A bridge crack detection method and system

Abstract

The present invention provides a bridge crack detection method and system, and relates to the technical field of bridge crack detection. The present invention divides the bridge into grid areas, thereby finding the stress concentration area of ​​the bridge according to the motion trajectory and vehicle weight data of each vehicle, and arranges a combined sensing module at the bottom of the bridge in the stress concentration area to detect the cracks. This method can not only locate the position where the bridge is most likely to crack, but also reduce the points that need to be detected, which not only reduces the detection cost, but also reduces the data that needs to be detected, making the system respond faster. At the same time, by detecting the environmental information of each detection point and using the environmental information to correct the detection result, the influence of the ambient temperature and wind force on the detection result is reduced, making the detection result more accurate.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge crack detection, and in particular to a bridge crack detection method and system. Background Art

[0002] Existing nondestructive detection methods for bridge cracks mainly include ultrasonic detection, elastic wave detection, acoustic emission detection, image detection and sensor detection. In sensor detection, the use of optical fiber sensors for detection is a common method. However, in traditional detection methods, since the locations of cracks are relatively random and usually related to the stress on various parts of the bridge, it is difficult to determine the detection points. Detection can only be carried out in a large-area coverage manner, resulting in increased detection costs and reduced response speed.

[0003] For example, a bridge crack monitoring and early warning system and early warning method disclosed in Chinese patent publication number CN106290377A can monitor the growth of cracks, but it is still difficult to determine the possible location of the cracks. In addition, when the optical fiber sensor is affected by temperature and wind, it will deform and generate light signals, which can easily cause false alarms and reduce the overall detection accuracy.

[0004] The above information disclosed in this Background section is only for enhancement of understanding of the background of the present disclosure and therefore it may contain information that does not constitute the prior art that is already known to one of ordinary skill in the art. Summary of the invention

[0005] The object of the present invention is to provide a bridge crack detection method and system to solve the problems raised in the above background technology.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A bridge crack detection method, the specific steps comprising:

[0008] S1: 3D modeling of the bridge is performed, and the road surface of the bridge is evenly divided into several groups of grid areas. Vehicle information and movement information entering the bridge within a period of time are collected, and several stress concentration areas are generated based on the vehicle information and movement information;

[0009] S2: Combined sensing modules are respectively set at the bottom of the stress concentration area and both sides of the bridge to collect the total strain of the bridge in the corresponding area and the environmental information of the environment where the combined sensing modules are located;

[0010] S3: The corresponding total strain is corrected according to the environmental information of each area to obtain the stress strain of each area, and the stress concentration area is compared with the stress strain on both sides of the bridge, and different alarm signals are generated according to the comparison results.

[0011] Preferably, the bridge is divided horizontally and vertically according to the user setting and the lanes of the bridge, and the bridge is divided into grid areas, where Set the number of users for the horizontal direction, is the number of longitudinal lanes.

[0012] Preferably, the vehicle information includes vehicle weight data, traffic flow data, and license plate data; the motion information includes the vehicle's motion trajectory and motion time; the combined sensing module includes a fiber optic sensing unit, a temperature sensing unit, and an anemometer; and the environmental information includes ambient temperature, ambient wind speed, and wind direction.

[0013] Preferably, the generation logic of the stress concentration area is:

[0014] Based on the 3D modeling, mesh area division and motion information of the bridge, the travel time of each vehicle passing through different areas is obtained. , where the subscript Indicates grid coordinates, superscript Indicates the vehicle number, ,in Represents the traffic flow data within the sampling time;

[0015] Calculate the total weight and total driving time of vehicles passing through different areas during the sampling time, and calculate the concentration coefficient corresponding to different areas based on the total weight and total driving time , calculated as:

[0016]

[0017] In the formula Represents the vehicle weight data of each vehicle passing through different areas, Indicates a preset time threshold;

[0018] The concentration coefficients of different regions Centralized Matrix , calculate the concentration matrix The average value of each element in and standard deviation , the calculation methods are:

[0019]

[0020]

[0021] When the concentration factor of a certain area satisfy When , the area is considered to be a stress concentration area, where Indicates the preset fluctuation coefficient.

[0022] Preferably, the method for correcting the total strain of each region according to the environmental information is:

[0023] Calculate the temperature error of the strain detected by the optical fiber sensing unit according to the ambient temperature , calculated as:

[0024]

[0025] In the formula Indicates the preset reference temperature, Indicates the ambient temperature, represents the reference length of the optical fiber sensor at the reference temperature, Indicates the linear expansion coefficient of the optical fiber sensor;

[0026] According to the ambient wind speed and wind direction, calculate the wind force error of the strain detected by the optical fiber sensing unit , calculated as:

[0027]

[0028] In the formula Represents the angle between the wind direction and the optical fiber sensing unit, represents the air density, represents the drag coefficient of the optical fiber sensing unit, represents the diameter of the optical fiber sensing unit, represents the elastic modulus of the optical fiber sensing unit;

[0029] According to the temperature error , Wind force error and the total strain Calculate the force and strain , .

[0030] Preferably, the stress concentration area is compared with the force strain on both sides of the bridge:

[0031] When in continuous In the sampling, a certain area satisfies both , it is considered that cracks appear in the area and a crack alarm signal is generated;

[0032] When in continuous In the sampling, the stress strain on both sides of the bridge satisfies , it is considered that the optical fiber sensing units on both sides of the bridge are abnormal and generate equipment alarm signals;

[0033] in , They represent the stress strain on both sides of the bridge, Indicates the preset error coefficient.

[0034] A bridge crack detection system, the detection system adopts the above detection method, including a positioning device and a detection device:

[0035] The positioning device includes:

[0036] A first data acquisition module, the first data acquisition module includes two groups of detection units, which are respectively arranged at the entrances of both ends of the bridge and are both communicatively connected to the data processing module, and are used to collect vehicle information of vehicles entering the bridge;

[0037] A second data acquisition module, the second data acquisition module includes a plurality of groups of image acquisition units, which are evenly arranged along the bridge and are in communication connection with the data processing module, and are used to collect movement information of vehicles entering the bridge;

[0038] A data processing module, which is in communication with the data analysis module and is used to perform 3D modeling and grid area division on the bridge, and generate stress concentration areas according to vehicle information and motion information;

[0039] The detection device includes:

[0040] A combined sensing module, which is arranged at the bottom of the stress concentration area of ​​the bridge and both sides of the bridge, includes an optical fiber sensing unit, a temperature sensing unit, and an anemometer, and is connected to the data analysis module for communication, and is used to collect the total strain and environmental information of each stress concentration area and both sides of the bridge;

[0041] A data analysis module, which is in communication with the alarm module and is used to modify the total strain amount according to the environmental information to generate the force strain amount, compare the force strain amounts of each stress concentration area and both sides of the bridge, and send the comparison results to the alarm module;

[0042] An alarm module is used to generate different alarm signals according to different comparison results.

[0043] Compared with the prior art, the present invention has the following beneficial effects:

[0044] The present invention divides the bridge into grid areas, thereby finding the stress concentration area of ​​the bridge according to the movement trajectory and weight data of each vehicle, and setting a combined sensing module at the bottom of the bridge in the stress concentration area to detect cracks. This method can not only locate the position where cracks are most likely to occur on the bridge, but also reduce the points that need to be detected, which not only reduces the detection cost, but also reduces the data that needs to be detected, making the system respond faster. At the same time, by detecting the environmental information of each detection point and using the environmental information to correct the detection result, the influence of ambient temperature and wind force on the detection result is reduced, making the detection result more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a schematic diagram of the overall method flow of the present invention;

[0046] Figure 2 It is a schematic diagram of the module of the present invention. DETAILED DESCRIPTION

[0047] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific embodiments.

[0048] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present invention should be understood by people with ordinary skills in the field to which the present invention belongs. The words "first", "second" and similar words used in the present invention do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0049] Example:

[0050] See also Figure 1 , the present invention provides a technical solution:

[0051] A bridge crack detection method, the specific steps comprising:

[0052] S1: 3D modeling of the bridge is performed, and the road surface of the bridge is evenly divided into several groups of grid areas. When modeling, the length, width, height and other parameters of the bridge can be obtained from the engineering drawings of the bridge, which can be obtained from the online database of the municipal department or design company, or by taking drone photos and then restoring the model. When dividing, the bridge is divided horizontally and vertically according to the user settings and the lanes of the bridge, and the bridge is divided into grid areas, where Set the number of users for the horizontal direction, is the number of longitudinal lanes. The larger the number set by the user, the finer the divided grid area is, and the more accurate the generated stress concentration area is. However, the amount of data calculation is also greater. Therefore, it is necessary to adjust according to the actual situation so that the length of each grid area is at least greater than the length of some common vehicles. The vehicle information and movement information entering the bridge within a period of time are collected. The vehicle information includes vehicle weight data, traffic flow data, and license plate data. The movement information includes the vehicle's movement trajectory and movement time. Several stress concentration areas are generated based on the vehicle information and movement information.

[0053] The generation logic of the stress concentration area is:

[0054] Based on the 3D modeling, mesh area division and motion information of the bridge, the travel time of each vehicle passing through different areas is obtained. , where the subscript Indicates grid coordinates, superscript Indicates the vehicle number, ,in Represents the traffic flow data within the sampling time;

[0055] Calculate the total weight and total driving time of vehicles passing through different areas during the sampling time, and calculate the concentration coefficient corresponding to different areas based on the total weight and total driving time , calculated as:

[0056]

[0057] In the formula Represents the vehicle weight data of each vehicle passing through different areas, Indicates the preset time threshold.

[0058] It can be seen from the calculation formula of the concentration coefficient that the concentration coefficient reflects the impact of the total weight of vehicles passing through a certain area and the corresponding driving time of each vehicle in the area on the area during the data collection time. The time threshold represents the time required to pass through the area when driving at a certain speed. This value can be obtained by detecting the motion trajectories of different vehicles for a long time and calculating their average speed. It can also be defined by the user according to actual conditions. When the vehicle is driving normally, the value of the second half of the logarithmic part of the concentration coefficient remains at around 1, and the concentration coefficient is mainly affected by the total weight. When a traffic jam occurs, the driving time of vehicles passing through the grid area increases greatly, which will also greatly increase the value of the second half of the logarithmic part of the concentration coefficient. At this time, the concentration coefficient is affected by the total weight and the total driving time, but the influence of the total weight is still the main one, and the influence of the total driving time is relatively small, which plays a role in auxiliary judgment.

[0059] The concentration coefficients of different regions Centralized Matrix , calculate the concentration matrix The average value of each element in and standard deviation , the calculation methods are:

[0060]

[0061]

[0062] When the concentration factor of a certain area satisfy When , the area is considered to be a stress concentration area, where Indicates the preset fluctuation coefficient.

[0063] S2: Combined sensing modules are respectively set up at the bottom of the stress concentration area and both sides of the bridge to collect the total strain of the bridge in the corresponding area and the environmental information of the environment where the combined sensing module is located. The combined sensing module includes an optical fiber sensing unit, a temperature sensing unit, and an anemometer. The environmental information includes ambient temperature, ambient wind speed, and wind direction. Since there will be no vehicles passing by on both sides of the bridge, the stress is minimal, so it is used for comparison and as a judgment standard. The coordinates of one side can be expressed as , , …, , the coordinates on the other side can be expressed as , , …, .

[0064] S3: The corresponding total strain is corrected according to the environmental information of each area to obtain the stress strain of each area, and the stress concentration area is compared with the stress strain on both sides of the bridge, and different alarm signals are generated according to the comparison results.

[0065] The method for correcting the total strain of each area based on environmental information is:

[0066] Calculate the temperature error of the strain detected by the optical fiber sensing unit according to the ambient temperature , calculated as:

[0067]

[0068] In the formula Indicates the preset reference temperature, Indicates the ambient temperature, represents the reference length of the optical fiber sensor at the reference temperature, Indicates the linear expansion coefficient of the optical fiber sensor;

[0069] According to the ambient wind speed and wind direction, calculate the wind force error of the strain detected by the optical fiber sensing unit , calculated as:

[0070]

[0071] In the formula Represents the angle between the wind direction and the optical fiber sensing unit, represents the air density, represents the drag coefficient of the optical fiber sensing unit, represents the diameter of the optical fiber sensing unit, It represents the elastic modulus of the fiber optic sensing unit. When installing the fiber optic sensing unit, the fiber optic sensing unit can be set parallel to the bridge. In this way, when the anemometer collects the wind direction, the angle between it and the fiber optic sensing unit can be obtained.

[0072] According to the temperature error , Wind force error and the total strain Calculate the force and strain , By subtracting the temperature error caused by ambient temperature and the wind error caused by wind, the environmental factors in the detection results can be reduced and the detection accuracy can be improved.

[0073] Compare the stress concentration area with the force and strain on both sides of the bridge:

[0074] When in continuous In the sampling, a certain area satisfies both , then it is considered that the stress strain in the stress concentration area is and the corresponding stress strain on both sides of the bridge and In comparison, it has been at a large value for a long time and has not recovered. Therefore, it is most likely not caused by vibration caused by the passing of a vehicle, but deformation caused by cracks. Therefore, it is determined that cracks appear in this area and a crack alarm signal is generated.

[0075] When in continuous In the sampling, the stress strain on both sides of the bridge satisfies Since the two sides of the bridge are not lanes and no vehicles pass by, they are considered to be the least affected. Under normal circumstances, the force strain on both sides should be basically the same. If there is a large change on one side, it is considered that the fiber optic sensor units on both sides of the bridge are abnormal, and an equipment alarm signal is generated. By comparing the fiber optic sensor units on both sides of the bridge, inaccurate detection and false alarms caused by equipment reasons can be reduced, thereby improving the detection accuracy of the entire detection system.

[0076] in , They represent the stress strain on both sides of the bridge, Indicates the preset error coefficient.

[0077] See also Figure 2 The present invention also provides a bridge crack detection system, which adopts the above detection method and includes a positioning device and a detection device:

[0078] The positioning device includes:

[0079] A first data acquisition module, the first data acquisition module includes two groups of detection units, the detection units include a camera for shooting images and a scale or pressure sensor for measuring weight, which are respectively arranged at the entrances at both ends of the bridge and are both communicatively connected with the data processing module, and are used to collect vehicle information of vehicles entering the bridge;

[0080] A second data acquisition module, which includes a plurality of image acquisition units, and restores the motion path of the corresponding vehicle on the bridge by shooting a video of the vehicle or collecting a plurality of motion images. The second data acquisition module is evenly arranged along the bridge and is in communication connection with the data processing module, and is used to collect motion information of vehicles entering the bridge;

[0081] A data processing module, which is in communication with the data analysis module and is used to perform 3D modeling and grid area division on the bridge, and generate stress concentration areas according to vehicle information and motion information;

[0082] The detection device includes:

[0083] A combined sensing module, which is arranged at the bottom of the stress concentration area of ​​the bridge and both sides of the bridge, includes an optical fiber sensing unit, a temperature sensing unit, and an anemometer, and is connected to the data analysis module for communication, and is used to collect the total strain and environmental information of each stress concentration area and both sides of the bridge;

[0084] A data analysis module, which is in communication with the alarm module and is used to modify the total strain amount according to the environmental information to generate the force strain amount, compare the force strain amounts of each stress concentration area and both sides of the bridge, and send the comparison results to the alarm module;

[0085] An alarm module is used to generate different alarm signals according to different comparison results.

[0086] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0087] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. Those skilled in the art may appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein may be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0088] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0089] The above description is only a specific implementation manner of the present application, but 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.

Claims

1. A bridge crack detection method, characterized in that: The specific steps include: S1: 3D modeling of the bridge is performed, and the road surface of the bridge is evenly divided into several groups of grid areas. Vehicle information and movement information entering the bridge within a period of time are collected, and several stress concentration areas are generated based on the vehicle information and movement information; The bridge is divided horizontally and vertically according to the user settings and the lanes of the bridge. grid areas, where Set the number of users for the horizontal direction, is the number of longitudinal lanes; The generation logic of the stress concentration area is: Based on the 3D modeling, mesh area division and motion information of the bridge, the travel time of each vehicle passing through different areas is obtained. , where the subscript Indicates grid coordinates, superscript Indicates the vehicle number, ,in Represents the traffic flow data within the sampling time; Calculate the total weight and total driving time of vehicles passing through different areas during the sampling time, and calculate the concentration coefficient corresponding to different areas based on the total weight and total driving time , calculated as: In the formula Represents the vehicle weight data of each vehicle passing through different areas, Indicates a preset time threshold; The concentration coefficients of different regions Centralized Matrix , calculate the concentration matrix The average value of each element in and standard deviation , the calculation methods are: When the concentration factor of a certain area satisfy When , the area is considered to be a stress concentration area, where Indicates the preset volatility coefficient; S2: Combined sensing modules are respectively set at the bottom of the stress concentration area and both sides of the bridge to collect the total strain of the bridge in the corresponding area and the environmental information of the environment where the combined sensing modules are located; S3: Correct the corresponding total strain according to the environmental information of each area to obtain the stress strain of each area, compare the stress concentration area with the stress strain on both sides of the bridge, and generate different alarm signals according to the comparison results; The method for correcting the total strain of each area based on environmental information is: Calculate the temperature error of the strain detected by the optical fiber sensing unit according to the ambient temperature , calculated as: In the formula Indicates the preset reference temperature, Indicates the ambient temperature, represents the reference length of the optical fiber sensor at the reference temperature, It represents the linear expansion coefficient of the optical fiber sensor; According to the ambient wind speed and wind direction, calculate the wind force error of the strain detected by the optical fiber sensing unit , calculated as: In the formula Represents the angle between the wind direction and the optical fiber sensing unit, represents the air density, represents the drag coefficient of the optical fiber sensing unit, represents the diameter of the optical fiber sensing unit, represents the elastic modulus of the optical fiber sensing unit; According to the temperature error , Wind force error and the total strain Calculate the force and strain , .

2. A bridge crack detection method according to claim 1, characterized in that: The vehicle information includes vehicle weight data, traffic flow data, and license plate data; the motion information includes the vehicle's motion trajectory and motion time; the combined sensing module includes a fiber optic sensing unit, a temperature sensing unit, and an anemometer; and the environmental information includes ambient temperature, ambient wind speed, and wind direction.

3. A bridge crack detection method according to claim 1, characterized in that: Compare the stress concentration area with the force and strain on both sides of the bridge: When in continuous In the sampling, a certain area satisfies both , it is considered that cracks appear in the area and a crack alarm signal is generated; When in continuous In the sampling, the stress strain on both sides of the bridge satisfies , it is considered that the optical fiber sensing units on both sides of the bridge are abnormal and generate equipment alarm signals; in , They represent the stress strain on both sides of the bridge, Indicates the preset error coefficient.

4. A bridge crack detection system, characterized in that: The detection system adopts the detection method according to any one of claims 1 to 3, including a positioning device and a detection device: The positioning device includes: A first data acquisition module, the first data acquisition module includes two groups of detection units, which are respectively arranged at the entrances of both ends of the bridge and are both communicatively connected to the data processing module, and are used to collect vehicle information of vehicles entering the bridge; A second data acquisition module, the second data acquisition module includes a plurality of groups of image acquisition units, which are evenly arranged along the bridge and are in communication connection with the data processing module, and are used to collect movement information of vehicles entering the bridge; A data processing module, which is in communication with the data analysis module and is used to perform 3D modeling and grid area division on the bridge, and generate stress concentration areas according to vehicle information and motion information; The detection device includes: A combined sensing module, which is arranged at the bottom of the stress concentration area of ​​the bridge and both sides of the bridge, includes an optical fiber sensing unit, a temperature sensing unit, and an anemometer, and is connected to the data analysis module for communication, and is used to collect the total strain and environmental information of each stress concentration area and both sides of the bridge; A data analysis module, which is in communication with the alarm module and is used to modify the total strain amount according to the environmental information to generate the force strain amount, compare the force strain amounts of each stress concentration area and both sides of the bridge, and send the comparison results to the alarm module; An alarm module is used to generate different alarm signals according to different comparison results.

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