Bridge safety early warning method and device based on bridge tunnel structure and storage medium

Abstract

The invention provides a bridge safety early warning method and device based on a bridge tunnel structure and a storage medium, and the early warning method comprises the steps: obtaining a meteorological data set at each sampling point based on a meteorological sensor of a plurality of sampling points; acquiring a meteorological sharing index; obtaining structure data at each collection point based on a structure monitoring sensor of a plurality of collection points; obtaining a structure sharing index; obtaining bridge body structure health indexes; obtaining a bridge structure evaluation index based on the structure sharing index and the bridge body structure health index; acquiring weather forecast information at the bridge, and acquiring a bridge safety assessment index s * based on the bridge structure assessment index, the weather sharing index and the dynamically adjusted weight; and comparing the obtained bridge safety evaluation index s * with a safety threshold, and when the bridge safety evaluation index s * is greater than the safety threshold, triggering early warning. By adopting the early warning method provided by the invention, the deployment of a meteorological sensor of the bridge body can be omitted while the bridge safety early warning is realized.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge monitoring, and in particular to a bridge safety early warning method, equipment and storage medium based on a bridge-tunnel structure. Background Art

[0002] In the construction of roads, railways and other transportation, many bridges and tunnels need to be built. In order to cross special terrains such as deep valleys and mountains, bridges across deep valleys and mountains are often built, as well as tunnels connected to bridges in the mountains on both sides. This type of structure is called bridge-tunnel structure in this article. Figure 1 .

[0003] In order to ensure safety in use, sensors and related testing devices are generally deployed during the use of bridge and tunnel structures to test the quality of bridges and tunnels. Testing items generally include bridge pile foundation integrity testing, structural concrete quality testing, structural concrete durability testing, etc.

[0004] In the process of implementing the present invention, the inventors found that there are at least the following problems in the prior art:

[0005] At present, the monitoring and early warning systems for bridge and tunnel structures are mainly limited to the monitoring of the bridge and tunnel structures themselves, and there has been no research on the use of sensor data from surrounding structures for collaborative analysis and risk assessment. In addition, in addition to the structural health of the bridge itself, environmental factors also have an impact on the safety of general bridges. Therefore, in order to collect meteorological and environmental data, bridges are usually installed with multiple dedicated sensors, which further increases the power consumption and complexity of the system. Independent monitoring of each structure also means that they cannot share data, especially in the same geographical area, where multiple sensors often repeatedly monitor the same environmental and meteorological data, resulting in higher system deployment and maintenance costs.

[0006] Therefore, a bridge safety early warning method, device and storage medium based on bridge-tunnel structures are needed. Summary of the invention

[0007] In view of this, an embodiment of the present invention provides a bridge safety early warning method, device and storage medium based on a bridge-tunnel structure to at least solve one of the problems in the prior art.

[0008] In a first aspect, an embodiment of the present invention provides a bridge safety early warning method based on a bridge tunnel structure, the early warning method comprising:

[0009] Based on a plurality of meteorological sensors at different sampling points arranged in a tunnel and / or a slope on at least one side of a target bridge and within a set distance range corresponding to the type of the target bridge classified by span size from the target bridge, a meteorological data set at each sampling point is obtained, including wind speed, rainfall and temperature data;

[0010] Obtain meteorological sharing indicators based on the meteorological data sets of multiple sampling points, the distance between the sampling points and the target bridge, and the sensor health;

[0011] Based on structural monitoring sensors configured at multiple collection points of a tunnel entrance and exit and / or a slope on at least one side of a target bridge, structural data at each collection point is acquired, wherein the structural data is one of stress, displacement and vibration data;

[0012] Normalizing the acquired structural data at all acquisition points, and obtaining structural sharing indicators based on the normalized structural data, the distance between the acquisition point and the target bridge, and the sensor health;

[0013] Based on the structural data of the target bridge itself obtained by its own structural monitoring sensors, including stress, displacement and vibration data of multiple key parts, the structural health index of the bridge itself is obtained;

[0014] Obtaining a bridge structure evaluation index based on the structural sharing index and the bridge body structural health index;

[0015] Obtain weather forecast information at the bridge, and obtain the bridge safety assessment index s based on the bridge structure assessment index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1; wherein the bridge safety assessment index s * The size of represents the different safety levels of the bridge. * The larger it is, the more dangerous the bridge condition is;

[0016] The bridge safety evaluation index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

[0017] In a second aspect, an embodiment of the present invention further provides a bridge safety early warning device based on a bridge tunnel structure, the early warning device comprising:

[0018] A memory for storing computer executable instructions;

[0019] The processor is used to implement the early warning method of the above technical solution when executing the computer executable instructions stored in the memory.

[0020] In a third aspect, an embodiment of the present invention further provides a storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to execute the early warning method of the above technical solution.

[0021] Additional advantages, purposes, and features of the present invention will be described in part in the following description, and will become apparent to those skilled in the art after studying the following, or may be learned from the practice of the present invention. The purposes and other advantages of the present invention may be achieved and obtained by the structures specifically indicated in the specification and the accompanying drawings.

[0022] Those skilled in the art will appreciate that the objectives and advantages that can be achieved with the present invention are not limited to the above specific description, and the above and other objectives that can be achieved by the present invention will be more clearly understood from the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The drawings described herein are used to provide a further understanding of the present invention, constitute a part of this application, and do not constitute a limitation of the present invention. The components in the drawings are not drawn to scale, but are only for illustrating the principles of the present invention. In order to facilitate the illustration and description of some parts of the present invention, the corresponding parts in the drawings may be enlarged, that is, they may become larger relative to other components in the exemplary device actually manufactured according to the present invention. In the drawings:

[0024] Figure 1 A schematic diagram of an existing bridge-tunnel structure;

[0025] Figure 2 is a flow chart of an early warning method according to an embodiment of the present invention;

[0026] Figure 3 is a schematic diagram of an early warning device according to an embodiment of the present invention;

[0027] Figure 4 FIG. 4 is a schematic diagram of an early warning system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments and the accompanying drawings. Here, the illustrative embodiments of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0029] It should also be noted that, in order to avoid obscuring the present invention due to unnecessary details, only structures and / or processing steps closely related to the solutions according to the present invention are shown in the accompanying drawings, while other details that are not closely related to the present invention are omitted.

[0030] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, elements, steps or components, but does not exclude the presence or addition of one or more other features, elements, steps or components.

[0031] It should also be noted that, unless otherwise specified, the term “connection” herein may refer not only to a direct connection but also to an indirect connection involving an intermediate.

[0032] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0033] First, refer to Figure 2 The bridge safety early warning method 100 based on the bridge-tunnel structure according to the embodiment of the present application is described. Figure 2 As shown, the early warning method 100 may include steps S110 to S180, which are specifically as follows:

[0034] In step S110, based on meteorological sensors at multiple sampling points located at different positions within a set distance range corresponding to the type of the target bridge classified by span size and configured in a tunnel and / or slope on at least one side of the target bridge, a meteorological data set at each sampling point is obtained, including wind speed, rainfall and temperature data.

[0035] In step S120, a meteorological sharing index is obtained based on the meteorological data sets of the plurality of sampling points, the distance between the sampling points and the target bridge, and the sensor health.

[0036] In step S130, based on the structural monitoring sensors configured at multiple collection points of the tunnel entrance and exit and / or the slope on at least one side of the target bridge, the structural data at each collection point is obtained, and the structural data is one of stress, displacement and vibration data.

[0037] In step S140, the structural data acquired at all the acquisition points are normalized, and a structural sharing index is acquired based on the normalized structural data, the distance between the acquisition point and the target bridge, and the sensor health.

[0038] In step S150, based on the target bridge's own structural data acquired by its own structural monitoring sensors, including stress, displacement and vibration data of multiple key parts, the structural health index of the bridge body is obtained.

[0039] In step S160, a bridge structure evaluation index is obtained based on the structure sharing index and the bridge body structure health index.

[0040] In step S170, weather forecast information at the bridge is obtained, and the bridge safety assessment index s is obtained based on the bridge structure assessment index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1; wherein the bridge safety assessment index s * The size of represents the different safety levels of the bridge. * The larger it is, the more dangerous the bridge is.

[0041] In step S180, the obtained bridge safety assessment index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

[0042] In an embodiment of the present application, first, multiple meteorological data sets of different locations of tunnels and / or slopes within a set distance range from a target bridge are obtained, and meteorological sharing indicators are obtained based on the multiple meteorological data sets; multiple structural data of tunnel entrances and / or slopes are obtained, and the structural sharing indicators are further obtained after the data are normalized; then the structural health index of the bridge body is obtained, and the bridge structure evaluation index is obtained based on the structural sharing index and the structural health index of the bridge body, and then the dynamically adjusted meteorological sharing index weight and safety threshold are determined according to the weather forecast information at the bridge, and the bridge safety evaluation index s is obtained based on the bridge structure evaluation index, the meteorological sharing index and the dynamically adjusted weight. * Finally, the bridge safety evaluation index s * Compare the size with the safety threshold and determine whether to trigger an early warning based on the situation.

[0043] For example, the collected meteorological data sets and structural data information of slopes and tunnels can be uploaded to the cloud through 4G / 5G networks or the Internet of Things. These data are not only used for structural health analysis of slopes and tunnels, but can also be used for bridge structures. The bridge structure establishes a connection with the cloud server through a preset network protocol, sends request information at regular intervals, and obtains meteorological shared indicators and structural shared indicators. After receiving the request, the cloud processes and returns meteorological shared indicators and structural shared indicators. Based on its own edge computing device, the bridge structure integrates the received information with its own monitoring data. Before data integration, the edge computing device can first perform local preprocessing on its own monitoring data, filter noise, and then perform risk assessment and status judgment, reducing the configuration of its own meteorological sensors, thereby achieving lightweight.

[0044] It can be seen from the description of the above process that according to the early warning method 100 of the embodiment of the present application, by sharing the data of the slope and tunnel sensors around the bridge (including meteorological and structural data information), it is avoided to repeatedly install meteorological sensors on the bridge body, thereby reducing system cost and power consumption, and integrating the relevant shared indicators of the tunnels and slopes around the bridge, considering the weather information at the bridge, and obtaining the bridge safety assessment index s * The result is compared with the size of the safety threshold that is dynamically adjusted according to the weather forecast information at the bridge to achieve bridge safety warning.

[0045] Among them, Figure 2 In the figure, step S110, step S130 and step S150 are shown to be arranged to be performed in sequence, which is only an example. It can be understood that the sequence of step S110, step S130 and step S150 may not be limited. For example, the three steps may be performed in parallel and simultaneously.

[0046] The contents of the above steps of the early warning method 100 according to the embodiment of the present application will be described in detail below.

[0047] For common bridges, in order to achieve real-time monitoring of the safety status of the bridge structure itself, sensors are generally arranged at key locations. For example, structural monitoring sensors are installed on the pier foundation or main beam of the bridge to monitor a variety of structural parameters.

[0048] For example, for bridge pier foundations, displacement sensors are installed to obtain pier displacement data to monitor the displacement changes of the pier foundation caused by water flow and evaluate the stability of the foundation; strain sensors and acceleration sensors are arranged in the support area of ​​the main beam, the mid-span position, the beam end nodes, and the connection between the cross beam and the main beam to obtain beam stress data and beam vibration data for real-time monitoring of the stress state and vibration response of the beam. The above are only some examples, and the content of arranging sensors in other key locations is not elaborated here one by one.

[0049] Then, based on the stress, displacement and vibration data obtained by sensors at key parts of the bridge, all the acquired stress, displacement and vibration data are normalized. For all the stress data after normalization, according to the weights corresponding to the corresponding key parts, the bridge body stress index S is obtained through weighted calculation. local Using the same method, the bridge body vibration index V local , Bridge body displacement index D local Finally, the bridge structure health index M is obtained by the following formula: local ,

[0050]

[0051] The above content is the specific content of step S150 of the embodiment of the present application. Therefore, step S150 will not be repeated in the following.

[0052] In an embodiment of the present application, in step S110, based on meteorological sensors at multiple sampling points located at different positions within a set distance range corresponding to the type of the target bridge classified by span size and configured in a tunnel and / or slope on at least one side of the target bridge, a meteorological data set at each sampling point is obtained, including wind speed, rainfall and temperature data.

[0053] It should be noted that, in terms of sensors using structures around bridges (slopes, tunnels), different data sources are used in different situations. Among them, bridges can be classified into small bridges, medium bridges, large bridges and extra-large bridges according to span size. In this embodiment, when meteorological sensors at sampling points around bridges are used to obtain meteorological data, there are specific and strict restrictions on their locations.

[0054] Specifically, for small bridges (with a total span of multiple holes within 8 to 30 meters and a single span within 5 to 20 meters), the meteorological monitoring data collected by meteorological sensors at sampling points of surrounding structures such as slopes and tunnels within 10 meters of the target bridge are used; for medium bridges (with a total span of multiple holes within 30 to 100 meters and a single span within 20 to 40 meters), the meteorological monitoring data collected by meteorological sensors at sampling points of surrounding structures such as slopes and tunnels within 20 meters of the bridge are used; for large bridges (with a total span of multiple holes within 100 to 1000 meters and a single span within 40 to 1500 meters) and extra-large bridges (with a total span of multiple holes greater than 1000 meters and a single span greater than 150 meters), the meteorological monitoring data collected by meteorological sensors at sampling points of surrounding structures such as slopes and tunnels within 50 meters of the bridge are used.

[0055] Specifically, for ease of understanding and description, assuming that the target bridge is a multi-hole bridge with a total span length of 200m, 6 and 7 sampling points are arranged on the two slopes of the target bridge respectively, and a total of 12 sampling points are set within 50 meters of the target bridge in the tunnel on one side of the target bridge. The meteorological sensor at each sampling point obtains three meteorological data: wind speed, rainfall, and temperature, forming a meteorological data set.

[0056] For example, within a sampling period, such as 10 minutes or 30 minutes, the meteorological sensor at each sampling point collects three meteorological data, namely wind speed, rainfall and temperature, to form a meteorological data set. Or the meteorological sensor at the sampling point obtains 10 values ​​of the corresponding meteorological data at a sampling interval Δt within a sampling period, and the average of these 10 values ​​is used as the final value of the corresponding meteorological data for subsequent calculations.

[0057] In an embodiment of the present application, in step S120, a meteorological sharing index is obtained based on the meteorological data sets of multiple sampling points, the distance between the sampling points and the target bridge, and the sensor health.

[0058] Specifically, the following may be included:

[0059] Based on the distance between the sampling point and the target bridge, determine the first influencing factor ω of the meteorological data set of the i-th sampling point i ,

[0060]

[0061] Among them, d i is the distance between each sampling point and the target bridge. i The sensor health degree has a value range of 0 to 1, indicating the health status of the relevant sensor. The better the health status, the larger the value. The sensor health degree is an existing technical parameter. For details, please refer to: "Sensor health degree evaluation method based on fuzzy set theory", Cao Zhenghong, Shen Jihong, "Journal of Electric Machines and Control", Issue 5, Volume 14, May 2010. It gives a quantitative comprehensive evaluation index of the sensor health state: sensor health degree, which is not described here.

[0062] Based on the determined first impact factor ω i The meteorological sharing index M is determined by using the meteorological data sets of multiple sampling points weather

[0063]

[0064] Where M is the number of sampling points, W i , R i and T i are the wind speed, rainfall and temperature data in the meteorological dataset at the i-th sampling point.

[0065] In an embodiment of the present application, in step S130, based on the structural monitoring sensors configured at multiple collection points of the tunnel entrance and exit and / or the slope on at least one side of the target bridge, the structural data at each collection point is obtained. The structural data at each collection point is one of stress, displacement and vibration data.

[0066] For tunnel structures, stress sensors can be installed at the arch top and arch foot at the entrance and exit, displacement sensors can be installed at the midpoint and bottom of the side wall, and vibration sensors can be installed at key parts of the tunnel lining and support structure. For slope structures, displacement sensors can be installed at the top and bottom of the slope, vibration sensors can be installed at different heights and positions of the slope, and stress sensors can be installed at potential sliding surfaces, crack areas, or geological structure changes of the slope.

[0067] For example, 12 collection points are arranged on the slope of one side of the target bridge, and 18 collection points are arranged at the tunnel entrances and exits on both sides of the target bridge. Among the above 30 collection points, the structural monitoring sensor at each collection point obtains one of stress, displacement and vibration data, for example, 10 stress data, 10 displacement data and 10 vibration data are obtained respectively.

[0068] In an embodiment of the present application, in step S140, the structural data acquired at all acquisition points are normalized, and a structural sharing index is acquired based on the normalized structural data, the distance between the acquisition point and the target bridge, and the sensor health.

[0069] First, since the data units and dimensions of stress, vibration and displacement are different, these data should be standardized before fusion, such as normalization, to make them comparable.

[0070]

[0071] Among them, S j represents the jth stress data among all the stress data obtained, V k represents the kth vibration data obtained, D l Indicates the lth displacement data obtained, S j ', V k ', D l ' are normalized data. max(S), max(V) and max(D) represent the historical maximum values ​​of the corresponding data, and min(S), min(V) and min(D) represent the historical minimum values ​​of the corresponding data.

[0072] Then, based on the distance between the acquisition point and the target bridge, the second influencing factor β of the structural data at different acquisition points is determined. s(v,d),j(k,l) ,

[0073]

[0074] Among them, d j(k,l) Indicates the distance between the acquisition point where the structural data of the corresponding sequence number is located and the target bridge. j(k,l) Indicates the health of the sensor that obtains the structure data of the corresponding sequence number.

[0075] Here β s(v,d),j(k,l) This is the β in the following s,j , β v,k , β d,l The total expression of .

[0076] Based on the determined second impact factor β s(v,d),j(k,l)The structure sharing index M is determined by the obtained normalized structure data struct ,

[0077]

[0078] Where N represents the number of stress data obtained, β s,j represents the second influencing factor corresponding to the jth stress data obtained, P represents the number of vibration data obtained, β v,k represents the second impact factor corresponding to the kth vibration data obtained, Q represents the number of displacement data obtained, β d,l Indicates the second impact factor corresponding to the obtained lth displacement data.

[0079] Taking the example of obtaining 10 stress data, 10 displacement data and 10 vibration data from 30 acquisition points on the slopes on both sides of the target bridge and the tunnel entrances and exits in the previous article, N, P and Q are taken as 10 respectively.

[0080] In step S160, a bridge structure evaluation index is obtained based on the structure sharing index and the bridge body structure health index.

[0081] Specifically, based on the structural sharing index M struct and the bridge structure health index M local Obtain bridge structure evaluation index R struct

[0082] R struct =γ·M struct +δ·M local

[0083] Among them, γ and δ are the weights of the structural sharing index and the bridge structure health index respectively. γ+δ=1. For example, γ takes the value of 0.3 and δ takes the value of 0.7.

[0084] In step S170, weather forecast information at the bridge is obtained, and the bridge safety assessment index s is obtained based on the bridge structure assessment index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1. Among them, the bridge safety assessment index s * The size of represents the different safety levels of the bridge. * The larger it is, the more dangerous the bridge is.

[0085] Specifically, the bridge safety assessment index s is obtained * ,

[0086] s * =λ·R struct +μ·Mweather

[0087] Among them, λ and μ are the weights of bridge structure evaluation index and meteorological sharing index respectively. λ+μ=1.

[0088] It should be noted that λ and μ need to be dynamically adjusted according to the weather information at the bridge, rather than fixed. Taking the weight of meteorological sharing indicators as an example, under extreme weather conditions, the weight of meteorological sharing indicators should be increased, and the weight of bridge structure evaluation indicators should be relatively reduced.

[0089] The weight of the meteorological sharing index is dynamically adjusted according to the weather forecast information at the bridge.

[0090] μ'=μ"×f

[0091] Among them, μ' is the weight of the meteorological sharing index under extreme weather, and μ" is the weight of the meteorological sharing index under non-extreme weather. Among them, extreme weather refers to wind speed>20m / s, or rainfall>50mm / h. f is the adjustment coefficient, f>1. f is a certain value, for example, 1.5.

[0092] For example, according to the weather forecast information at the bridge, the weather information at the bridge is determined to be non-extreme weather, for example, at this time, λ takes a value of 0.6 and μ takes a value of 0.4. When the weather information at the bridge is determined to be extreme weather, the value is changed to λ taking a value of 0.4 and μ taking a value of 0.6.

[0093] In step S180, the obtained bridge safety assessment index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

[0094] It should be noted that the safety threshold also needs to be dynamically adjusted according to the weather information at the bridge, rather than fixed. During extreme weather, the safety threshold triggered by the warning will be automatically lowered to cope with sudden risks.

[0095] The safety threshold is dynamically adjusted according to the weather forecast information at the bridge, specifically:

[0096] t'=t"-e

[0097] Among them, t' is the safety threshold under extreme weather, t" is the safety threshold under non-extreme weather, 0.1≤e≤0.2, and e is a certain value. For example, according to the weather forecast information at the bridge, the weather information at the bridge is determined to be non-extreme weather, and the safety threshold is 0.85 at this time. When it is determined that the weather information at the bridge is extreme weather, the safety threshold is reduced to 0.75.

[0098] When the bridge safety evaluation index s *When the value is greater than the safety threshold, an early warning is triggered. This usually means that the safety of the bridge has reached an extremely high risk and may be damaged or fail at any time, and emergency measures must be taken immediately. Early warning information can be sent to relevant management departments and on-site monitoring personnel through various channels (such as SMS, email, mobile applications, etc.). Through the integrated GPS and navigation system, voice or text warnings can be issued in real time to drivers and pedestrians on the bridge to remind them to avoid the bridge.

[0099] In addition, the bridge safety assessment index s can also be * Further set up multiple levels to deal with different risk levels and achieve graded processing. For example, taking the safety threshold of 0.85 as an example, when s * If the safety threshold exceeds 0.85, the system will immediately trigger a level 1 warning. This usually means that the structure has reached an extremely high risk and may be damaged or fail at any time. Emergency measures must be taken immediately to remind vehicles and personnel to avoid the bridge. * In the medium risk range (0.65≤s * <0.85), the system triggers a secondary warning and advises management to conduct further inspections of the structure and take appropriate preventive measures. * In the low risk range (such as 0.35≤s * <0.65), the system will issue a third-level warning to remind monitoring personnel to pay attention to possible structural abnormalities and continue to observe the trend of changes. * In the risk-free range (0≤s * <0.35), indicating that the bridge is safe.

[0100] Based on the above description, according to the early warning method of the embodiment of the present application, the repeated arrangement of meteorological sensors and the repeated collection of meteorological data are avoided by sharing data, the cost and power consumption are reduced, and the relevant shared indicators of the tunnels and slopes around the bridge are integrated, and the weather information at the bridge is considered to obtain the bridge safety assessment index s * By comparing the results with the safety threshold values ​​dynamically adjusted according to the weather forecast information at the bridge, it is possible to issue warnings according to different risk levels and conduct bridge safety warnings. This method enhances the monitoring and warning capabilities of bridges through multi-source data sharing and intelligent analysis.

[0101] refer to Figure 3The embodiment of the present application also provides an early warning device 200 for implementing the early warning method 100 according to the embodiment of the present application. The early warning device 200 includes a processor 210 and a memory 220. The early warning device 200 may include one or more processors 210 and one or more memories 220. The memory 220 stores an executable program run by the processor 210, and when the executable program is run by the processor 210, the processor 210 executes the early warning method 100 according to the embodiment of the present application described above.

[0102] The processor 210 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities.

[0103] The memory 220 may include one or more computer program products, and the computer program product may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 210 may run the program instructions to implement the client functions (implemented by the processor) in the embodiments of the present application described herein and / or other desired functions. Various applications and various data may also be stored in the computer-readable storage medium, such as various data used and / or generated by the application, etc.

[0104] The early warning device 200 may also include an input device and an output device, and these components are interconnected through a bus system and / or other forms of connection mechanisms. It should be noted that Figure 3 The components and structures of the early warning device 200 shown are merely exemplary and non-limiting. The early warning device 200 may also have other components and structures as required.

[0105] The input device may be a device used by a user to input instructions, and may include one or more of a keyboard, a mouse, a microphone, a touch screen, etc. In addition, the input device may also be any interface for receiving information.

[0106] The output device may output various information (eg, images or sounds) to the outside (eg, a user), and may include one or more of a display, a speaker, etc. In addition, the output device may also be any other device with an output function.

[0107] Exemplarily, the example early warning device 200 for implementing the early warning method 100 according to the embodiment of the present application can be applied to terminal devices (such as mobile phones), tablet computers, laptops, ultra-mobile personal computers (ultra-mobile personal computers, UMPCs), handheld computers, netbooks, personal digital assistants (personal digital assistants, PDAs), wearable devices (such as smart watches, smart glasses or smart helmets, etc.), augmented reality (augmented reality, AR), virtual reality (virtual reality, VR) devices, smart home devices, car computers and other electronic devices, and the embodiments of the present application do not impose any restrictions on this.

[0108] Those skilled in the art can understand the specific operation of the early warning device 200 for implementing the early warning method 100 according to the embodiment of the present application in combination with the contents described above. For the sake of brevity, the specific details are not repeated here, and only some main operations of the processor 210 are described.

[0109] In one embodiment of the present application, when the executable program is executed by the processor 210, the processor 210 executes the following steps:

[0110] Based on the meteorological sensors at multiple sampling points located at different positions within a set distance range corresponding to the type of the target bridge classified by span size and configured in the tunnel and / or slope on at least one side of the target bridge, a meteorological data set at each sampling point is obtained, including wind speed, rainfall and temperature data; based on the meteorological data sets of the multiple sampling points obtained, the distance between the sampling points and the target bridge, and the health of the sensors, a meteorological sharing index is obtained; based on the structural monitoring sensors at multiple collection points of the tunnel entrance and exit and / or slope on at least one side of the target bridge, structural data at each collection point is obtained, and the structural data is one of stress, displacement and vibration data The structure data at all acquisition points are normalized, and the structure sharing index is obtained based on the normalized structure data, the distance between the acquisition point and the target bridge, and the sensor health; the bridge body structure health index is obtained based on the structure data of the target bridge itself acquired by the structure monitoring sensor of the target bridge itself, including stress, displacement and vibration data of multiple key parts; the bridge structure evaluation index is obtained based on the structure sharing index and the bridge body structure health index; the weather forecast information at the bridge is obtained, and the bridge safety evaluation index s is obtained based on the bridge structure evaluation index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1; wherein the bridge safety assessment index s *The size of represents the different safety levels of the bridge. * The larger the value, the more dangerous the bridge condition. The bridge safety assessment index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

[0111] The above exemplary shows the early warning method 100 according to the embodiment of the present application. Figure 4 The following describes an early warning system 300 provided in accordance with another aspect of an embodiment of the present application.

[0112] Reference Figure 4 The example early warning system 300 for implementing the early warning method of the embodiment of the present application is described. The early warning system 300 may include a meteorological data set acquisition module 310, a meteorological shared index acquisition module 320, a structural data acquisition module 330, a structural shared index acquisition module 340, a structural health index acquisition module 350, a structural assessment index acquisition module 360, a safety assessment index acquisition module 370 and an early warning module 380. Among them:

[0113] The meteorological data set acquisition module 310 is used to: based on meteorological sensors at multiple sampling points located at different positions within a set distance range corresponding to the type of the target bridge classified by span size and configured in a tunnel and / or slope on at least one side of the target bridge, acquire the meteorological data set at each sampling point, including wind speed, rainfall and temperature data.

[0114] The meteorological sharing index acquisition module 320 is used to acquire the meteorological sharing index based on the meteorological data sets of the multiple sampling points, the distance between the sampling points and the target bridge, and the sensor health.

[0115] The structural data acquisition module 330 is used to: acquire structural data at each collection point based on structural monitoring sensors configured at multiple collection points of the tunnel entrance and exit and / or the slope on at least one side of the target bridge, wherein the structural data is one of stress, displacement and vibration data.

[0116] The structure sharing index acquisition module 340 is used to normalize the structure data acquired at all acquisition points, and acquire the structure sharing index based on the normalized structure data, the distance between the acquisition point and the target bridge, and the sensor health.

[0117] The structural health index acquisition module 350 is used to obtain the structural health index of the bridge body based on the self-structural data acquired by the structural monitoring sensors of the target bridge itself, including stress, displacement and vibration data of multiple key parts.

[0118] The structural evaluation index acquisition module 360 ​​is used to obtain a bridge structure evaluation index based on the structural sharing index and the bridge body structural health index.

[0119] The safety assessment index acquisition module 370 is used to: obtain weather forecast information at the bridge, and obtain the bridge safety assessment index s based on the bridge structure assessment index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1; wherein the bridge safety assessment index s * The size of represents the different safety levels of the bridge. * The larger it is, the more dangerous the bridge is.

[0120] The early warning module 380 is used to: obtain the bridge safety assessment index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

[0121] The early warning system 300 proposed in the embodiment of the present invention reduces the deployment of sensors on the bridge itself by sharing the meteorological and structural data of the surrounding environment of the target bridge, thereby realizing a lightweight design of the early warning system. The system uses sensor data of surrounding structures (slopes, tunnels) combined with real-time monitoring of the bridge itself to conduct comprehensive risk assessment and early warning. Through the innovative idea of ​​sharing data, the system effectively reduces the installation requirements of sensors on the bridge, reduces power consumption, and improves monitoring efficiency.

[0122] In addition, according to an embodiment of the present application, the present application further provides a storage medium, on which a computer program is stored, and when the computer program is run by a processor, it is used to execute the corresponding steps of the early warning method 100 of the embodiment of the present application. The storage medium may include, for example, a memory card of a smart phone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0123] In addition, according to an embodiment of the present application, the present application also provides a computer program product, including computer instructions, which, when executed by a processor, implement the steps of the monitoring method of the embodiment of the present application or implement the steps of the early warning method of the embodiment of the present application.

[0124] Although example embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above example embodiments are merely exemplary and are not intended to limit the scope of the present application to this. Those of ordinary skill in the art may make various changes and modifications therein without departing from the scope and spirit of the present application. All these changes and modifications are intended to be included within the scope of the present application as required by the appended claims.

[0125] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0126] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed.

[0127] In addition, those skilled in the art will appreciate that, although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments is meant to be within the scope of the present application and form different embodiments. For example, in the claims, any one of the claimed embodiments can be used in any combination.

[0128] It should be noted that the above embodiments illustrate the present application rather than limit the present application, and that those skilled in the art may design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference symbol between brackets should not be constructed as a limitation to the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "one" or "an" preceding an element does not exclude the presence of multiple such elements. The present application may be implemented by means of hardware including several different elements and by means of a suitably programmed computer. In a unit claim that lists several devices, several of these devices may be embodied by the same hardware item. The use of the words first, second, and third, etc. does not indicate any order. These words may be interpreted as names.

[0129] The above is only a specific implementation or description of a specific implementation of the present application, and the protection scope of the present application is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. The protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A bridge safety early warning method based on bridge-tunnel structures, characterized in that: The early warning method comprises: Based on a plurality of meteorological sensors at different sampling points arranged in a tunnel and / or a slope on at least one side of a target bridge and within a set distance range corresponding to the type of the target bridge classified by span size from the target bridge, a meteorological data set at each sampling point is obtained, including wind speed, rainfall and temperature data; Obtain meteorological sharing indicators based on the meteorological data sets of multiple sampling points, the distance between the sampling points and the target bridge, and the sensor health; Based on structural monitoring sensors configured at multiple collection points of a tunnel entrance and exit and / or a slope on at least one side of a target bridge, structural data at each collection point is acquired, wherein the structural data is one of stress, displacement and vibration data; Normalizing the acquired structural data at all acquisition points, and obtaining structural sharing indicators based on the normalized structural data, the distance between the acquisition point and the target bridge, and the sensor health; Based on the structural data of the target bridge itself obtained by its own structural monitoring sensors, including stress, displacement and vibration data of multiple key parts, the structural health index of the bridge itself is obtained; Obtaining a bridge structure evaluation index based on the structural sharing index and the bridge body structural health index; Obtain weather forecast information at the bridge, and obtain the bridge safety assessment index s based on the bridge structure assessment index, the meteorological sharing index and the weight dynamically adjusted according to the weather forecast information at the bridge. * , 0≤s * ≤1; wherein the bridge safety assessment index s * The size of represents the different safety levels of the bridge. * The larger it is, the more dangerous the bridge condition is; The bridge safety evaluation index s * Compared with the safety threshold dynamically adjusted according to the weather forecast information at the bridge, when the bridge safety assessment index s * If the value is greater than the safety threshold, an early warning is triggered.

2. The early warning method according to claim 1, characterized in that: The obtaining of meteorological sharing indicators specifically includes: Based on the distance between the sampling point and the target bridge, determine the first influencing factor ω of the meteorological data set of the i-th sampling point i , Among them, d i is the distance between the sampling point and the target bridge, h i is the sensor health; Based on the determined first impact factor ω i The meteorological sharing index M is determined by using the meteorological data sets of multiple sampling points weather Where M is the number of sampling points, W i , R i and T i are the wind speed, rainfall and temperature data in the meteorological dataset at the i-th sampling point.

3. The early warning method according to claim 1, characterized in that: The structural data at all acquisition points are normalized, specifically: Among them, S j represents the jth stress data among all the stress data obtained, V k represents the kth vibration data obtained, D l represents the lth displacement data obtained, max(S), max(V) and max(D) represent the historical maximum values ​​of the corresponding class data.

4. The early warning method according to claim 3, characterized in that: The obtaining of the structural sharing index specifically includes: Based on the distance between the acquisition point and the target bridge, the second influencing factor β of the structural data at different acquisition points is determined s(v,d),j(k,l) , Among them, d j(k,l) Indicates the distance between the acquisition point where the structure data of the corresponding sequence number is located and the target bridge, h j(k,l) Indicates the health of the sensor that obtains the structural data of the corresponding sequence number; Based on the determined second impact factor β s(v,d),j(k,l) The structure sharing index M is determined by the obtained normalized structure data struct , Where N represents the number of stress data obtained, β s,j represents the second influencing factor corresponding to the jth stress data obtained, P represents the number of vibration data obtained, β v,k represents the second impact factor corresponding to the kth vibration data obtained, Q represents the number of displacement data obtained, β d,l Indicates the second impact factor corresponding to the obtained lth displacement data.

5. The early warning method according to claim 1, characterized in that: The set distance corresponding to the type of target bridge classified by span size specifically refers to: When the target bridge is classified as a small bridge according to span size, the corresponding set distance is 10 meters; When the target bridge is classified as a medium bridge according to span size, the corresponding set distance is 20 meters; When the target bridge is classified as a large bridge or an extra-large bridge according to the span size, the corresponding set distance is 50 meters.

6. The early warning method according to claim 4, characterized in that: The structure sharing index and the bridge body structure health index M local Obtain bridge structure evaluation index R struct , specifically: R struct =γ·M struct +δ·M local Among them, γ and δ are the weights of the structural sharing index and the bridge structure health index respectively.

7. The early warning method according to claim 6, characterized in that: The bridge safety assessment index s is obtained * , specifically: s * =λ·R struct +μ·M weather Among them, λ and μ are the weights of bridge structure evaluation index and meteorological sharing index respectively.

8. The early warning method according to claim 1, characterized in that: The weights dynamically adjusted according to the weather forecast information at the bridge specifically refer to: μ'=μ"×f Among them, μ' is the weight of the meteorological sharing index under extreme weather conditions, μ" is the weight of the meteorological sharing index under non-extreme weather conditions, f>1, and f is a certain value; The safety threshold dynamically adjusted according to the weather forecast information at the bridge specifically refers to: t'=t"-e Among them, t' is the safety threshold under extreme weather conditions, t" is the safety threshold under non-extreme weather conditions, 0.1≤e≤0.2, and e is a certain value.

9. A bridge safety warning device based on a bridge-tunnel structure, characterized in that: The early warning equipment includes: A memory for storing computer executable instructions; A processor, used to implement the early warning method according to any one of claims 1 to 8 when executing the computer executable instructions stored in the memory.

10. A storage medium storing computer instructions, wherein: The computer instructions are used to enable the computer to execute the early warning method according to any one of claims 1 to 8.

Images