CN118690616A - A method for locating tunnel fires and monitoring lining structure damage after disasters - Google Patents

Abstract

The application discloses a method for positioning tunnel fire and monitoring damage of a lining structure after the fire, which comprises the following steps: dividing a tunnel into a plurality of adjacent monitoring sections along the longitudinal length direction, and arranging a deformation detection module and a temperature detection unit; positioning a fire point when abnormality occurs in the detection data of the deformation detection module and/or the temperature detection unit; and after the fire disaster is over, analyzing structural damage of the tunnel lining on the equipment intact section according to the data re-detected after the fire disaster by the deformation detection module and the temperature detection unit. The application has the beneficial effects that: the occurrence of fire is determined by timely capturing abnormal deformation data and temperature data of the lining by using related equipment used for detecting the tunnel lining structure; and determining the position of the fire disaster in the tunnel and the fire disaster range according to the position parameters of the equipment. After fire extinguishment, the influence range and the influence degree of the fire on the structure can be judged through an undamaged deformation monitoring system.

Description

A method for locating tunnel fires and monitoring lining structure damage after disasters

Technical Field

The present application relates to the technical field of tunnel safety monitoring, and in particular to a method for locating tunnel fires and monitoring lining structure damage after a disaster.

Background Art

During the use of the tunnel, fires may occur due to line failures or vehicle accidents. When a fire occurs in a tunnel, the monitoring department needs to obtain fire information in a timely manner so as to quickly put out the fire and reduce the impact of the high temperature of the fire on the tunnel lining structure.

The traditional fire alarm system used in the tunnel uses DIC technology to identify flame images and issue alarms. The related equipment includes: dual-wavelength flame detectors and related alarm equipment, which are fully functional but single. The traditional post-disaster damage assessment method mainly uses carbonization depth detection, rebound detection and core drilling detection; however, after a fire actually occurs, it is difficult to determine the affected area of the tunnel. The entire process relies on manual detection, which is time-consuming, labor-intensive and highly subjective.

Summary of the invention

One of the objects of the present application is to provide a method for locating tunnel fires and monitoring lining structure damage after a disaster, which can solve at least one of the defects in the above-mentioned background technology.

In order to achieve at least one of the above purposes, the technical solution adopted by the present application is: a method for locating a tunnel fire and monitoring damage to a lining structure after a disaster, comprising the following steps:

S100: Divide the tunnel into a plurality of adjacent monitoring sections along the longitudinal length direction, and arrange a deformation detection module and a temperature detection unit for detecting longitudinal deformation and surface temperature for each of the monitoring sections;

S200: When the detection data of the deformation detection module and/or the temperature detection unit is abnormal, the fire point is located according to the monitoring section position corresponding to the abnormal data and an alarm is issued to the control center;

S300: After the fire is over, the monitoring section where the fire occurred is divided into a damaged equipment section and an intact equipment section according to the damage of the equipment;

S400: For the equipment intact section, structural damage analysis of the tunnel lining is performed based on the data re-detected by the deformation detection module and the temperature detection unit after the disaster.

Preferably, the deformation detection module includes a monitoring point and a visual detection unit; the monitoring point is arranged at the end of the monitoring segment, the visual detection unit is installed on the monitoring segment, and the visual detection unit is suitable for capturing images of the monitoring point to obtain the longitudinal deformation of the monitoring segment.

Preferably, a plurality of the monitoring points are provided at the end of the monitoring section, and the plurality of the monitoring points are arranged at equal intervals along the cross-sectional contour direction of the tunnel.

Preferably, a target is installed at the monitoring point, and the visual detection unit is suitable for collecting images of the target, and then obtaining the longitudinal deformation amount corresponding to the monitoring section according to the change of the imaging size of the target.

Preferably, the visual detection unit is installed at one end of the monitoring section to capture images of the target at the other end of the monitoring section.

Preferably, the targets are installed at both ends of the monitoring section, the visual detection unit is installed in the middle of the monitoring section, and the visual detection unit simultaneously captures images of the targets at both ends of the monitoring section.

Preferably, the location of the fire point in step S200 includes the following process:

S210: numbering each monitoring segment and the corresponding data; determining the number of fire points according to the numbers corresponding to the abnormal data, and locating the monitoring segment position corresponding to each fire point;

S220: comparing the longitudinal deformations of both ends of the monitoring section corresponding to the fire point according to the data collected by the visual detection unit;

S230: Locate the specific position of the fire point in the monitoring section according to the comparison results of the longitudinal deformations at both ends and the data of the temperature detection unit.

Preferably, a plurality of settlement joints are formed along the longitudinal length direction of the tunnel according to the construction, the tunnel is divided into n sections according to the settlement joints, and the tunnel between adjacent settlement joints is divided into m sections, thereby obtaining n×m monitoring sections.

Preferably, step S400 includes the following specific processes:

S410: Based on the mechanical properties of concrete, a concrete performance data set is constructed through finite element simulation;

S420: training the concrete performance data set using a deep learning method to obtain a concrete performance evaluation model;

S430: Collect temperature and longitudinal deformation data of intact equipment sections after the disaster;

S440: inputting the data collected in step S430 into the concrete performance evaluation model for inversion to obtain the actual elastic modulus of different monitoring sections of the tunnel;

S450: Compare the inversion result of step S440 with the design standard to determine the degree of structural degradation of each monitored section of the tunnel.

Preferably, after completing step S420, the obtained concrete performance evaluation model is corrected, including the following process:

S421: Substituting historical data of tunnel temperature and longitudinal deformation into a concrete performance evaluation model as correction data;

S422: Compare the output results of the concrete performance evaluation model with the historical elastic modulus data of the tunnel;

S423: If the error between the two is less than or equal to the set threshold, it means that the obtained concrete performance evaluation model meets the accuracy requirement;

S424: If the error between the two is greater than a set threshold, an error analysis is performed and the concrete performance evaluation model is corrected based on historical data.

Compared with the prior art, the beneficial effects of this application are:

This application can use the relevant equipment used for tunnel lining structure detection to timely capture the abnormal deformation data and temperature data of the lining to determine the occurrence of a fire; and determine the location and scope of the fire in the tunnel based on the location parameters of the equipment. After the fire is extinguished, the scope and degree of the fire's impact on the structure can be determined through the undamaged deformation monitoring system.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a schematic diagram of the workflow of this application.

FIG. 2 is a schematic diagram of the arrangement structure of the visual detection unit and the temperature detection unit in the tunnel in the present application.

FIG. 3 is a schematic diagram showing the principle of longitudinal deformation calculation performed by the visual detection unit in the present application.

FIG. 4 is a schematic diagram of locating a single fire point by using a visual detection unit and a temperature detection unit in the present application.

FIG5 is a schematic diagram of positioning multiple fire points by using a visual detection unit and a temperature detection unit in the present application.

FIG6 is a schematic diagram of the correction process of the concrete performance evaluation model in this application.

DETAILED DESCRIPTION

Below, the present application is further described in conjunction with specific implementation methods. It should be noted that, under the premise of no conflict, the various embodiments or technical features described below can be arbitrarily combined to form new embodiments.

In the description of the present application, it should be noted that directional words, such as the terms "center", "lateral", "longitudinal", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", etc., indicating directions and positional relationships are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of narrating the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and cannot be understood as limiting the specific scope of protection of the present application.

It should be noted that the terms "first", "second", etc. in the description and claims of the present application are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

The terms "including" and "having" and any variations thereof in the specification and claims of the present application are intended to cover non-exclusive inclusions. For example, a process, method, system, product or apparatus comprising a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products or apparatuses.

One of the preferred embodiments of the present application, as shown in FIG1 , is a method for locating a tunnel fire and monitoring damage to a lining structure after a disaster, comprising the following steps:

S100: Divide the tunnel into a plurality of adjacent monitoring sections along the longitudinal length direction, and arrange a deformation detection module and a temperature detection unit for detecting longitudinal deformation and surface temperature for each monitoring section.

S200: When the detection data of the deformation detection module and/or the temperature detection unit is abnormal, the fire point is located according to the monitoring section position corresponding to the abnormal data and an alarm is sent to the control center.

S300: After the fire is over, the monitoring section where the fire occurred is divided into a damaged equipment section and an intact equipment section according to the damage to the equipment.

S400: For the intact equipment section, structural damage analysis of the tunnel lining is performed based on the data of the deformation detection module and the temperature detection unit re-detected after the disaster.

It is understandable that the strength of the tunnel lining structure is mainly determined by the elastic modulus E, and the factors that affect the elastic modulus are mainly temperature and longitudinal deformation; since the tunnel is generally a circular arch cross-section, the longitudinal deformation can also be regarded as axial deformation. Therefore, the monitoring of the strength of the tunnel lining structure is mainly the monitoring of the surface temperature and longitudinal deformation of the tunnel. Since the length of the tunnel is generally long, in order to facilitate monitoring and improve the accuracy of monitoring, the tunnel can be divided into multiple sections along the longitudinal or axial length direction, so that multiple monitoring sections with relatively short lengths can be obtained. Then, the deformation detection module and the temperature detection unit can be arranged in the corresponding monitoring section to collect the relevant data of the corresponding monitoring section respectively, and then calculate the structural strength of the corresponding monitoring section.

When a fire occurs in a tunnel, the temperature in the tunnel will change dramatically. The lining at the fire location will cause the temperature of the tunnel lining structure to rise sharply under high temperature baking, causing the longitudinal displacement of the lining at the fire location to be significantly abnormal. It should be noted that the obvious change in the longitudinal displacement of the lining under high temperature is relative to the normal temperature. Therefore, when a fire occurs in a tunnel, the abnormality of the longitudinal deformation data of the lining can be used for judgment, and the location of the fire point can be located according to the monitoring section position corresponding to the abnormal longitudinal deformation data. At the same time, the temperature detection unit installed in the monitoring section can also obviously monitor the abnormal temperature data, so the abnormal data of the temperature detection unit can also be used as a basis for judging the occurrence of a fire, and the location of the fire point can be located according to the monitoring section position corresponding to the abnormal data of the temperature detection unit. Of course, in order to further improve the judgment accuracy of the fire, the data of the two can be combined for judgment.

It should be known that when a fire occurs, if the fire is large or the environment is significantly higher than the working temperature of the equipment, the deformation detection module and the temperature detection unit may be damaged. Therefore, when monitoring the damage to the tunnel lining structure after a disaster, it is necessary to evaluate the damaged equipment section and the intact equipment section separately. For the damaged equipment section, it is necessary to evaluate the deterioration and damage of the lining structure of the monitoring section corresponding to the fire section through theoretical means based on the temperature gradient distribution and continuous temperature distribution of the fire section of the tunnel during the entire process of the fire; the specific theoretical means are conventional techniques of those skilled in the art, so they will not be elaborated here in detail. For the intact equipment section, the lining structure damage can be monitored and analyzed and evaluated based on the data re-detected by the deformation detection module and the temperature detection unit corresponding to the monitoring section.

Specifically, as shown in FIG. 1 , the above method can be implemented through a monitoring system, which mainly includes three modules: a front-end data acquisition module, a fire alarm module, and a structural degradation evaluation module.

The front-end data acquisition module mainly collects the tunnel surface temperature and longitudinal deformation (axial deformation) of the monitoring section through the deformation detection module and temperature detection unit installed in each monitoring section. The data collected by the front-end data acquisition module can be sent to the fire alarm module and the structural degradation evaluation module respectively.

The fire alarm module identifies abnormal data from the received data and sends it to the control center for alarm; abnormal data includes abnormal surface temperature ΔT and abnormal longitudinal deformation (axial deformation) ΔL. After receiving the alarm information, the operator of the control center can call the camera equipment near the location where the abnormal data occurs, or call the camera equipment of the deformation detection module to manually determine the fire situation at the location of the abnormal data. After determining that a fire has occurred, the specific location and scope of the fire can be located according to the location of the abnormal data, and then the fire alarm information can be issued to the tunnel to alert passing vehicles; at the same time, the fire situation can be sent to the structural degradation assessment module.

The structural degradation evaluation module can judge the damage of the equipment arranged near the fire point. For the damaged equipment section, the temperature gradient distribution and the duration of high temperature can be collected. It should be noted that the function of the temperature detection unit is to detect the temperature. Therefore, in a high temperature environment, the temperature detection unit is generally not easily damaged. The main damaged equipment is the deformation detection module using visual detection; therefore, the temperature gradient and duration of the damaged equipment section can be recorded by the temperature detection unit. Finally, the damage to the lining structure of the damaged equipment section can be evaluated by theoretical means based on the recorded data, and the damaged deformation monitoring equipment, that is, the deformation detection module, can be restored. For the intact equipment section, the damage to the lining structure can be evaluated based on the tunnel surface temperature and tunnel longitudinal deformation data resent by the front-end data acquisition module after the disaster.

In this embodiment, there are multiple specific structures of the deformation detection module that can simultaneously realize the longitudinal deformation monitoring of the monitoring section of the tunnel and the monitoring of the fire point in the tunnel. For the convenience of understanding, one of the structures will be given below for detailed description. As shown in Figure 2, the deformation detection module includes a monitoring point and a visual detection unit; the monitoring point is set at the end of the monitoring section, and the visual detection unit is installed in the monitoring section. The visual detection unit can collect images of the monitoring point to obtain the longitudinal deformation of the monitoring section.

It should be known that the monitoring of fire in the tunnel can be judged by the sudden change of longitudinal deformation of the monitoring section obtained by the visual detection unit, or it can be directly identified by the visual detection unit. Of course, the visual detection unit's viewing angle range may not be able to directly identify the entire range of the monitoring section, so the visual detection unit can be used as a way of human camera confirmation after the longitudinal deformation data is abnormal.

It can be understood that the specific structure and working principle of the visual detection unit and the temperature detection unit are well-known technologies to those skilled in the art; common visual detection units include displacement monitoring camera devices such as gun cameras and ball cameras, and common temperature detection units include thermometers and temperature sensors. For the temperature detection unit, a thermometer can be used to capture the reading of the thermometer through a displacement monitoring camera and transmit the image data to the control center for long-distance temperature data reading; for the temperature sensor, it can be directly transmitted to the control center by signal transmission; the specific selection can be made according to the actual needs of those skilled in the art. For each monitoring segment, a temperature detection unit can be installed on the central surface of the monitoring segment, or multiple temperature detection units can be installed at equal intervals along the surface of the monitoring segment.

Specifically, this application uses non-contact measurement to monitor the longitudinal strain of the tunnel and the ambient temperature in sections and establish a relationship. It also analyzes the relationship between the longitudinal deformation and the degradation of the structural stiffness in sections, thereby locating the sections where tunnel diseases are prone to or have occurred, and conducting key monitoring. This can effectively avoid the influence of tunnel deformation on the monitoring results and improve the monitoring accuracy. This process is low-cost, simple to operate, and can protect the entire tunnel section. In combination with existing non-contact monitoring, it can achieve accurate positioning of tunnel damage.

In this embodiment, as shown in FIG2 , in order to facilitate the visual detection unit to monitor the longitudinal deformation of the tunnel, a target can be installed at the detection point; the visual detection unit can capture a clear image by shooting the corresponding target. The visual detection unit can continuously capture images of the target; and then the longitudinal deformation of the corresponding monitoring section can be calculated based on the changes in the imaging size of the target in the images captured multiple times.

It should be known that the common way to directly monitor an object visually is to directly collect the deformation of the object; specifically, the initial position of the monitoring point of the object can be marked, and then the monitoring point can move with the deformation of the object during the deformation of the object. At this time, the deformation of the object can be obtained by comparing the current position of the monitoring point with the marked position. However, in actual use, since the shooting direction of the visual detection unit is perpendicular to the deformation direction of the object and always remains stationary, a certain deflection angle will be generated between the visual detection unit and the object during the deformation of the object, thereby affecting the accuracy of deformation collection; if you want to improve the accuracy, you need to use a corresponding algorithm to compensate, which will increase the calculation amount and cost of deformation collection, and the accuracy of the algorithm also directly affects the accuracy of deformation detection.

In this embodiment, the longitudinal displacement change from the target to the visual detection unit, i.e., the longitudinal deformation of the monitoring segment, can be obtained by reverse deduction based on the different image sizes of the target as the distance from the monitoring segment to the visual detection unit changes with the longitudinal deformation of the monitoring segment. For convenience, the following is a detailed description of the process of obtaining the longitudinal deformation of the monitoring segment by different target imaging sizes in this embodiment.

Specifically, as shown in FIG3 , the height of the target can be set to H, the longitudinal distance between the target and the lens of the displacement monitoring camera can be set to L+ΔL, and the distance between the lens of the displacement monitoring camera and the internal imaging element can be set to l. Initially, the target can be represented by a solid-line frame, and the image height dimension of the target in the internal imaging element of the displacement monitoring camera is x ₀ . As the monitoring segment deforms longitudinally, the target can move synchronously with the deformation of the monitoring segment, and the target can be represented by a dotted-line frame; assuming that the target is approaching the displacement monitoring camera, and the approaching distance is ΔL, that is, the longitudinal deformation of the monitoring segment, then the longitudinal distance between the target and the lens of the displacement monitoring camera is L. Correspondingly, the image height dimension of the target in the internal imaging element of the displacement monitoring camera is x.

According to the geometric relationship, the following relationship can exist:

x ₀ /l=H/(L+ΔL), x/l=H/L.

By transforming the above relationship, we can obtain: Hl= x ₀ (L+ΔL), Hl=xL.

Furthermore, according to x ₀ (L+ΔL)= xL, the calculation formula for the longitudinal deformation ΔL can be simplified to: ΔL=[(x/x ₀ )-1]L.

It should be known that, from the above calculation formula, the calculation of the longitudinal deformation of the monitoring section has nothing to do with the height of the target and the distance from the lens of the displacement monitoring camera to the imaging element, but is only related to the imaging height of the target and the longitudinal distance from the displacement monitoring camera to the target. This can effectively simplify the calculation process and avoid the influence of other factors on the calculation results, and can effectively improve the monitoring accuracy of the longitudinal deformation of the monitoring section.

It should be noted that in the above calculation process, the vertical distance from the target to the displacement monitoring camera is assumed to be constant; since the tunnel is a circular arch structure with strong compressive resistance, the tunnel can be regarded as having no deformation in the vertical direction. Therefore, there is only a change in the distance in the longitudinal direction between the target and the displacement monitoring camera, which can maintain a high accuracy of the calculation result and the calculation process is relatively simple.

In this embodiment, only one monitoring point may be set at the end of the monitoring section; however, considering that the stress conditions at various positions along the cross-sectional contour of the tunnel may be inconsistent, that is, the longitudinal deformation amounts at various positions along the cross-sectional contour of the tunnel may be inconsistent. Therefore, in order to maintain the accuracy of the monitoring results, multiple monitoring points may be set at the end of each monitoring section, and the multiple monitoring points are set at equal intervals along the cross-sectional contour of the tunnel. As a specific example, as shown in FIG2, each monitoring section is provided with two monitoring points along the cross-sectional contour, and the two monitoring points are symmetrically arranged. The targets installed at the two monitoring points at the same end are imaged by different visual detection units to respectively calculate the corresponding longitudinal deformation amounts.

In this embodiment, based on the imaging relationship between the visual detection unit and the target, there are multiple ways to install the visual detection unit. For ease of understanding, two examples are used for detailed description below.

Example 1: As shown in FIG. 2 , the visual detection unit may be installed at any position on the wall corresponding to the monitoring section, so that the visual detection unit can capture images of a target installed at at least one end of the monitoring section.

It can be understood that the number of visual detection units generally corresponds to the number of monitoring sections. For the case where the tunnel section between adjacent settlement joints includes multiple monitoring sections, targets can be installed at both ends of each monitoring section, and two adjacent monitoring sections share a monitoring point at adjacent positions.

Then, the visual detection unit located between the monitoring segments can collect images of the target installed at one end of the monitoring segment, and in order to ensure that all monitoring segments are measured, the target positions used for image collection in the two targets corresponding to each monitoring segment are consistent. At this time, the longitudinal deformation of a single monitoring segment can be obtained by summing the calculation results of two adjacent visual detection units.

Of course, the visual detection unit located between the monitoring sections can simultaneously capture images of the targets at both ends of the monitoring section, and the longitudinal deformation of the monitoring section can be obtained by adding the results of the image capture and reverse calculation of the targets at both ends by the visual detection unit. In the current situation, the visual detection unit is preferably installed in the middle of the wall of the monitoring section so that the initial distance from the visual detection unit to the targets at both ends of the monitoring section is the same.

Example 2: The visual detection unit is installed at a monitoring point at one end of the monitoring section, so that the visual detection unit can collect images of the target installed at the monitoring point at the other end of the monitoring section.

It can be understood that the longitudinal deformation of the monitoring segment can be regarded as the change in distance between the monitoring points at both ends. Therefore, the visual detection unit can be installed at one end of the monitoring segment. In this way, when the monitoring segment undergoes longitudinal deformation, the change in distance between the visual detection unit and the monitoring point at the other end of the monitoring segment can be regarded as the longitudinal deformation of the monitoring segment.

It should be known that both of the above examples can meet the requirements of this application, but in order to further improve the accuracy of collecting longitudinal deformation, the installation method of the visual detection unit in this embodiment preferably adopts the method in the above example 1 in which the visual detection unit simultaneously collects images of the targets at both ends of the monitoring section, so that the targets installed at each monitoring point can be captured by two visual detection units for mutual verification.

In this embodiment, based on the installation method of the visual detection unit and the temperature detection unit, the location of the fire point in step S200 includes the following process:

S210: numbering each monitoring section and the corresponding data; determining the number of fire points according to the numbers corresponding to the abnormal data, and locating the monitoring section position corresponding to each fire point.

S220: According to the data collected by the visual detection unit, the longitudinal deformations of both ends of the monitoring section corresponding to the fire point are compared.

S230: Locate the specific position of the fire point in the monitoring section according to the comparison results of the longitudinal deformations at both ends combined with the data of the temperature detection unit.

It should be known that a fire in a tunnel may be a single-source fire or a multi-source fire; single-source fire and multi-source fire can be judged based on the location of the fire. For ease of understanding, the specific judgment process of single-source fire and multi-source fire will be described in detail below.

For a single-source fire scenario, as shown in Figure 4, there are two specific locations of the fire point: one is near the middle of the monitoring section, that is, near the installation position of the visual detection unit and the temperature detection unit; the other is near the end of the monitoring section, that is, near the installation position of the target. For ease of understanding, the following will describe the two situations separately.

If only one monitoring segment has a sudden change in longitudinal deformation and temperature data at the same time, and the longitudinal deformation and temperature data of adjacent monitoring segments subsequently become abnormal, the monitoring system of the control center will issue a fire alarm and prompt the operator to confirm the fire. If the fire is confirmed, the monitoring segment position corresponding to the fire point can be located according to the monitoring segment number corresponding to the sudden change in longitudinal deformation and temperature data, and the fire source appears near the position of the visual detection unit, that is, near the middle of the monitoring segment.

If the deformation data on one side of only one monitoring section changes suddenly, the temperature data collected by the temperature detection unit at the same position will also change abnormally. At this time, the monitoring system of the control center will issue a fire alarm and prompt the operator to confirm the fire. If the fire is confirmed, the monitoring section position corresponding to the fire point can be located according to the monitoring section number corresponding to the longitudinal deformation mutation and the temperature data abnormality, and the fire point is close to the side position of the longitudinal deformation mutation of the monitoring section.

For multi-source fire scenarios, as shown in Figure 5, the specific location of the fire point is mainly the same as that of the single-source fire scenario, the difference is that there are multiple fire points. The method for determining the location of the fire point of a multi-source fire is the same as that of the single-source fire, the difference is that there are multiple data mutations, and each monitoring segment of the data mutation location corresponds to a fire point. That is, the multi-source fire scenario can be regarded as the separate judgment of multiple single-source fire scenarios.

It should be known that, taking Figures 4 and 5 as examples, when the fire point is located in the middle of the monitoring section, the longitudinal deformation mutations on the left and right sides of the monitoring section occur almost simultaneously, and the mutation values of the two are also basically the same. When the fire point is located on the side of the monitoring section, if the longitudinal deformation data mutation occurs first on the left side of the monitoring section and then on the right side, and the mutation amount on the left side is greater than the mutation amount on the right side, it can be determined that the fire point is located on the left side of the monitoring section; otherwise, the fire point is on the right side.

It is understandable that based on the coverage of abnormal data, the development of fire in the tunnel can be accurately grasped, including information such as fire scope, fire location, temperature gradient distribution, and continuous high temperature distribution, and linked with relevant equipment in the tunnel to issue tunnel fire alarm information to remind vehicles inside and outside the tunnel to pay attention to driving safety.

Those skilled in the art should know that there are joints in the tunnel during construction, and the joints can be divided into settlement joints and construction joints. Among them, the settlement joints cannot realize the transfer of longitudinal deformation between two adjacent tunnel sections, so as to avoid the longitudinal deformation interference of the tunnel sections on both sides of the settlement joints. The construction joint is the joint surface where the concrete is poured successively, and the longitudinal deformation of the adjacent tunnel sections can be transferred. Therefore, when arranging the monitoring system of the present application, it is only necessary to consider the settlement joints of the tunnel. The setting distance of the settlement joints can be comprehensively considered according to the length of the tunnel, the cross-sectional form, the geological conditions, the design load and other conditions. Therefore, according to the setting distance of the settlement joints, the monitoring section division method of the tunnel can be mainly divided into the following two methods.

Method 1: For settlement joints with shorter distances, the tunnel section between adjacent settlement joints can be directly set as the monitoring section. Then, n-1 settlement joints are required to form n continuous monitoring sections in the tunnel. Generally speaking, the value of n is greater than 1.

Method 2: For settlement joints with a long distance, as shown in Figure 2, the tunnel can be divided into n sections according to the number of settlement joints, and then the tunnel sections between adjacent settlement joints are divided into m sections according to appropriate lengths, so that the tunnel can have n×m monitoring sections.

It can be understood that both of the above two methods can meet the requirements of this application, and can be selected according to the actual needs of those skilled in the art. The values of n and m can be selected according to actual needs. For example, as shown in Figure 1, the value of n is greater than 1, and the value of m is 3. The longitudinal deformations of the three monitoring sections corresponding to adjacent settlement joints can be marked as ΔL ₁ , ΔL ₂ , and ΔL ₃ , respectively, and the corresponding temperatures are marked as ΔT ₁ , ΔT _2, and ΔT ₃ , respectively; the elastic moduli corresponding to the three monitoring sections are E ₁ , E ₂ , and E ₃ , respectively, and the elastic modulus is related to the ratio of the corresponding longitudinal deformation to the temperature.

In this embodiment, step S400 includes the following specific processes:

S410: Based on the mechanical properties of concrete, a concrete performance dataset is constructed through finite element simulation.

S42: Use deep learning methods to train the concrete performance data set to obtain a concrete performance evaluation model.

S430: Collect temperature and longitudinal deformation data of intact equipment sections after the disaster.

S440: Input the data collected in step S430 into the concrete performance evaluation model for inversion to obtain elastic modulus evaluation values of different monitoring sections of the tunnel.

S450: Compare the inversion result of step S440 with the design standard to determine the degree of structural degradation of each monitored section of the tunnel.

It can be understood that for the establishment of the concrete performance evaluation model; first, a finite element model of the tunnel concrete structure can be established in the finite element software based on the known mechanical properties of concrete; then the temperature is used as the input of the model, and the deformation relationship is used as the output of the model; by listing as many temperature parameters as possible and inputting them into the model to output the corresponding deformation, a data set including different temperatures and the deformations that match them can be obtained, i.e., a concrete performance data set. It should be known that the obtained concrete performance data already contains the longitudinal deformation corresponding to the different temperatures that may occur in the tunnel during use. Then, the concrete performance data set is trained through a deep learning model to obtain a concrete performance evaluation model, and the output of the concrete performance evaluation model is the elastic modulus E of the concrete structure.

For the front-end data collection of the target tunnel, the visual inspection unit and temperature detection unit of the intact section of the equipment can be used to obtain the surface temperature and longitudinal deformation of the monitoring section. Then the collected data is input into the concrete performance evaluation model to obtain the elastic modulus evaluation value of each monitoring section of the target tunnel. Finally, the obtained elastic modulus evaluation value is compared with the design standard to determine the degree of deterioration of the monitoring section.

It is important to know that after the data collected from the intact section of the equipment after the disaster is sent to the concrete performance evaluation model, the concrete performance evaluation model can use a table-like method to quickly match the input parameters with the concrete performance data set, and output the elastic modulus that has been calculated in advance according to the matched position, which can effectively improve the calculation speed of the model.

It should be known that the mechanical properties of concrete, that is, the initial elastic modulus E of concrete, can be obtained from the tunnel structure inspection report. The design standard of concrete can also be obtained from the tunnel structure inspection report. Generally speaking, the ultimate strength of the concrete structure that can operate normally can be used as the judgment threshold. Concrete structures with strengths lower than the ultimate strength of normal operation can be judged as abnormal, and vice versa.

In this embodiment, as shown in FIG6 , after completing step S420, the obtained concrete performance evaluation model is corrected, including the following process:

Preferably, after completing step S420, the obtained concrete performance evaluation model is corrected, including the following process:

S421: Substitute the historical data of the temperature and longitudinal deformation of the tunnel into the concrete performance evaluation model as correction data.

S422: Compare the output results of the concrete performance evaluation model with the historical elastic modulus data of the tunnel.

S423: If the error between the two is less than or equal to the set threshold, it means that the obtained concrete performance evaluation model meets the accuracy requirements.

S424: If the error between the two is greater than a set threshold, an error analysis is performed and the concrete performance evaluation model is corrected based on historical data.

It is understandable that the data in the concrete performance data set is obtained through finite element simulation, which is only theoretical deformation information obtained by theoretical calculation. In order to ensure that the obtained concrete performance evaluation model has sufficient accuracy, it is necessary to compare the actual value with the theoretical value to realize the correction of the concrete performance evaluation model. The historical data of the tunnel structure can be obtained from the tunnel structure monitoring report, and the temperature and deformation data of half a year to one year can be used as correction data.

The above describes the basic principles, main features and advantages of the present application. Those skilled in the art should understand that the present application is not limited by the above embodiments. The above embodiments and the specification only describe the principles of the present application. The present application may have various changes and improvements without departing from the spirit and scope of the present application. These changes and improvements fall within the scope of the present application for which protection is sought. The scope of protection claimed by the present application is defined by the attached claims and their equivalents.

Claims (10)

1. A method for locating a tunnel fire and monitoring lining structure damage after a disaster, characterized in that it comprises the following steps: S100: Divide the tunnel into a plurality of adjacent monitoring sections along the longitudinal length direction, and arrange a deformation detection module and a temperature detection unit for detecting longitudinal deformation and surface temperature for each of the monitoring sections; S200: When the detection data of the deformation detection module and/or the temperature detection unit is abnormal, the fire point is located according to the monitoring section position corresponding to the abnormal data and an alarm is issued to the control center; S300: After the fire is over, the monitoring section where the fire occurred is divided into a damaged equipment section and an intact equipment section according to the damage of the equipment; S400: For the equipment intact section, structural damage analysis of the tunnel lining is performed based on the data re-detected by the deformation detection module and the temperature detection unit after the disaster. 2. The method for locating tunnel fires and monitoring lining structure damage after a disaster as described in claim 1 is characterized in that the deformation detection module includes a monitoring point and a visual detection unit; the monitoring point is arranged at the end of the monitoring section, and the visual detection unit is installed on the monitoring section; the visual detection unit is suitable for performing image acquisition on the monitoring point to obtain the longitudinal deformation of the monitoring section. 3. The method for locating tunnel fires and monitoring lining structure damage after disasters as described in claim 2 is characterized in that a plurality of monitoring points are arranged at the end of the monitoring section, and the plurality of monitoring points are arranged at equal intervals along the cross-sectional contour direction of the tunnel. 4. The method for locating tunnel fires and monitoring lining structure damage after disasters as described in claim 2 is characterized in that a target is installed at the monitoring point, and the visual detection unit is suitable for capturing images of the target, and then obtaining the longitudinal deformation corresponding to the monitoring section according to the change in the imaging size of the target. 5. The method for locating tunnel fire and monitoring lining structure damage after a disaster as described in claim 4 is characterized in that the visual detection unit is installed at one end of the monitoring section to collect images of the target at the other end of the monitoring section. 6. The method for locating tunnel fires and monitoring lining structure damage after a disaster as described in claim 4 is characterized in that the targets are installed at both ends of the monitoring section, the visual detection unit is installed in the middle of the monitoring section, and the visual detection unit simultaneously collects images of the targets at both ends of the monitoring section. 7. The method for locating a tunnel fire and monitoring lining structure damage after a disaster as claimed in claim 6, characterized in that the location of the fire point in step S200 includes the following process: S210: numbering each monitoring segment and the corresponding data; determining the number of fire points according to the numbers corresponding to the abnormal data, and locating the monitoring segment position corresponding to each fire point; S220: comparing the longitudinal deformations of both ends of the monitoring section corresponding to the fire point according to the data collected by the visual detection unit; S230: Locate the specific position of the fire point in the monitoring section according to the comparison results of the longitudinal deformations at both ends and the data of the temperature detection unit. 8. The method for locating a tunnel fire and monitoring damage to a lining structure after a disaster as described in claim 1 is characterized in that a plurality of settlement joints are formed along the longitudinal length direction of the tunnel according to construction, the tunnel is divided into n sections according to the positions of the settlement joints, and the tunnel between adjacent settlement joints is divided into m sections, thereby obtaining n×m monitoring sections. 9. The method for locating a tunnel fire and monitoring lining structure damage after a disaster according to any one of claims 1 to 8, characterized in that step S400 comprises the following specific processes: S410: Based on the mechanical properties of concrete, a concrete performance data set is constructed through finite element simulation; S420: training the concrete performance data set using a deep learning method to obtain a concrete performance evaluation model; S430: Collect temperature and longitudinal deformation data of intact equipment sections after the disaster; S440: inputting the data collected in step S430 into the concrete performance evaluation model for inversion to obtain the actual elastic modulus of different monitoring sections of the tunnel; S450: Compare the inversion result of step S440 with the design standard to determine the degree of structural degradation of the intact section of the equipment. 10. The method for locating a tunnel fire and monitoring damage to a lining structure after a disaster as claimed in claim 9, characterized in that after completing step S420, the obtained concrete performance evaluation model is corrected, comprising the following process: S421: Substituting historical data of tunnel temperature and longitudinal deformation into a concrete performance evaluation model as correction data; S422: Compare the output results of the concrete performance evaluation model with the historical elastic modulus data of the tunnel; S423: If the error between the two is less than or equal to the set threshold, it means that the obtained concrete performance evaluation model meets the accuracy requirement; S424: If the error between the two is greater than a set threshold, an error analysis is performed and the concrete performance evaluation model is corrected based on historical data.