, and peripheral convergence.

[0058] 2. Wireless transmission: The data is encrypted and transmitted through the Wi-Sun network. The path selection algorithm dynamically optimizes the routing (such as the AODV protocol), and the communication relay device starts data forwarding when the signal strength is lower than -90 dBm.

[0059] 3. Cloud access: The gateway uploads the data to the cloud platform through the 4G network, and the transmission period can be configured (default 5 minutes / time, real-time transmission in emergency mode).

[0060] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment can be integrated into a processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above integrated unit can be implemented in the form of hardware or in the form of a software functional unit. In addition, the specific names of each functional unit and module are only for the convenience of mutual distinction and do not limit the protection scope of this application. The specific working process of the units and modules in the above system can refer to the corresponding process in the foregoing method embodiment and will not be elaborated here.

[0061] Based on the same technical concept, an embodiment of the present application further provides a method for real-time monitoring of tunnel micro-deformation, including the following main steps: Deformation monitoring data acquisition: The micro-deformation radar monitor installed in the tunnel cooperates with the target to monitor the deformation of the tunnel cross-section and generate deformation detection data; Deformation monitoring data transmission: The deformation detection data is transmitted to the communication gateway located at the tunnel entrance by wireless transmission. The communication gateway is communicatively connected with the micro-deformation radar monitor through an Internet of Things self-organizing network communication system and transmits the deformation detection data to the tunnel monitoring system cloud platform; Deformation early warning response: The tunnel monitoring system cloud platform has a set classification and grading risk early warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding early warning responses according to the analysis results and the classification and grading risk early warning mechanism.

[0062] In the above embodiments, the descriptions of the respective embodiments have their own emphases. For parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0063] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0064] In the embodiments provided in the present application, it should be understood that the disclosed device / network device and method can be implemented in other ways. For example, the device / network device embodiments described above are merely illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection to each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0065] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0066] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A real-time monitoring system for tunnel micro-deformation, characterized in that: The system includes: a micro-deformation radar monitor, a target, a communication gateway, and a tunnel monitoring system cloud platform; The micro-deformation radar monitor installed in the tunnel is used in conjunction with the target to monitor the deformation of the tunnel cross-section and generate deformation detection data; The deformation detection data is transmitted to the communication gateway located at the tunnel entrance through wireless transmission. The communication gateway is communicatively connected to the micro-deformation radar monitor through an Internet of Things self-organizing network communication system and transmits the deformation detection data to the tunnel monitoring system cloud platform; The tunnel monitoring system cloud platform has a set classification and grading risk warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding warning responses according to the analysis results and the classification and grading risk warning mechanism.

2. The real-time monitoring system for tunnel micro-deformation according to claim 1, characterized in that, The deformation detection data includes the crown settlement displacement data, and / or horizontal displacement data, and / or peripheral displacement data of the tunnel. The micro-deformation radar monitor uses millimeter-wave radar phase interference measurement technology to monitor the tunnel in real time and generate the deformation detection data.

3. The real-time tunnel micro-deformation monitoring system according to claim 2, wherein There are multiple targets, and they have corner reflectors for cooperating with the micro-deformation radar monitor. The targets are respectively installed at different positions to collect different displacement data, including: the target installed at the crown settlement point is used to monitor the crown settlement displacement data, the target installed at the horizontal displacement point is used to monitor the horizontal displacement data, and the target installed at the peripheral displacement point is used to monitor the peripheral displacement data.

4. The real-time tunnel micro-deformation monitoring system according to claim 3, characterized in that, The micro-deformation radar monitor is installed on the side wall of the monitored tunnel, is horizontally opposite to the target installed at the horizontal displacement point, and can monitor the reflection signal of the target installed at the crown settlement point.

5. The real-time tunnel micro-deformation monitoring system according to claim 1, characterized in that, The Internet of Things self-organizing network communication system adopts a narrowband Internet of Things Mesh self-organizing network communication system with a Wi-sun architecture. The communication gateway accesses the Internet in the LAN, and / or WIFI, and / or 4G mode, and transmits the deformation detection data sent by the micro-deformation radar monitor to the tunnel monitoring system cloud platform.

6. The real-time tunnel micro-deformation monitoring system according to claim 5, characterized in that The Internet of Things self-organizing network communication system also includes communication relay equipment. The communication relay equipment is installed in the tunnel and has a data forwarding function to enhance the health of the Internet of Things self-organizing network communication system.

7. The real-time tunnel micro-deformation monitoring system according to any one of claims 1 to 6, characterized in that, The micro-deformation radar monitor, and / or the communication gateway, and / or the communication relay equipment has a self-provided power supply and can work normally without relying on external power.

8. The real-time tunnel micro-deformation monitoring system according to claim 1, characterized in that The tunnel monitoring system cloud platform has a display module. The display module displays the analysis and processing results of the received deformation detection data in real time. The results include: the stability of the tunnel surrounding rock and / or the dynamic information of the mechanical form change of the support system.

9. The real-time monitoring system for tunnel micro-deformation according to claim 1, characterized in that, The tunnel monitoring system cloud platform uses the displacement rate and displacement data of the tunnel cross-section reflected by the deformation detection data as the basis for the warning standard, and filters the warning situation and conducts hierarchical responses according to the duration of the warning situation and the number of warning points.

10. A real-time monitoring method for micro-deformation of tunnels, characterized in that: It includes the following main steps: Deformation monitoring data acquisition: The micro-deformation radar monitor installed in the tunnel is used in conjunction with the target to monitor the deformation of the tunnel cross-section and generate deformation detection data; Deformation monitoring data transmission: The deformation detection data is transmitted to the communication gateway located at the tunnel entrance through wireless transmission. The communication gateway is communicatively connected to the micro-deformation radar monitor through an Internet of Things self-organizing network communication system, and transmits the deformation detection data to the tunnel monitoring system cloud platform; Deformation early warning response: The tunnel monitoring system cloud platform has a set classification and grading risk early warning mechanism, analyzes and processes the received deformation detection data, and triggers corresponding early warning responses according to the analysis results and the classification and grading risk early warning mechanism.

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