Traffic tunnel inspection safety monitoring method, equipment and medium

Abstract

The invention discloses an inspection safety monitoring method and equipment for a traffic tunnel, and a medium, belongs to the technical field of traffic tunnels, and is used for solving the technical problems that the daily inspection of an existing traffic tunnel is relatively difficult, the hidden danger problem of the traffic tunnel is relatively slow to find, the management workload of manual inspection is relatively large, and the cost of maintenance inspection is relatively high. The method comprises the following steps: performing conventional hidden danger factor identification on a traffic tunnel under multiple areas according to a regular inspection route, and determining conventional inspection information; performing identification processing on the emergency hidden danger factors in the traffic tunnel through a monitoring camera in the traffic tunnel, and determining positioning information corresponding to the emergency hidden danger factors; according to the positioning information, carrying out hidden danger feature identification on the emergency hidden danger factors, and determining emergency inspection information; performing alarm grade division on the conventional inspection information and the emergency inspection information to obtain an inspection safety grade; and determining an inspection prevention and control strategy based on the inspection safety level.

Description

Technical Field

[0001] The present application relates to the field of traffic tunnels, and in particular to a method, equipment and medium for patrol safety monitoring of traffic tunnels. Background Art

[0002] Highway traffic construction has always been the top priority of my country's infrastructure construction. With the continuous advancement of highway construction to inland mountainous areas, the construction of tunnel projects has also increased. This has made my country one of the countries with the largest number and mileage of tunnel construction in the world. Although tunnel construction faces arduous challenges, it has also promoted the development of tunnel engineering technology, and the operation and maintenance management of tunnels has also received more and more attention from departments at all levels.

[0003] As more and more highway tunnels enter periodic maintenance, various operating companies have accumulated a lot of experience in tunnel maintenance and management, but there are still many defects in daily patrol and regular inspection work, mainly: daily maintenance and patrol management are rough, timeliness is poor, and too long an inspection cycle cannot make up for the defects of daily patrol work; my country has a vast territory, complex mountainous geographical environment, and large differences in the environment of the areas through which tunnels pass. Tunnel patrol maintenance and management work has its own particularity. With the passage of time, tunnel diseases increase, and the difficulty of patrol increases. It requires a lot of manpower and material resources for daily patrol, with high labor costs and high risks of patrol. At the same time, manual patrol is also prone to consume a lot of energy, low efficiency and prone to patrol errors in traffic tunnels, which is not conducive to the safe passage of vehicles in traffic tunnels. Summary of the invention

[0004] The embodiments of the present application provide a traffic tunnel inspection safety monitoring method, equipment and medium, which are used to solve the following technical problems: routine inspections of existing traffic tunnels are relatively difficult, hidden dangers in traffic tunnels are discovered slowly, the management workload of manual inspections is large, and the costs of maintenance inspections are high.

[0005] The present application embodiment adopts the following technical solutions:

[0006] On the one hand, an embodiment of the present application provides a patrol safety monitoring method for a traffic tunnel, comprising: determining a scheduled patrol route for an intelligent patrol device based on structural characteristics of the traffic tunnel; identifying conventional hidden danger factors in multiple areas of the traffic tunnel according to the scheduled patrol route, and determining conventional patrol information; identifying and processing emergency hidden danger factors in the traffic tunnel through monitoring cameras in the traffic tunnel, and determining positioning information corresponding to the emergency hidden danger factors; controlling the intelligent patrol device to complete route cruising according to the positioning information, and identifying hidden danger characteristics of the emergency hidden danger factors, and determining emergency patrol information; dividing the conventional patrol information and the emergency patrol information into alarm levels to obtain a patrol safety level; and determining a patrol prevention and control strategy based on the patrol safety level.

[0007] The embodiment of the present application can ensure systematic inspection of various areas of the traffic tunnel by determining the scheduled inspection route of the intelligent inspection equipment, thereby improving the coverage and efficiency of the inspection. In this way, various safety hazards in the tunnel can be fully detected and identified. Once an emergency hidden danger factor is found, the intelligent inspection equipment can be quickly controlled to go to the location to identify the hidden danger characteristics, which helps to take timely measures to deal with the emergency and ensure the safety of the tunnel. It helps to reasonably allocate resources and take corresponding emergency measures according to the severity of the hidden danger. It helps to improve the safety of traffic tunnels, reduce the risk of accidents, and ensure the safety of pedestrians and vehicles. It realizes the intelligence and automation of inspection work, reduces manual intervention, and improves the accuracy and reliability of inspection. It can also provide data support for tunnel management departments to help them make scientific decisions and optimize the operation and maintenance of tunnels.

[0008] In a feasible implementation, based on the structural characteristics of the traffic tunnel, the scheduled inspection route of the intelligent inspection equipment is determined, which specifically includes: obtaining the basic structural information of the traffic tunnel; wherein the basic structural information at least includes: length information, width information, height information, internal space information and tunnel direction information; performing modeling analysis on the basic structural information related to the three-dimensional model, and extracting structural features for modeling; wherein the structural features at least include: reference surface features, construction line features, spatial position features and position features of each device in the tunnel; based on the structural features, establishing a three-dimensional space model inside the tunnel; dividing the three-dimensional space model inside the tunnel by center lines, and according to the The center line is used to project and map the inner wall of the tunnel in the three-dimensional space model of the tunnel to determine a first inner wall mapping line and a second inner wall mapping line; wherein the first inner wall mapping line and the second inner wall mapping line are connecting lines between the entrance and the exit of the traffic tunnel; the position distribution information of the position features of each device in the tunnel in the structural features is collected on the inner wall of the tunnel; the first inner wall mapping line and the second inner wall mapping line are respectively calculated to overlap with the position distribution information to determine the inner wall mapping line with the minimum overlap; according to the inner wall mapping line with the minimum overlap, the rail route of the intelligent inspection equipment is correspondingly installed to obtain the scheduled inspection route.

[0009] In a feasible implementation manner, according to the scheduled inspection route, conventional hidden danger factors in multiple areas of the traffic tunnel are identified to determine conventional inspection information, specifically including: based on the light and dark change trend of the traffic tunnel, the traffic tunnel is divided into areas of brightness gradient to obtain brightness change areas; according to the brightness change areas and the corresponding regional tunnel lengths, the inspection time of the intelligent inspection equipment is divided into time periods to obtain the inspection time of each brightness change area; according to the inspection time and the scheduled inspection route, and through the intelligent inspection equipment, the dynamic hidden danger factors and static hidden danger factors in the traffic tunnel are imaged and processed to obtain dynamic hidden danger images and static hidden danger images; wherein the dynamic hidden danger factors include at least: traffic flow operation information, road spillage information and abnormal object information; the static hidden danger factors include at least: tunnel internal temperature information, tunnel water seepage information, tunnel wall peeling information, tunnel road surface information and tunnel disease information; through SIFT technology, the dynamic and static image features in the dynamic hidden danger image and the static hidden danger image are extracted, and the conventional inspection information is generated.

[0010] In a feasible implementation manner, emergency hidden danger factors in the traffic tunnel are identified and processed by monitoring cameras in the traffic tunnel, and the positioning information corresponding to the emergency hidden danger factors is determined, specifically including: based on the monitoring cameras in different brightness change areas in the traffic tunnel, real-time acquisition of tunnel internal images under continuous frames within a preset time interval; converting the text information corresponding to the emergency hidden danger factors into a feature image template to obtain an emergency hidden danger feature template; wherein the emergency hidden danger factors at least include: fire pixel features, water accumulation pixel features, traffic congestion pixel features, traffic accident pixel features, smoke pixel features, wall seepage pixel features and lighting failure pixel features; extracting several grayscale pixel features of the tunnel internal image; matching the grayscale pixel features with the emergency hidden danger feature template for pixel features to determine the emergency hidden danger type information; identifying the brightness change area position corresponding to the emergency hidden danger type information, and based on the brightness change area position, determining the positioning information of the emergency hidden danger factor in the brightness change area.

[0011] In a feasible implementation, before controlling the intelligent patrol device to complete route cruising according to the positioning information, identifying hidden danger features of the emergency hidden danger factors, and determining the emergency patrol information, the method also includes: based on the positioning information, changing the position instructions of the current position information of the intelligent patrol device, and generating an emergency patrol route; through the emergency patrol route, controlling the intelligent patrol device to run to the edge of the brightness change area corresponding to the positioning information; through the three-dimensional visual acquisition system of the intelligent patrol device, traversing the internal space of the tunnel in the current brightness change area, and generating a three-dimensional stereogram; based on the emergency hidden danger type information in the positioning information, punctuating the initial contour of the three-dimensional stereogram to obtain emergency hidden danger location information; according to the emergency hidden danger location information and through the intelligent patrol device, collecting the emergency hidden danger image under the wide-angle view corresponding to the emergency hidden danger factor.

[0012] In a feasible implementation, according to the positioning information, the intelligent inspection device is controlled to complete route cruising, and the emergency hidden danger factors are identified for hidden danger features to determine the emergency inspection information, which specifically includes: extracting several hidden danger features in the emergency hidden danger image through a preset deep neural network; determining the pixel areas corresponding to the several hidden danger features as candidate areas; and correcting the coordinate information of the candidate areas; assigning categories to each pixel in the candidate areas, and performing target segmentation processing on the emergency hidden danger factors in the candidate areas through instance segmentation technology to obtain an emergency hidden danger type image; performing semantic analysis and generation on the emergency hidden danger type image to obtain the emergency inspection information.

[0013] In a feasible implementation manner, the routine inspection information and the emergency inspection information are divided into alarm levels to obtain an inspection safety level, which specifically includes: evaluating and calculating the hidden danger change trend of the routine inspection information to obtain a routine hidden danger evaluation value; and evaluating and calculating the danger urgency of the emergency hidden danger inspection information to obtain an emergency hidden danger evaluation value; if the routine hidden danger evaluation value is greater than a first preset threshold and less than a second preset threshold, the routine inspection information is determined to be a low routine hidden danger level; if the routine hidden danger evaluation value is greater than or equal to the second preset threshold, the routine inspection information is determined to be a high routine hidden danger level; if the emergency hidden danger evaluation value is greater than a third preset threshold and less than a fourth preset threshold, the emergency hidden danger inspection information is determined to be a low emergency hidden danger level; if the emergency hidden danger evaluation value is greater than or equal to the fourth preset threshold, the emergency hidden danger inspection information is determined to be a high emergency hidden danger level; at the same time node, based on the low routine hidden danger level and the high routine hidden danger level, a dual danger level judgment is performed on the low emergency hidden danger level and the high emergency hidden danger level to determine the inspection safety level.

[0014] In a feasible implementation, based on the inspection safety level, an inspection prevention and control strategy is determined, specifically including: through a preset tunnel safety auxiliary decision-making system, the inspection safety level is digitally matched with the tunnel safety management event to determine the inspection prevention and control event; the inspection prevention and control event is comprehensively analyzed to determine the inspection prevention and control strategy; wherein the comprehensive analysis includes: pre-analysis, in-process analysis and post-analysis.

[0015] In a second aspect, an embodiment of the present application also provides a patrol safety monitoring device for a traffic tunnel, the device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor so that the at least one processor can execute a patrol safety monitoring method for a traffic tunnel as described in any of the above-mentioned embodiments.

[0016] In a third aspect, an embodiment of the present application further provides a non-volatile computer storage medium, characterized in that the storage medium is a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores at least one program, each of which includes instructions, and when the instructions are executed by a terminal, the terminal executes a patrol safety monitoring method for a traffic tunnel described in any of the above-mentioned embodiments.

[0017] The present application provides a method, device and medium for patrol safety monitoring of a traffic tunnel. Compared with the prior art, the embodiments of the present application have the following beneficial technical effects:

[0018] 1. Improve inspection efficiency: By determining the scheduled inspection route of the intelligent inspection equipment, it is possible to ensure systematic inspection of various areas of the traffic tunnel, thereby improving the coverage and efficiency of the inspection.

[0019] 2. Comprehensive hidden danger identification: This method not only takes into account conventional hidden danger factors, but also identifies emergency hidden danger factors through monitoring cameras and determines their location information. This can comprehensively detect and identify various safety hazards in the tunnel.

[0020] 3. Quick response to emergencies: Once an emergency hidden danger factor is discovered, the intelligent inspection equipment can be quickly controlled to go to the location to identify the hidden danger characteristics, which helps to take timely measures to deal with the emergency and ensure the safety of the tunnel.

[0021] 4. Alarm level classification and prevention and control strategies: Inspection information is classified into alarm levels, and inspection and prevention and control strategies are determined based on the levels, which helps to reasonably allocate resources and take corresponding emergency measures according to the severity of hidden dangers.

[0022] 5. Improve tunnel safety: By timely discovering and dealing with hidden dangers, it helps to improve the safety of traffic tunnels, reduce the risk of accidents, and ensure the safety of pedestrians and vehicles.

[0023] 6. Intelligence and automation: The use of intelligent inspection equipment and surveillance cameras has realized the intelligence and automation of inspection work, reduced manual intervention, and improved the accuracy and reliability of inspection.

[0024] 7. Data support and decision-making basis: The inspection information provided can provide data support for the tunnel management department, helping them make scientific decisions and optimize the operation and maintenance of the tunnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0026] Figure 1 A flow chart of a method for patrol safety monitoring of a traffic tunnel provided in an embodiment of the present application;

[0027] Figure 2A schematic structural diagram of a traffic tunnel inspection safety monitoring device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0029] The present application embodiment provides a traffic tunnel inspection safety monitoring method, such as Figure 1 As shown, the inspection safety monitoring method of a traffic tunnel specifically includes steps S101-S106:

[0030] S101. Determine a scheduled inspection route for intelligent inspection equipment based on structural characteristics of the traffic tunnel.

[0031] Specifically, it is necessary to first obtain the basic structural information of the traffic tunnel. The basic structural information includes at least: length information, width information, height information, internal space information and tunnel direction information. The basic structural information is modeled and analyzed for the three-dimensional model, and the structural features used for modeling are extracted. The structural features include at least: reference surface features, construction line features, spatial position features and the position features of each device in the tunnel. Based on the structural features, a three-dimensional space model of the tunnel interior is established.

[0032] Furthermore, the three-dimensional space model inside the tunnel is divided by the center line, and the inner wall of the tunnel in the three-dimensional space model inside the tunnel is projected and mapped according to the center line to determine the first inner wall mapping line and the second inner wall mapping line. The first inner wall mapping line and the second inner wall mapping line are the connecting lines between the entrance and the exit of the traffic tunnel.

[0033] Furthermore, the position distribution information of the position features of each device in the tunnel on the inner wall of the tunnel is collected.

[0034] Furthermore, it is necessary to calculate the position coincidence between the first inner wall mapping line and the second inner wall mapping line and the position distribution information respectively, so as to determine the inner wall mapping line with the minimum coincidence degree.

[0035] Furthermore, according to the inner wall mapping line at the minimum overlap, the rail route of the intelligent inspection equipment is installed accordingly, and a scheduled inspection route is obtained.

[0036] S102. According to the scheduled inspection route, conventional hidden danger factors in multiple areas of the traffic tunnel are identified to determine conventional inspection information.

[0037] Specifically, based on the light and dark change trend of the traffic tunnel, the traffic tunnel is first divided into regions of brightness gradient to obtain brightness change regions.

[0038] Furthermore, according to the brightness change area and the corresponding regional tunnel length, the inspection time of the intelligent inspection device is divided into time periods to obtain the inspection time of each brightness change area.

[0039] Furthermore, according to the inspection time and the scheduled inspection route, and through the intelligent inspection equipment, the dynamic hidden danger factors and static hidden danger factors in the traffic tunnel are imaged and processed to obtain dynamic hidden danger images and static hidden danger images. Among them, the dynamic hidden danger factors at least include: traffic flow information, road spillage information and abnormal object information. The static hidden danger factors at least include: tunnel internal temperature information, tunnel water seepage information, tunnel wall peeling information, tunnel road surface information and tunnel disease information.

[0040] Furthermore, SIFT technology is used to extract dynamic and static image features in dynamic hidden danger images and static hidden danger images, and generate regular inspection information.

[0041] S103. Using the surveillance cameras in the traffic tunnel, identify and process emergency hidden danger factors in the traffic tunnel, and determine the location information corresponding to the emergency hidden danger factors.

[0042] Specifically, firstly, based on the surveillance cameras in different brightness change areas in the traffic tunnel, the tunnel interior images in continuous frames are collected in real time within a preset time interval.

[0043] Furthermore, it is necessary to convert the text information corresponding to the emergency hidden danger factors into a feature image template to obtain an emergency hidden danger feature template. Among them, the emergency hidden danger factors at least include: fire pixel features, water accumulation pixel features, traffic congestion pixel features, traffic accident pixel features, smoke pixel features, wall water seepage pixel features and lighting failure pixel features.

[0044] Furthermore, several grayscale pixel features of the tunnel internal image are extracted. Then, the grayscale pixel features are matched with the emergency hidden danger feature template to determine the emergency hidden danger type information. The position of the brightness change area corresponding to the emergency hidden danger type information is identified, and based on the position of the brightness change area, the location information of the emergency hidden danger factor in the brightness change area is determined.

[0045] S104. According to the positioning information, the intelligent inspection equipment is controlled to complete the route patrol, and the hidden danger characteristics of the emergency hidden danger factors are identified to determine the emergency inspection information.

[0046] Specifically, the current position information of the intelligent inspection device is changed by the position instruction using the positioning information, and an emergency cruise route is generated. Through the emergency cruise route, the intelligent inspection device is controlled to run to the edge of the brightness change area corresponding to the positioning information.

[0047] Furthermore, the three-dimensional visual acquisition system of the intelligent inspection equipment traverses the internal space of the tunnel in the current brightness change area and generates a three-dimensional stereogram. Based on the emergency hidden danger type information in the positioning information, the initial outline of the three-dimensional stereogram is punctuated and the emergency hidden danger location information is obtained.

[0048] As a feasible implementation method, the 3D visual acquisition system is composed of high-precision visual measurement components such as high-precision infrared sensors, laser radars and industrial panoramic cameras. The industrial panoramic camera plays a role in intelligent positioning and identification of tunnel diseases. The laser radar can accurately collect 3D tunnel environment information and construct a detailed cloud map, which plays a role in traffic monitoring and road spillage identification. The infrared sensor is responsible for measuring the thermal image of the tunnel surface temperature, which can detect abnormal temperature areas and play a role in tunnel fire detection.

[0049] Furthermore, it is also necessary to collect emergency hazard images under a wide-angle view corresponding to the emergency hazard factors based on the emergency hazard location information and through intelligent inspection equipment.

[0050] Furthermore, a preset deep neural network is used to extract several hidden danger features in the emergency hidden danger image; the pixel areas corresponding to the several hidden danger features are determined as candidate areas. The coordinate information of the candidate areas is corrected. Each pixel in the candidate area is assigned a category, and the emergency hidden danger factors in the candidate area are segmented by instance segmentation technology to obtain an emergency hidden danger type image.

[0051] Furthermore, semantic analysis and generation are performed on emergency hidden danger type images to obtain emergency inspection information.

[0052] In one embodiment, deep learning-based image segmentation technology is used to achieve high-level analysis of diseases. The algorithm can divide an image into several super pixels and perform high-level analysis on the image, mainly semantic segmentation and instance segmentation. Semantic segmentation assigns a category to each pixel, and instance segmentation further classifies pixels based on semantic segmentation to improve the precision and accuracy of segmentation.

[0053] S105, classify the routine inspection information and the emergency inspection information into alarm levels to obtain the inspection safety level.

[0054] Specifically, the conventional inspection information is evaluated and calculated for the trend of hidden danger changes to obtain a conventional hidden danger evaluation value, and the emergency hidden danger inspection information is evaluated and calculated for the degree of danger urgency to obtain an emergency hidden danger evaluation value.

[0055] If the conventional hidden danger assessment value is greater than the first preset threshold and less than the second preset threshold, the conventional inspection information is determined as a low conventional hidden danger level. If the conventional hidden danger assessment value is greater than or equal to the second preset threshold, the conventional inspection information is determined as a high conventional hidden danger level.

[0056] If the emergency hazard assessment value is greater than the third preset threshold and less than the fourth preset threshold, the emergency hazard inspection information is determined as a low emergency hazard level. If the emergency hazard assessment value is greater than or equal to the fourth preset threshold, the emergency hazard inspection information is determined as a high emergency hazard level.

[0057] Finally, at the same time point, it is necessary to make a double danger level judgment on the low emergency hazard level and the high emergency hazard level based on the low routine hazard level and the high routine hazard level to determine the inspection safety level.

[0058] As a feasible implementation method, at the same time node, if the data collected is that the interior of the tunnel is in a state of low conventional hidden danger level and low emergency hidden danger level, the inspection safety level will be judged as a low-level hidden danger inspection level. If the data collected is that the interior of the tunnel is in a state of low conventional hidden danger level and high emergency hidden danger level, the inspection safety level will be judged as a high-level first-class hidden danger inspection level. If the data collected is that the interior of the tunnel is in a state of high conventional hidden danger level and low emergency hidden danger level, the inspection safety level will be judged as a high-level second-class hidden danger inspection level. If the data collected is that the interior of the tunnel is in a state of high conventional hidden danger level and high emergency hidden danger level, the inspection safety level will be judged as a special-level hidden danger inspection level. Based on the different judged inspection safety levels, the processing status of the traffic tunnel can be determined, and corresponding staff can be arranged to increase manpower and implement corresponding solutions for different hidden danger inspection levels.

[0059] S106. Determine the inspection prevention and control strategy based on the inspection safety level.

[0060] Specifically, through the preset tunnel safety decision-making support system, the inspection safety level is matched with the tunnel safety management events in a digital way to determine the inspection prevention and control events; the inspection prevention and control events are analyzed in an all-round way to determine the inspection prevention and control strategy. Among them, the all-round analysis includes: pre-analysis, in-process analysis and post-analysis.

[0061] In one embodiment, the tunnel safety decision-making support system is used to perform data matching on different tunnel safety management events. Therefore, once a corresponding event occurs, the intelligent analysis and decision-making support system can conduct comprehensive management before, during, and after the event, thereby analyzing the inspection and prevention strategies that can solve the hidden problems in the tunnel.

[0062] In addition, the present application also provides a traffic tunnel inspection safety monitoring device, such as Figure 2 As shown, the inspection safety monitoring equipment 200 for a traffic tunnel specifically includes:

[0063] At least one processor 201. And a memory 202 in communication with the at least one processor 201. The memory 202 stores instructions that can be executed by the at least one processor 201, so that the at least one processor 201 can execute:

[0064] Based on the structural characteristics of the traffic tunnel, determine the scheduled inspection route of the intelligent inspection equipment;

[0065] According to the scheduled inspection route, the conventional hidden danger factors in multiple areas of the traffic tunnel are identified to determine the conventional inspection information;

[0066] Through the surveillance cameras in the traffic tunnel, the emergency hidden danger factors in the traffic tunnel are identified and processed, and the location information corresponding to the emergency hidden danger factors is determined;

[0067] According to the positioning information, the intelligent inspection equipment is controlled to complete the route patrol, and the hidden danger characteristics of emergency hidden danger factors are identified to determine the emergency inspection information;

[0068] Routine inspection information and emergency inspection information are divided into alarm levels to obtain inspection safety levels;

[0069] Based on the inspection safety level, determine the inspection prevention and control strategy.

[0070] The embodiment of the present application can ensure systematic inspection of various areas of the traffic tunnel by determining the scheduled inspection route of the intelligent inspection equipment, thereby improving the coverage and efficiency of the inspection. In this way, various safety hazards in the tunnel can be fully detected and identified. Once an emergency hidden danger factor is found, the intelligent inspection equipment can be quickly controlled to go to the location to identify the hidden danger characteristics, which helps to take timely measures to deal with the emergency and ensure the safety of the tunnel. It helps to reasonably allocate resources and take corresponding emergency measures according to the severity of the hidden danger. It helps to improve the safety of traffic tunnels, reduce the risk of accidents, and ensure the safety of pedestrians and vehicles. It realizes the intelligence and automation of inspection work, reduces manual intervention, and improves the accuracy and reliability of inspection. It can also provide data support for tunnel management departments to help them make scientific decisions and optimize the operation and maintenance of tunnels.

[0071] Each embodiment in this application is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0072] The devices and media provided in the embodiments of the present application correspond one-to-one to the methods. Therefore, the devices and media also have similar beneficial technical effects as the corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0073] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0074] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0075] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0077] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0078] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0079] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0080] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0081] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the specification of the present application.

Claims

1. A traffic tunnel inspection safety monitoring method, characterized in that: The method comprises: Based on the structural characteristics of the traffic tunnel, determine the scheduled inspection route of the intelligent inspection equipment; According to the scheduled inspection route, conventional hidden danger factors in multiple areas of the traffic tunnel are identified to determine conventional inspection information; By using the surveillance camera in the traffic tunnel, the emergency hidden danger factors in the traffic tunnel are identified and processed, and the positioning information corresponding to the emergency hidden danger factors is determined; According to the positioning information, the intelligent inspection device is controlled to complete the route cruise, and the hidden danger characteristics of the emergency hidden danger factors are identified to determine the emergency inspection information; Classify the routine inspection information and the emergency inspection information into alarm levels to obtain an inspection safety level; Based on the inspection safety level, an inspection prevention and control strategy is determined.

2. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: Based on the structural characteristics of the traffic tunnel, the scheduled inspection route of the intelligent inspection equipment is determined, including: Obtaining basic structural information of the traffic tunnel; wherein the basic structural information at least includes: length information, width information, height information, internal space information and tunnel direction information; The basic structural information is subjected to modeling analysis related to the three-dimensional model, and structural features used for modeling are extracted; wherein the structural features at least include: reference plane features, construction line features, spatial position features, and position features of various equipment in the tunnel; Based on the structural features, a three-dimensional spatial model of the interior of the tunnel is established; The three-dimensional space model inside the tunnel is divided by a center line, and according to the center line, the inner wall of the tunnel in the three-dimensional space model inside the tunnel is projected and mapped to determine a first inner wall mapping line and a second inner wall mapping line; wherein the first inner wall mapping line and the second inner wall mapping line are connecting lines between the entrance and the exit of the traffic tunnel; Collecting the position distribution information of each equipment position feature in the tunnel among the structural features on the inner wall of the tunnel; Performing position coincidence calculation on the first inner wall mapping line and the second inner wall mapping line respectively with the position distribution information to determine the inner wall mapping line with the minimum coincidence degree; According to the inner wall mapping line with the minimum overlap, the rail route of the intelligent inspection equipment is installed accordingly, and the scheduled inspection route is obtained.

3. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: According to the scheduled inspection route, conventional hidden danger factors in multiple areas of the traffic tunnel are identified to determine conventional inspection information, specifically including: Based on the light and dark change trend of the traffic tunnel, the traffic tunnel is divided into regions with brightness gradients to obtain brightness change regions; According to the brightness change area and the corresponding regional tunnel length, the inspection time of the intelligent inspection device is divided into time periods to obtain the inspection time of each brightness change area; According to the inspection time and the scheduled inspection route, and through the intelligent inspection equipment, the dynamic hidden danger factors and the static hidden danger factors in the traffic tunnel are imaged and processed to obtain dynamic hidden danger images and static hidden danger images; wherein the dynamic hidden danger factors at least include: traffic flow operation information, road spillage information and abnormal object information; the static hidden danger factors at least include: tunnel internal temperature information, tunnel water seepage information, tunnel wall peeling information, tunnel road surface information and tunnel disease information; The dynamic and static image features in the dynamic hidden danger image and the static hidden danger image are extracted by using SIFT technology, and the conventional inspection information is generated.

4. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: By using the surveillance camera in the traffic tunnel, the emergency hidden danger factors in the traffic tunnel are identified and processed, and the location information corresponding to the emergency hidden danger factors is determined, specifically including: Based on the monitoring cameras in different brightness change areas in the traffic tunnel, real-time acquisition of tunnel interior images in continuous frames within a preset time interval; The text information corresponding to the emergency hidden danger factor is converted into a feature image template to obtain an emergency hidden danger feature template; wherein the emergency hidden danger factor at least includes: fire pixel features, water accumulation pixel features, traffic congestion pixel features, traffic accident pixel features, smoke pixel features, wall water seepage pixel features and lighting failure pixel features; Extracting a number of grayscale pixel features of the tunnel interior image; Perform pixel feature matching processing on the grayscale pixel feature and the emergency hidden danger feature template to determine the emergency hidden danger type information; The position of the brightness change area corresponding to the emergency hidden danger type information is identified, and based on the position of the brightness change area, the positioning information of the emergency hidden danger factor in the brightness change area is determined.

5. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: Before controlling the intelligent inspection device to complete route cruising according to the positioning information, and identifying the hidden danger characteristics of the emergency hidden danger factors to determine the emergency inspection information, the method further includes: Based on the positioning information, the current position information of the intelligent inspection device is processed by changing the position instruction, and an emergency patrol route is generated; Through the emergency cruise route, the intelligent inspection device is controlled to run to the edge of the brightness change area corresponding to the positioning information; Through the three-dimensional visual acquisition system of the intelligent inspection device, the internal space of the tunnel in the current brightness change area is traversed and a three-dimensional stereogram is generated; Based on the emergency hidden danger type information in the positioning information, the punctuation positioning of the initial outline of the three-dimensional stereogram is performed to obtain the emergency hidden danger position information; According to the emergency hidden danger location information and through the intelligent inspection device, an emergency hidden danger image under a wide-angle view corresponding to the emergency hidden danger factor is collected.

6. A traffic tunnel inspection safety monitoring method according to claim 5, characterized in that: According to the positioning information, the intelligent inspection device is controlled to complete the route cruise, and the hidden danger characteristics of the emergency hidden danger factors are identified to determine the emergency inspection information, which specifically includes: Extracting several hidden danger features in the emergency hidden danger image through a preset deep neural network; Determine the pixel areas corresponding to the plurality of hidden danger features as candidate areas; and perform correction processing on the coordinate information of the candidate areas; Assigning a category to each pixel in the candidate area, and performing target segmentation processing on the emergency hidden danger factors in the candidate area through instance segmentation technology to obtain an emergency hidden danger type image; Semantic analysis and generation are performed on the emergency hidden danger type image to obtain the emergency inspection information.

7. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: The routine inspection information and the emergency inspection information are divided into alarm levels to obtain the inspection safety level, which specifically includes: The conventional inspection information is evaluated and calculated for the trend of hidden danger changes to obtain a conventional hidden danger evaluation value; and the emergency hidden danger inspection information is evaluated and calculated for the degree of danger urgency to obtain an emergency hidden danger evaluation value; If the conventional hidden danger assessment value is greater than the first preset threshold value and less than the second preset threshold value, the conventional inspection information is determined as a low conventional hidden danger level; If the conventional hidden danger assessment value is greater than or equal to the second preset threshold, the conventional inspection information is determined as a high conventional hidden danger level; If the emergency hidden danger assessment value is greater than the third preset threshold value and less than the fourth preset threshold value, the emergency hidden danger inspection information is determined as a low emergency hidden danger level; If the emergency hidden danger assessment value is greater than or equal to the fourth preset threshold, the emergency hidden danger inspection information is determined as a high emergency hidden danger level; At the same time point, based on the low conventional hazard level and the high conventional hazard level, a dual hazard level judgment is performed on the low emergency hazard level and the high emergency hazard level to determine the inspection safety level.

8. A traffic tunnel inspection safety monitoring method according to claim 1, characterized in that: Based on the inspection safety level, the inspection prevention and control strategy is determined, including: Through the preset tunnel safety auxiliary decision-making system, the inspection safety level is matched with the tunnel safety management event in a digital manner to determine the inspection prevention and control event; Conduct a comprehensive analysis of the inspection and prevention events to determine the inspection and prevention strategy; wherein the comprehensive analysis includes: pre-analysis, in-analysis, and post-analysis.

9. A patrol safety monitoring device for a traffic tunnel, characterized in that: The device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, so that the at least one processor can execute the inspection safety monitoring method for a traffic tunnel according to any one of claims 1-8.

10. A non-volatile computer storage medium, characterized in that: The storage medium is a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores at least one program, each of which includes instructions, and when the instructions are executed by the terminal, the terminal executes the inspection safety monitoring method for a traffic tunnel according to any one of claims 1-8.

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