Bridge bearing damage detection method and system based on deflection monitoring

Abstract

The present application relates to the field of bridge damage detection, in particular to a bridge bearing damage detection method and system based on deflection monitoring. The method first obtains deflection data, wind speed data, wind pressure data and vibration frequency data of different detection positions of the bridge at each time, obtains the adjustment deformation degree of the target detection position at the target time according to the wind speed data and wind pressure data of the target detection position at the target time and the serial number value corresponding to the target time, and combines the deflection data and the vibration frequency data, obtains the adjustment deformation degree of the target detection position at the target time, obtains the damage characteristic value of the target detection position according to the fluctuation of the adjustment deformation degree of the target detection position at each time, obtains the damage possibility of each detection position according to the difference of the damage characteristic value of each detection position, and detects the bearing damage of different positions of the bridge based on the damage possibility. The present application can eliminate the influence of wind force on the bridge bearing damage detection and improve the accuracy of the bridge damage position detection.

Description

Technical Field

[0001] This invention relates to the field of bridge damage detection, and specifically to a method and system for detecting bridge load-bearing damage based on deflection monitoring. Background Technology

[0002] Deflection refers to the vertical displacement of a structure or component when it undergoes bending deformation under external force. There is a close relationship between bridge deflection and load-bearing damage. When a bridge has load-bearing damage such as concrete cracking, steel corrosion or fracture, it will lead to a decrease in the stiffness of the bridge structure, which in turn will lead to a significant increase in bridge deflection. By monitoring and analyzing bridge deflection, we can provide important reference for assessing the load-bearing capacity and safety status of the bridge, promptly identify potential safety hazards of load-bearing damage, and ensure the safe operation of the bridge.

[0003] In related technologies, multiple deflection sensors are usually installed at different locations on a bridge to collect deflection data. The location of load-bearing damage is determined by analyzing the deformation differences between the locations. However, wind factors can affect the actual measurement of deflection. Under the action of wind, the bridge may resonate, causing severe vibrations at a specific frequency, which leads to large deformations. This can result in errors in the measurement results of the deflection sensors, affecting the judgment of the location of bridge damage. Summary of the Invention

[0004] To address the technical problem that wind forces can cause errors in the measurement results of deflection sensors, affecting the determination of bridge damage locations, this invention aims to provide a bridge load-bearing damage detection method and system based on deflection monitoring. The specific technical solution adopted is as follows: This invention proposes a method for detecting bridge load-bearing damage based on deflection monitoring, the method comprising: Obtain deflection data, wind speed data, wind pressure data, and vibration frequency data at different detection locations on the bridge at each moment within a preset time period; Using any detection location as the target detection location and any time as the target time, the initial deformation degree of the target detection location at the target time is obtained based on the deflection and vibration frequency data of the target detection location at the target time. The wind force influence degree of the target detection location at the target time is obtained based on the wind speed and wind pressure data of the target detection location at the target time and the corresponding sequence number value. Based on the wind force influence degree, the initial deformation degree is adjusted to obtain the adjusted deformation degree of the target detection location at the target time. Based on the fluctuation of the degree of adjustment deformation at the target detection location at each time and the overall level of deflection data at all times, the damage characteristic value of the target detection location is obtained; based on the difference of the damage characteristic value of each detection location in the preset neighborhood of the target detection location and the damage characteristic value of the target detection location, the damage probability of the target detection location is obtained. Based on the probability of damage at each detection location, load-bearing damage at different locations on the bridge is detected.

[0005] Furthermore, obtaining the initial deformation degree of the target detection position at the target time includes: By performing a negative correlation mapping on the elastic modulus of the materials used in the bridge, the deformation coefficient of the bridge can be obtained. The bridge's deflection influence weight is obtained by combining the bridge's length and the aforementioned deformation coefficient. The product of the deflection influence weight and the deflection data of the target detection position at the target time is used as the first deformation parameter of the target detection position at the target time. The absolute value of the difference between the vibration frequency data of the target detection location at the target time and the natural vibration frequency of the bridge is used as the second deformation parameter of the target detection location at the target time. The first deformation parameter and the second deformation parameter are combined to obtain the initial degree of deformation of the target detection position at the target time.

[0006] Furthermore, the degree of wind influence on the target detection location at the target time includes: The wind-receiving area of ​​the integrated sensor at the target detection location is used as the numerator, the surface roughness of the integrated sensor at the target detection location is used as the denominator, and the ratio is used as the drag coefficient of the integrated sensor at the target detection location. By combining the wind speed data and wind pressure data at the target detection location at the target time with the drag coefficient of the integrated sensor at the target detection location, the wind force coefficient at the target detection location at the target time is obtained. Based on the sequence number corresponding to the target time, the wind force coefficient of the target detection location at the target time is adjusted to obtain the degree of wind force influence of the target detection location at the target time.

[0007] Further, adjusting the wind force coefficient of the target detection location at the target time based on the sequence value corresponding to the target time, to obtain the degree of wind influence of the target detection location at the target time, includes: Use the index value corresponding to the target time as the numerator, the sum of the index values ​​corresponding to all times as the denominator, and use the ratio as the cumulative weight of the wind force at the target time. The product of the cumulative wind force weight at the target time and the wind force coefficient at the target detection location at the target time is normalized to obtain the degree of wind force influence at the target detection location at the target time.

[0008] Furthermore, the degree of adjustment deformation of the target detection position at the target time includes: The product of the wind force influence at the target detection location at the target time and the initial deformation degree is used as the deformation degree adjustment amount at the target detection location at the target time. The difference between the initial deformation degree and the deformation degree adjustment amount at the target detection position at the target time is taken as the adjusted deformation degree of the target detection position at the target time.

[0009] Furthermore, obtaining the damage feature value at the target detection location includes: The degree of dispersion of the adjustment deformation at the target detection position at all times is analyzed to obtain the degree of deformation fluctuation at the target detection position. The average value of the deflection data at all times at the target detection location is taken as the overall deflection value at the target detection location; By combining the degree of deformation fluctuation and the overall deflection value, the damage characteristic value of the target detection location is obtained.

[0010] Furthermore, the probability of damage at the target detection location includes: In the target detection location and the preset neighborhood, other detection locations besides the target detection location are used as reference detection locations; Based on the difference in damage feature values ​​between the target detection location and each reference detection location, a first damage coefficient for the target detection location is obtained; The difference between the damage feature value at the target detection location and the minimum damage feature value at all detection locations is used as the second damage coefficient of the target detection location. The first damage coefficient and the second damage coefficient are combined and normalized to obtain the damage probability at the target detection location.

[0011] Furthermore, the first damage coefficient for obtaining the target detection location includes: The damage feature value at the target detection location is used as the numerator, and the damage feature value at each reference detection location is used as the denominator. The ratio is used as the relative deformation difference value between the target detection location and each reference detection location. The average of the relative deformation differences between the target detection location and all reference detection locations is used as the first damage coefficient for the target detection location.

[0012] Furthermore, the detection of load-bearing damage at different locations on the bridge includes: The detection locations where the probability of damage is greater than a preset probability threshold are taken as the load-bearing damage locations of the bridge.

[0013] The present invention also proposes a bridge load-bearing damage detection system based on deflection monitoring. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements any of the steps of a bridge load-bearing damage detection method based on deflection monitoring.

[0014] The present invention has the following beneficial effects: This invention addresses the issue that wind can cause errors in the measurement results of deflection sensors, affecting the determination of bridge damage locations. Therefore, it first acquires deflection, wind speed, wind pressure, and vibration frequency data at different detection locations on the bridge at each moment within a preset time period. Subsequently, based on these data, the degree of deformation at different detection locations can be accurately analyzed, eliminating the influence of wind on bridge deformation and improving the accuracy of damage location detection. The invention first analyzes the deformation of the target detection location at a target time, using the initial deformation degree to preliminarily reflect the extent of deformation at the target detection location. However, it considers that wind interference can lead to lower calculation accuracy in the initial deformation degree calculation process, and also takes into account the inherent characteristics of bridge deformation. While there is a cumulative effect, the effect of wind on bridges is not cumulative. Therefore, by analyzing the wind speed and wind pressure data at the target detection location at the target time and combining them with the corresponding sequence value at the target time, the degree of wind influence is used to reflect the degree of wind influence on the deformation of the target detection location at the target time. Based on the degree of wind influence, the initial deformation degree is adjusted to eliminate the influence of wind on the bridge deformation analysis. By adjusting the deformation degree, the extent of deformation at the target detection location of the bridge at the target time is accurately reflected. Furthermore, the degree of load-bearing damage caused by deformation at the target detection location of the bridge is reflected through damage characteristic values. Finally, based on the damage probability, load-bearing damage at different locations of the bridge is detected, improving the accuracy of bridge load-bearing damage detection. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1A flowchart illustrating a bridge load-bearing damage detection method based on deflection monitoring, provided in one embodiment of the present invention; Figure 2 This is a schematic diagram of the distribution of integrated sensors on a bridge according to an embodiment of the present invention; Figure 3 This is a flowchart illustrating a method for obtaining the degree of wind influence on the target detection location at the target time, according to an embodiment of the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of a bridge load-bearing damage detection method and system based on deflection monitoring proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details a specific scheme for a bridge load-bearing damage detection method and system based on deflection monitoring provided by the present invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a bridge load-bearing damage detection method based on deflection monitoring, according to an embodiment of the present invention. The method includes: Step S1: Obtain deflection data, wind speed data, wind pressure data, and vibration frequency data at different detection locations on the bridge at each moment within a preset time period.

[0021] Bridge deflection measures the degree of deformation under stress. If a bridge is damaged, especially due to structural fatigue or cracks, its stiffness decreases, leading to greater deflection under the same load and more pronounced deformation. Therefore, analyzing bridge deflection data can help determine whether damage exists, its location, and its extent.

[0022] This invention uses a truss arch bridge as an example. Since the trusses of a truss arch bridge primarily bear the tensile force from the bridge deck, the bridge structure at the truss location is more prone to deformation and load-bearing damage. Furthermore, because this invention requires the measurement of various data, multiple different types of sensors are needed. To facilitate data acquisition, this invention integrates multiple sensors—namely, fiber optic sensors, wind speed sensors, wind pressure sensors, and accelerometers—to form an integrated sensor. These integrated sensors are then installed on the side of the bridge structure at the truss location. (See [link to relevant documentation]). Figure 2 The diagram illustrates the distribution of integrated sensors on a bridge according to an embodiment of the present invention. The installation location of each integrated sensor can be considered as a detection location. The fiber optic sensor in the integrated sensor at each detection location can be used to collect the deflection data of the detection location at each moment within a preset time period. The wind speed sensor can be used to collect the wind speed data of the detection location at each moment within the preset time period. The wind pressure sensor can be used to collect the wind pressure data of the detection location at each moment within the preset time period. The accelerometer can be used to collect the vibration frequency data of the detection location at each moment within the preset time period.

[0023] The preset time period is set to 30 minutes, and the time interval for all data collections is the same, set to 0.25 seconds. The specific values ​​of the preset time period and the time interval for data collection can also be set by the implementer according to the specific implementation scenario, and are not limited here.

[0024] Step S2: Take any detection location as the target detection location and any time as the target time. Based on the deflection data and vibration frequency data of the target detection location at the target time, obtain the initial deformation degree of the target detection location at the target time. Based on the wind speed data and wind pressure data of the target detection location at the target time and the corresponding sequence value of the target time, obtain the wind force influence degree of the target detection location at the target time. Based on the wind force influence degree, adjust the initial deformation degree to obtain the adjusted deformation degree of the target detection location at the target time.

[0025] Because the deformation and wind load vary at different detection locations on a bridge at different times, we first use any one detection location as the target detection location and any one time as the target time. Then, we analyze the deformation of the target detection location at the target time. The larger the deflection data of the target detection location at the target time, the greater the degree of deformation. At the same time, the degree of deformation of the target detection location at the target time is also related to the vibration frequency data. Therefore, we can analyze the deflection and vibration frequency data of the target detection location at the target time. The initial deformation degree obtained can preliminarily reflect the degree of deformation of the target detection location of the bridge at the target time. Subsequently, we can further adjust the initial deformation degree to eliminate the influence of wind and improve the accuracy of the deformation analysis of the target detection location.

[0026] Preferably, in one embodiment of the present invention, the method for obtaining the initial deformation degree of the target detection position at the target time specifically includes: The smaller the elastic modulus of the materials used to manufacture a bridge, the lower the stiffness of the bridge, and thus the more easily the bridge deforms under load. Therefore, a negative correlation mapping can be performed on the elastic modulus of the materials used in the bridge to obtain the deformation coefficient of the bridge. The larger the deformation coefficient, the more easily the bridge deforms. The elastic modulus of the materials used in the bridge is a known value. If the main material used in the bridge is concrete, the elastic modulus is usually 20-40 GPa. If the main material used in the bridge is structural steel, the elastic modulus is usually 200-210 GPa. The specific value of the elastic modulus can be determined according to the specific materials used in the bridge.

[0027] Meanwhile, the greater the length of the bridge and the greater the deformation coefficient, the more easily the bridge is deformed, and the greater the deflection of the bridge when deformation occurs. Therefore, the length and deformation coefficient of the bridge can be combined to obtain the deflection influence weight of the bridge. Then, the product of the deflection influence weight and the deflection data of the target detection position at the target time can be used as the first deformation parameter of the target detection position at the target time. The larger the first deformation parameter, the greater the degree of deformation of the target detection position of the bridge at the target time.

[0028] In embodiments of the present invention, the sum or product of the bridge length and deformation coefficient can be used as the weight of the bridge deflection influence, thereby achieving a comprehensive consideration of the two, which is not limited here.

[0029] Meanwhile, the greater the difference between the vibration frequency data of the target detection location at the target time and the natural vibration frequency of the bridge, the greater the degree of deformation of the target detection location at the target time. Therefore, the absolute value of the difference between the vibration frequency data of the target detection location at the target time and the natural vibration frequency of the bridge can be used as the second deformation parameter of the target detection location at the target time. The natural vibration frequency of the bridge is a known value, which can be obtained through existing active excitation testing or finite element analysis, etc., which will not be elaborated here.

[0030] Then, the first deformation parameter and the second deformation parameter can be combined to obtain the initial degree of deformation of the target detection position at the target time.

[0031] In embodiments of the present invention, the sum or product of the first deformation parameter and the second deformation parameter can be used as the initial degree of deformation of the target detection position at the target time, thereby achieving a combination of the two, which is not limited here.

[0032] As an example, in one embodiment of the present invention, the expression for the initial deformation degree of the target detection position at the target time can be specifically as follows: in, This indicates the initial degree of deformation at the target detection location at the target time. Indicates the length of the bridge; This indicates the elastic modulus of the materials used in bridge construction. ; Indicates the deformation coefficient of the bridge; This indicates the weight of the bridge's deflection effect; This represents the deflection data at the target detection location at the target time. This represents the first deformation parameter at the target detection location at the target time. This represents the vibration frequency data at the target detection location at the target time. Indicates the natural vibration frequency of the bridge; The second deformation parameter represents the target detection location at the target time.

[0033] It should be noted that negative correlation mapping can also be achieved through other basic mathematical operations in other embodiments of the present invention, which will not be elaborated here.

[0034] Considering the interference of wind force during the calculation of the initial deformation degree, which leads to low calculation accuracy, and considering that the deformation of the bridge has a cumulative effect, but the effect of wind force on the bridge does not have a cumulative effect, we analyze the wind speed and wind pressure data of the target detection location at the target time, and combine them with the corresponding sequence value at the target time to reflect the degree of wind force influence on the deformation of the target detection location at the target time through the degree of wind force influence.

[0035] Preferably, in one embodiment of the present invention, the method for obtaining the degree of wind influence at the target detection location at the target time specifically includes: Please see Figure 3 The diagram illustrates a flowchart of a method for obtaining the degree of wind influence on a target detection location at a target time, according to an embodiment of the present invention.

[0036] Step S201: Take the wind-receiving area of ​​the integrated sensor at the target detection location as the numerator, the surface roughness of the integrated sensor at the target detection location as the denominator, and use the ratio as the drag coefficient of the integrated sensor at the target detection location.

[0037] The larger the wind-receiving area of ​​the integrated sensor at the target detection location and the smaller the surface roughness of the integrated sensor at the target detection location, the stronger the effect of wind on the target detection location. Therefore, the wind-receiving area of ​​the integrated sensor at the target detection location can be used as the numerator, and the surface roughness of the integrated sensor at the target detection location can be used as the denominator. The ratio can be used as the drag coefficient of the integrated sensor at the target detection location. The wind-receiving area of ​​the integrated sensor at the target detection location is the projected area of ​​the integrated sensor in the wind direction. The surface roughness of the integrated sensor at the target detection location is obtained by scanning the surface of the integrated sensor with a contact roughness meter and recording its small height changes, thereby generating the surface roughness of the integrated sensor.

[0038] Step S202: Combine the wind speed and wind pressure data at the target detection location at the target time with the drag coefficient of the integrated sensor at the target detection location to obtain the wind force coefficient at the target detection location at the target time.

[0039] When wind acts on a bridge, it causes deformation or vibration. The magnitude of the wind force acting on each detection location determines the degree of influence on the deformation of that location. The greater the wind speed and wind pressure data at the target detection location at the target time, and the greater the drag coefficient of the integrated sensor at the target detection location, the stronger the wind force acting on the target detection location at the target time. This indicates that the wind force has a greater impact on the deformation of the target detection location at the target time. Therefore, the wind speed and wind pressure data at the target detection location at the target time, along with the drag coefficient of the integrated sensor at the target detection location, can be combined to obtain the wind force coefficient of the target detection location at the target time.

[0040] In embodiments of the present invention, the sum or product of the wind speed data and wind pressure data of the target detection location at the target time and the drag coefficient of the integrated sensor at the target detection location can be used as the wind force coefficient of the target detection location at the target time, thereby achieving a comprehensive analysis of the three data points. No limitation is imposed here.

[0041] As an example, in one embodiment of the present invention, the expression for the wind force coefficient at the target detection location at the target time can be specifically as follows: in, This represents the wind force coefficient at the target detection location at the target time. This represents the wind speed data at the target detection location at the target time. This represents the wind pressure data at the target detection location at the target time. The windward area of ​​the integrated sensor representing the target detection location; The roughness of the integrated sensor surface indicating the target detection location. ; The drag coefficient of the integrated sensor representing the target detection position.

[0042] Step S203: Adjust the wind force coefficient of the target detection location at the target time according to the sequence value corresponding to the target time, and obtain the degree of wind force influence of the target detection location at the target time.

[0043] Because the deformation of a bridge has a cumulative effect over time—meaning that the deflection at the target detection location increases and the deformation becomes more pronounced over time—while the effect of wind on a bridge does not have a cumulative effect over time, directly adjusting the initial deformation level using the wind force coefficient in subsequent calculations would result in lower accuracy of the final calculation results. Therefore, it is necessary to adjust the wind force coefficient at the target detection location at the target time based on the corresponding sequence value to obtain the degree of wind influence at the target detection location at the target time.

[0044] Preferably, in one embodiment of the present invention, the method for obtaining the degree of wind influence at the target detection location at the target time further includes: The numerator is the index value corresponding to the target time, and the denominator is the sum of the index values ​​corresponding to all times. This ratio is used as the cumulative wind force weight for the target time. The product of this cumulative wind force weight and the wind force coefficient at the target detection location at the target time is then normalized, limiting the calculation result to... Within the range, the degree of wind influence on the target detection location at the target time can be obtained.

[0045] In one embodiment of the present invention, the normalization process can be specifically, for example, maximum and minimum value normalization. Furthermore, the normalization in subsequent steps can all adopt maximum and minimum value normalization. In other embodiments of the present invention, other normalization methods can be selected according to the specific range of the numerical values, which will not be elaborated further.

[0046] As an example, in one embodiment of the present invention, the expression for the degree of wind influence at the target detection location at the target time can be specifically as follows: in, This indicates the degree of wind influence on the target detection location at the target time. This represents the wind force coefficient at the target detection location at the target time. This indicates the sequence number corresponding to the target time. For example, if the target time is the first time, then the sequence number corresponding to the target time is the value 1. Indicates the first The sequence number corresponding to the time; This indicates the number of all moments within a preset time period; Indicates the cumulative weight of wind force at the target time; This represents the normalization function, used for normalization processing.

[0047] After obtaining the degree of wind influence at the target detection location at the target time, the initial deformation degree of the target detection location at the target time can be adjusted using the degree of wind influence, thereby eliminating the influence of wind on the bridge deformation analysis. The obtained adjusted deformation degree accurately reflects the degree of deformation of the target detection location of the bridge at the target time. Subsequently, based on the adjusted deformation degree of the target detection location at each time, the possibility of load-bearing damage at the target detection location can be accurately analyzed.

[0048] Preferably, in one embodiment of the present invention, the method for obtaining the degree of adjustment deformation of the target detection position at the target time specifically includes: The greater the wind influence on the target detection location at the target time, the greater the wind force effect on the target detection location at the target time. In order to eliminate the influence of wind force on deformation analysis, it is necessary to reduce the initial deformation degree to a greater extent. Therefore, the product of the wind influence on the target detection location at the target time and the initial deformation degree can be used as the deformation degree adjustment of the target detection location at the target time, and the difference between the initial deformation degree of the target detection location at the target time and the deformation degree adjustment can be used as the adjusted deformation degree of the target detection location at the target time.

[0049] As an example, in one embodiment of the present invention, the expression for the degree of adjustment of the target detection position at the target time can be specifically as follows: in, This indicates the degree of adjustment and deformation of the target detection position at the target time. This indicates the degree of wind influence on the target detection location at the target time. This indicates the initial degree of deformation at the target detection location at the target time.

[0050] The degree of deformation adjustment of the target detection position at each time step can be obtained using the same method described above.

[0051] Step S3: Based on the fluctuation of the degree of adjustment deformation of the target detection position at each time and the overall level of deflection data at all times, obtain the damage feature value of the target detection position; based on the difference of the damage feature values ​​of each detection position in the preset neighborhood of the target detection position and the damage feature value of the target detection position, obtain the damage probability of the target detection position.

[0052] In the above deformation analysis of the target detection location at each moment, the influence of wind force was removed. Next, the load-bearing damage caused by deformation of the target detection location can be analyzed. When load-bearing damage occurs at the target detection location, the degree of adjustment deformation at each moment will exhibit irregular fluctuations. Furthermore, the overall level of deflection data at the target detection location at all moments is relatively large. Therefore, based on the fluctuation of the degree of adjustment deformation at each moment and the overall level of deflection data at all moments, the damage characteristic value of the target detection location can be obtained. The damage characteristic value reflects the degree of load-bearing damage caused by deformation at the target detection location of the bridge. Subsequently, the damage characteristic values ​​of different detection locations can be compared to accurately determine the detection location where load-bearing damage occurs, thereby improving the accuracy of the judgment of the bridge damage location.

[0053] Preferably, in one embodiment of the present invention, the method for obtaining the damage feature value at the target detection location specifically includes: The dispersion of the adjustment deformation degree of the target detection position at all times is analyzed to obtain the deformation fluctuation degree of the target detection position. The greater the deformation fluctuation degree, the greater the fluctuation of the adjustment deformation degree of the target detection position at each time, and thus the greater the degree of load-bearing damage at the target detection position.

[0054] In embodiments of the present invention, the standard deviation or variance of the degree of adjustment deformation of the target detection position at all times can be used as the degree of deformation fluctuation of the target detection position, thereby realizing the analysis of the degree of dispersion of the degree of adjustment deformation of the target detection position at all times, which is not limited here.

[0055] The average value of the deflection data at the target detection location at all times is taken as the overall deflection value of the target detection location. The larger the overall deflection value, the greater the overall level of the deflection data at the target detection location at all times, and thus the greater the degree of load-bearing damage at the target detection location.

[0056] This allows for the comprehensive analysis of the deformation fluctuation degree and the overall deflection value to obtain the damage characteristic value at the target detection location.

[0057] In embodiments of the present invention, the sum or product of the deformation fluctuation degree and the overall deflection value can be used as the damage characteristic value of the target detection location, thereby achieving a comprehensive understanding of the two, which is not limited herein.

[0058] As an example, in one embodiment of the present invention, the expression for the damage feature value at the target detection location can be specifically as follows: in, The damage feature value represents the location of the target detection; Indicates the degree of deformation fluctuation at the target detection location; This represents the overall deflection value at the target detection location.

[0059] The damage characteristic value of each detection location can be obtained using the same method described above. Based on the differences in the damage characteristic values ​​of each detection location, the probability of load-bearing damage at each detection location can be determined. If load-bearing damage occurs at the target detection location, the damage characteristic value of the target detection location will be larger than that of other detection locations in its local neighborhood, and the damage characteristic value of the target detection location will also be larger than that of all detection locations. Therefore, the probability of damage at the target detection location can be obtained based on the differences in the damage characteristic values ​​of each detection location in the preset neighborhood of the target detection location, as well as the damage characteristic value of the target detection location. The probability of damage reflects the likelihood of load-bearing damage occurring at the target detection location. Subsequently, the location of load-bearing damage on the bridge can be accurately detected based on the probability of damage, thereby improving the accuracy of bridge damage detection. The length of the preset neighborhood of the target detection location is set to 5, meaning that the preset neighborhood includes the four other detection locations closest to the target detection location and the target detection location itself. The specific value of the length of the preset neighborhood can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0060] Preferably, in one embodiment of the present invention, the method for obtaining the probability of damage at the target detection location specifically includes: In the target detection location and the preset neighborhood, other detection locations besides the target detection location are used as reference detection locations. Based on the difference in damage characteristic values ​​between the target detection location and each reference detection location, the first damage coefficient of the target detection location is obtained. The larger the first damage coefficient, the greater the possibility that the target detection location has load-bearing damage.

[0061] Preferably, in one embodiment of the present invention, the method for obtaining the first damage coefficient at the target detection location specifically includes: First, the damage characteristic value of the target detection location is used as the numerator, and the damage characteristic value of each reference detection location is used as the denominator. The ratio is used as the relative deformation difference value between the target detection location and each reference detection location. The larger the relative deformation difference value, the greater the degree of deformation at the target detection location compared to the degree of deformation at the reference detection location. This indicates that the target detection location is more likely to have load-bearing damage. Therefore, the average value of the relative deformation difference values ​​between the target detection location and all reference detection locations can be used as the first damage coefficient of the target detection location.

[0062] As an example, in one embodiment of the present invention, the expression for the first damage coefficient at the target detection location can be specifically as follows: in, The first damage coefficient represents the target detection location; The damage feature value represents the location of the target detection; Indicates the first Damage characteristic values ​​at each reference detection location; Indicates the target detection location and the first The relative deformation difference value between the reference detection locations ; This indicates the number of reference detection locations.

[0063] Then, the difference between the damage feature value of the target detection location and the minimum damage feature value of all detection locations is taken as the second damage coefficient of the target detection location. The larger the second damage coefficient, the larger the damage feature value of the target detection location is among all detection locations, which in turn indicates that the target detection location is more likely to have load-bearing damage.

[0064] As an example, in one embodiment of the present invention, the expression for the second damage coefficient at the target detection location can be specifically as follows: in, The second damage coefficient represents the target detection location; The damage feature value represents the location of the target detection; This represents the minimum value of the damage characteristic value across all detection locations.

[0065] Finally, the first and second damage coefficients are combined and normalized to limit the calculation results to a range of... Within the range, the probability of damage at the target detection location can be obtained.

[0066] In embodiments of the present invention, the sum or product of the first damage coefficient and the second damage coefficient can be calculated to achieve a combination of the two, which is not limited herein.

[0067] As an example, in one embodiment of the present invention, the expression for the probability of damage at the target detection location can be specifically as follows: in, Indicates the probability of damage at the target detection location; The first damage coefficient represents the target detection location; The second damage coefficient represents the target detection location; This represents the normalization function, used for normalization processing.

[0068] The probability of damage at each detection location can be obtained using the same method described above.

[0069] Step S4: Based on the probability of damage at each detection location, detect the load-bearing damage at different locations on the bridge.

[0070] The greater the probability of damage at a certain detection location, the more likely the bridge is to experience load-bearing damage at that location. Therefore, load-bearing damage at different locations on the bridge can be detected based on the probability of damage at each detection location, thereby improving the accuracy of bridge load-bearing damage detection.

[0071] Preferably, in one embodiment of the present invention, the method for detecting load-bearing damage at different locations of a bridge specifically includes: Locations where the probability of damage exceeds a preset probability threshold are defined as the locations of load-bearing damage to the bridge. The preset probability threshold ranges from [value missing]. In one embodiment of the present invention, the preset probability threshold is set to 0.85. The specific value of the preset probability threshold can also be set by the implementer according to the specific implementation scenario, and is not limited here.

[0072] For locations of load-bearing damage, during the inspection process, relevant personnel can use the location of the load-bearing damage as the center to find the damaged structures in the surrounding bridge structure, and promptly repair damaged structures such as cracks, corrosion, structural damage, and deformation to ensure the safe use of the bridge.

[0073] One embodiment of the present invention provides a bridge load-bearing damage detection system based on deflection monitoring. The system includes a memory, a processor, and a computer program. The memory is used to store the corresponding computer program, and the processor is used to run the corresponding computer program. When the computer program runs in the processor, it can implement the methods described in steps S1 to S4.

[0074] It should be noted that the order of the above embodiments of the present invention is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0075] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. A method for detecting bridge load-bearing damage based on deflection monitoring, characterized in that, The method includes: The deflection, wind speed, wind pressure, and vibration frequency data of different detection locations on the bridge are acquired at each moment within a preset time period; the time interval for acquiring various data is the same. Using any detection location as the target detection location and any time as the target time, the initial deformation degree of the target detection location at the target time is obtained based on the deflection and vibration frequency data of the target detection location at the target time. The wind force influence degree of the target detection location at the target time is obtained based on the wind speed and wind pressure data of the target detection location at the target time and the corresponding sequence number value. Based on the wind force influence degree, the initial deformation degree is adjusted to obtain the adjusted deformation degree of the target detection location at the target time. Based on the fluctuation of the degree of adjustment deformation at the target detection location at each time and the overall level of deflection data at all times, the damage characteristic value of the target detection location is obtained; based on the difference of the damage characteristic value of each detection location in the preset neighborhood of the target detection location and the damage characteristic value of the target detection location, the damage probability of the target detection location is obtained. Based on the probability of damage at each detection location, load-bearing damage at different locations of the bridge is detected; Obtaining the initial deformation degree of the target detection location at the target time includes: performing a negative correlation mapping on the elastic modulus of the bridge material to obtain the bridge's deformation coefficient; combining the bridge's length and the deformation coefficient to obtain the bridge's deflection influence weight; using the product of the deflection influence weight and the deflection data of the target detection location at the target time as the first deformation parameter of the target detection location at the target time; using the absolute value of the difference between the vibration frequency data of the target detection location at the target time and the bridge's natural vibration frequency as the second deformation parameter of the target detection location at the target time; and combining the first deformation parameter and the second deformation parameter to obtain the initial deformation degree of the target detection location at the target time. Obtaining the wind force influence of the target detection location at the target time includes: using the wind-receiving area of ​​the integrated sensor at the target detection location as the numerator, the surface roughness of the integrated sensor at the target detection location as the denominator, and using the ratio as the drag coefficient of the integrated sensor at the target detection location; combining the wind speed data, the wind pressure data, and the drag coefficient of the integrated sensor at the target detection location at the target time to obtain the wind force effect coefficient of the target detection location at the target time; and adjusting the wind force effect coefficient of the target detection location at the target time according to the sequence value corresponding to the target time to obtain the wind force influence of the target detection location at the target time. Based on the sequence value corresponding to the target time, the wind force coefficient of the target detection location at the target time is adjusted to obtain the degree of wind force influence of the target detection location at the target time. This includes: using the sequence value corresponding to the target time as the numerator, the cumulative value of the sequence values ​​corresponding to all times as the denominator, and using the ratio as the cumulative weight of wind force at the target time; and normalizing the product of the cumulative weight of wind force at the target time and the wind force coefficient of the target detection location at the target time to obtain the degree of wind force influence of the target detection location at the target time. Obtaining the degree of adjustment deformation of the target detection position at the target time includes: taking the product of the wind influence degree and the initial deformation degree of the target detection position at the target time as the adjustment amount of the deformation degree of the target detection position at the target time; and taking the difference between the initial deformation degree and the adjustment amount of the deformation degree of the target detection position at the target time as the degree of adjustment deformation of the target detection position at the target time.

2. The bridge load-bearing damage detection method based on deflection monitoring according to claim 1, characterized in that, The damage feature values ​​obtained at the target detection location include: The degree of dispersion of the adjustment deformation at the target detection position at all times is analyzed to obtain the degree of deformation fluctuation at the target detection position. The average value of the deflection data at all times at the target detection location is taken as the overall deflection value at the target detection location; By combining the degree of deformation fluctuation and the overall deflection value, the damage characteristic value of the target detection location is obtained.

3. The bridge load-bearing damage detection method based on deflection monitoring according to claim 1, characterized in that, The probability of damage at the target detection location includes: In the target detection location and the preset neighborhood, other detection locations besides the target detection location are used as reference detection locations; Based on the difference in damage feature values ​​between the target detection location and each reference detection location, a first damage coefficient for the target detection location is obtained; The difference between the damage feature value at the target detection location and the minimum damage feature value at all detection locations is used as the second damage coefficient of the target detection location. The first damage coefficient and the second damage coefficient are combined and normalized to obtain the damage probability at the target detection location.

4. The bridge load-bearing damage detection method based on deflection monitoring according to claim 3, characterized in that, The first damage coefficient for obtaining the target detection location includes: The damage feature value at the target detection location is used as the numerator, and the damage feature value at each reference detection location is used as the denominator. The ratio is used as the relative deformation difference value between the target detection location and each reference detection location. The average of the relative deformation differences between the target detection location and all reference detection locations is used as the first damage coefficient for the target detection location.

5. The bridge load-bearing damage detection method based on deflection monitoring according to claim 1, characterized in that, The detection of load-bearing damage at different locations on the bridge includes: The detection locations where the probability of damage is greater than a preset probability threshold are taken as the load-bearing damage locations of the bridge.

6. A bridge load-bearing damage detection system based on deflection monitoring, the system comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.

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