Deflection detection method, device and system for road bridge

Abstract

The invention relates to the technical field of mechanical property testing, in particular to a deflection detection method, device and system for a road bridge, and the method comprises the steps: obtaining initial deformation data and environment data of a target position of a to-be-detected road bridge; fitting the initial deformation data of each target position at each moment under the environment data to obtain a fitted deformation curve; determining the relative positioning difference of the target position under the environment data at each moment; determining a reference weight of each relative positioning difference; determining an influence positioning error of the target position under the environment data according to the relative positioning difference of the target position under the environment data and the reference weight of each relative positioning difference; and correcting the initial deformation data of the target position under the environment data by using the influence positioning error to obtain corrected deformation data of the target position, and taking the corrected deformation data as the deflection of the road bridge. Therefore, the detection accuracy of the deflection condition of each part of the road bridge is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of mechanical property testing, and particularly relates to a deflection detection method, device and system for road bridges. Background Art

[0002] As a key component of transportation infrastructure, the safety of road bridges is directly related to the smoothness of transportation and the safety of public life and property. The safety inspection of road bridges is an important means to ensure the structural safety and functional integrity of road bridges during long-term use. Among the many indicators for road bridge safety inspection, road bridge deflection is one of the key parameters for measuring the health status of road bridges. Road bridge deflection refers to the degree of deformation of a road bridge under the action of a load. Once the deflection is too large, it often indicates that the structure of the road bridge may have been damaged or is about to malfunction, which will lead to a decrease in the load-bearing capacity of the road bridge and a shortening of its service life. Therefore, in order to effectively ensure the safety of road bridges and prevent potential risks, it is particularly important to regularly and accurately detect the deflection of road bridges.

[0003] In some scenarios, fiber optic sensor technology is often used to detect the deflection of road bridges. Fiber optic sensors, with their extremely high sensitivity, can capture subtle deformation information of road bridges. However, due to the fact that the optical properties of the internal materials of fiber optic sensors are extremely susceptible to the influence of the external environment, and the environmental conditions at different positions of road bridges, such as temperature and humidity, vary significantly, the fiber optic sensors distributed at various locations on the road bridge are subject to different environmental interferences. The deformation conditions detected by the fiber optic sensors are actually the combined result of the deformation of the road bridge itself and the influence of environmental temperature and humidity on the optical properties of the fiber optic sensors. Among them, the bending deformation of the road bridge changes with the change of the load on the road bridge. Under the condition of determined temperature and humidity, the influence of the environment on the optical properties of the fiber optic sensors is relatively stable. However, due to the inconsistent temperature and humidity at various locations on the road bridge, the bending conditions of the road bridge detected by the fiber optic sensors are deviated, ultimately resulting in the inability to accurately detect the deflection conditions at various locations on the road bridge, affecting the assessment of the true health status of the road bridge. Summary of the Invention

[0004] In order to solve the technical problem of low detection accuracy of the deflection conditions at various locations on road bridges, the purpose of the present invention is to provide a deflection detection method, device and system for road bridges.

[0005] The specific technical solutions adopted to solve the above technical problems are as follows: An embodiment of the present invention provides a method for detecting the deflection of a road bridge, including: obtaining the initial deformation data and environmental data of the target position of the road bridge to be detected; fitting the initial deformation data at each target position at each moment under the environmental data to obtain a fitted deformation curve; determining the relative positioning difference of the target position at each moment under the environmental data according to the initial deformation data at each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position on the fitted deformation curve at each moment; determining the reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data at each target position at each moment under the corresponding environmental data; determining the influence positioning error of the target position under the environmental data according to the relative positioning difference of the target position under each environmental data and the reference weight of each relative positioning difference; using the influence positioning error to correct the initial deformation data of the target position under the environmental data to obtain the corrected deformation data of the target position, and taking the corrected deformation data as the deflection of the road bridge.

[0006] Optionally, determining the relative positioning difference of the target position at each moment under the environmental data according to the initial deformation data at each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position on the fitted deformation curve at each moment includes: calculating the first difference between the initial deformation data and the theoretical value of the deformation of the road bridge as the relative positioning difference.

[0007] Optionally, determining the reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data at each target position at each moment under the corresponding environmental data includes: determining the fitting confidence of the fitted deformation curve according to the relative positioning difference; determining the detection accuracy of the initial deformation data of the target position at each moment according to the initial deformation data of the target position at each moment and the average deformation data of the initial deformation data of other positions adjacent to the target position at each moment; determining the weighted average value of each relative positioning difference according to the relative positioning difference, fitting confidence, and detection accuracy of the target position at each moment under each environmental data; determining the standard deviation of each relative positioning difference of the target position under the environmental data by using the relative positioning difference, weighted average value, and the total number of times of the same environmental data of the target position at each moment under each environmental data; determining the reference weight of each relative positioning difference according to the standard deviation and the weighted average value of each relative positioning difference.

[0008] Optionally, determining the fitting confidence of the fitted deformation curve according to the relative positioning difference includes: performing inverse proportional normalization processing on each relative positioning difference to obtain a first normalized value; superimposing the first normalized values to obtain the fitting confidence of the fitted deformation curve.

[0009] Optionally, determining the detection accuracy of the initial deformation data of the target position at each moment based on the initial deformation data of the target position at each moment and the average deformation data of the initial deformation data of other positions adjacent to the target position includes: calculating the absolute value of the second difference between the initial deformation data and the average deformation data, and performing inverse proportional normalization processing on the absolute value of the second difference to obtain the detection accuracy.

[0010] Optionally, determining the weighted average of each relative positioning difference based on the relative positioning differences of the target position at each moment under each environmental data, the fitting confidence, and the detection accuracy includes: Calculating the first product between the relative positioning difference, the fitting confidence, and the detection accuracy, and superimposing each first product to obtain a first superimposed value; calculating the second product between the fitting confidence and the detection accuracy, and superimposing each second product to obtain a second superimposed value; determining the first ratio between the first superimposed value and the second superimposed value as the weighted average.

[0011] Optionally, determining the influencing positioning error of the target position under the environmental data based on the relative positioning differences of the target position under each environmental data and the reference weights of each relative positioning difference includes: calculating the third product between the relative positioning difference and the reference weights of each relative positioning difference, and superimposing each third product to obtain a third superimposed value; calculating the fourth superimposed value of the reference weights of each relative positioning difference; determining the second ratio between the third superimposed value and the fourth superimposed value as the influencing positioning error.

[0012] Optionally, correcting the initial deformation data of the target position under the environmental data using the influencing positioning error to obtain the corrected deformation data of the target position includes: determining the third difference between the initial deformation data and the influencing positioning error as the corrected deformation data of the target position.

[0013] Second aspect, an embodiment of the present invention provides a deflection detection device for a road bridge, including: an acquisition module, configured to acquire initial deformation data and environmental data of a target position of a road bridge to be detected; a fitting module, configured to fit the initial deformation data of each target position at each moment under the environmental data to obtain a fitted deformation curve; a determination module, configured to determine the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position at each moment on the fitted deformation curve; the determination module is further configured to determine the reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data of each target position at each moment under the corresponding environmental data; the determination module is further configured to determine the influence positioning error of the target position under the environmental data according to the relative positioning difference of the target position under each environmental data and the reference weight of each relative positioning difference; a correction module, configured to correct the initial deformation data of the target position under the environmental data by using the influence positioning error to obtain the corrected deformation data of the target position, and use the corrected deformation data as the deflection of the road bridge.

[0014] Third aspect, an embodiment of the present invention provides a deflection detection system for a road bridge, including: a processor and a memory; wherein, the memory is used to store a computer program that can run on the processor; the processor is configured to execute the program stored on the memory to implement the steps of the deflection detection method for a road bridge as mentioned in the first aspect.

[0015] The present invention has the following beneficial effects: First, acquire the initial deformation data and environmental data of the target position of the road bridge to be detected; and fit the initial deformation data of each target position at each moment under the environmental data to obtain a fitted deformation curve; then determine the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position at each moment on the fitted deformation curve; and determine the reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data of each target position at each moment under the corresponding environmental data; secondly, determine the influence positioning error of the target position under the environmental data according to the relative positioning difference of the target position under each environmental data and the reference weight of each relative positioning difference; finally, correct the initial deformation data of the target position under the environmental data by using the influence positioning error to obtain the corrected deformation data of the target position, and use the corrected deformation data as the deflection of the road bridge.

[0016] Thus, the embodiments of the present invention can determine the influence positioning errors at various positions on the road bridge by combining the initial deformation data and environmental data at each position of the road bridge, and correct the initial deformation data at various positions on the road bridge under different environments based on the influence positioning errors, so as to obtain the corrected deformation data at various positions on the road bridge, that is, the deflection of the road bridge. Therefore, the embodiments of the present invention correct the bending condition of the road bridge detected by the fiber optic sensor in combination with the environmental conditions at each position of the road bridge, and finally improve the detection accuracy of the deflection conditions at various parts of the road bridge, and more accurately realize the assessment of the true health condition of the road bridge. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0018] Figure 1 It is a flowchart of a method for detecting the deflection of a road bridge provided by an embodiment of the present invention; Figure 2 It is a schematic structural diagram of a device for detecting the deflection of a road bridge provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the intended invention purpose, the following will, in conjunction with the accompanying drawings and preferred embodiments, detail the specific implementation manners, structures, features, and effects of a method, device, and system for detecting the deflection of a road bridge proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. In addition, the specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0021] The following will specifically describe the specific solution of a method for detecting the deflection of a road bridge provided by the present invention with reference to the accompanying drawings.

[0022] Embodiment 1: Please refer to Figure 1 , which shows a flowchart of a method for detecting the deflection of a road bridge provided by an embodiment of the present invention, including: Step S101, obtain the initial deformation data and environmental data of the target position of the road bridge to be detected.

[0023] Specifically, in the embodiments of the present invention, at key positions under the road bridge, such as at intervals at the bottom and top of the road bridge, optical fiber sensors are arranged to detect the deformation of the corresponding positions of the road bridge. Among them, the distance can be set to 0.5 meters, and the optical fiber sensor can use a fiber Bragg grating sensor.

[0024] Furthermore, temperature sensors and humidity sensors are installed at the same positions to detect the environmental data at the corresponding positions. The environmental data includes, but is not limited to, temperature data and humidity data, as environmental identifiers for correcting the deformation data of the road bridge.

[0025] Furthermore, the embodiments of the present invention preset the detection frequency to 1 time / second, and preset to collect deformation data, temperature data, humidity data, etc. in the past month.

[0026] Furthermore, when the road bridge is subjected to a load, it will bend to a certain extent. Since most road bridges are integral, the load of the road bridge will be evenly distributed throughout the road bridge, or evenly distributed within a certain area. This makes the bending changes of the road bridge continuous at several adjacent detection points on the road bridge. During detection, due to the influence of the environment on the optical fiber sensor, the deformation information detected by it is inaccurate. It is actually the combined effect of the real deformation and the environmental influence. However, since the influence of the environment on the optical fiber sensor is also relatively stable, the magnitude of this interference can be determined by the interference of temperature on the sensor detection data under the same deformation situation in history, and then the detected deformation information can be corrected accordingly.

[0027] Furthermore, because the bending change of the road bridge is slow, and the changes in temperature and humidity in the environment do not change suddenly, no matter how the sensor is affected, its detection data will not show a sudden change. Accordingly, through the neighborhood period of the target moment, the deformation data detected at the target moment is smoothed by the deformation data detected within the neighborhood period to obtain the initial deformation data In the above formula, represents the deformation data detected by the optical fiber sensor at the th moment within the neighborhood period , where is centered on the target moment and takes the time period a period with a radius. The value can be 2 seconds. Thus, the initial deformation data at various positions of the road bridge at numerous moments can be obtained.

[0028] Step S102: Fit the initial deformation data at each target position at each moment under the environmental data to obtain a fitted deformation curve.

[0029] Specifically, since both ends of the road bridge are fixed on the support columns, when there is a load on it, a bending moment will be formed, causing the entire road bridge to disperse the load and then form a bend in the road bridge. This results in a relatively smooth curve for the road bridge. Therefore, first construct a fitted deformation curve of the road bridge based on the initial deformation data at each position of the road bridge at each moment. In the embodiment of the present invention, it is preset to use the least squares method to fit the fitted deformation curves at each moment, and at the same time obtain the road bridge bending values at each position on the fitted deformation curve, which are recorded as the theoretical values of the road bridge deformation at each position.

[0030] Step S103: Determine the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the road bridge deformation at each target position on the fitted deformation curve at each moment.

[0031] Specifically, taking a position on a road bridge as an example in the embodiment of the present invention, although the fitted deformation curve of the road bridge at the corresponding moment can be obtained by the least squares method, when the fiber optic sensor is working, it will be affected by environmental factors and other factors, which makes the initial deformation data of the road bridge detected by it different from the actual road bridge deformation data. Therefore, first calculate the relative positioning difference of the target position under the environmental data of where is the temperature data at the moment of is the humidity data at the moment of and is the environmental data at the moment of and is the environmental data at the moment of and

[0032] Further, as an optional embodiment of the present invention, determining the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the road bridge deformation at each target position on the fitted deformation curve at each moment includes: calculating the first difference between the initial deformation data and the theoretical value of the road bridge deformation as the relative positioning difference.

[0033] In the above formula, represents the target position at the time when the environmental data is the relative positioning difference. represents the target position at the time when the environmental data is the initial deformation data, where the environmental data also refers to the environmental data at the time when. represents the theoretical value of the deformation of the road and bridge at the target position at the time when.

[0034] Step S104, determine the reference weight of each of the relative positioning differences according to the relative positioning differences and the initial deformation data of each of the target positions at each moment under the corresponding environmental data.

[0035] Specifically, since the change of the environment is slow and the environment of adjacent positions is relatively consistent, the interference brought by it is approximately the same. Similarly, the bending of the road and bridge changes with the change of the load on it, but due to the rigidity of the road and bridge materials, the load at each part of the road and bridge also changes slowly, resulting in similar bending deformation conditions at adjacent positions. This leads to similar deformation data detected at several adjacent positions. In addition, in the above embodiments of the present invention, the bending situation of the road and bridge at each moment is fitted to obtain the corresponding fitted deformation curve. However, the closer the numerous reference data points on the fitted deformation curve are to the fitted curve, the more accurate the curve fitting is and the more the numerous reference data points on it conform to the fitted deformation curve.

[0036] Further, as an optional embodiment of the present invention, determining the reference weights of the relative positioning differences based on the relative positioning differences and the initial deformation data of each of the target positions at each moment under the corresponding environmental data includes: determining the fitting confidence of the fitting deformation curve according to the relative positioning differences; determining the detection accuracy of the initial deformation data of each target position at each moment according to the average deformation data of the initial deformation data of each target position at each moment and the initial deformation data of other positions adjacent to the target position at each moment; determining the weighted average of the relative positioning differences according to the relative positioning differences, the fitting confidence, and the detection accuracy of the target position at each moment under each of the environmental data; using the relative positioning differences, the weighted average, and the total number of times of the same environmental data of the target position at each moment under each of the environmental data to determine the standard deviation of each of the relative positioning differences of the target position under the environmental data; and determining the reference weights of the relative positioning differences according to the standard deviation and the weighted average of the relative positioning differences.

[0037] Specifically, as an optional embodiment of the present invention, determining the fitting confidence of the fitting deformation curve according to the relative positioning differences includes: performing inverse proportional normalization processing on each of the relative positioning differences to obtain a first normalized value; and superimposing the first normalized values to obtain the fitting confidence of the fitting deformation curve.

[0038] Among them, the embodiment of the present invention specifically uses the following formula to calculate the fitting confidence of the fitting deformation curve: In the above formula, represents the fitting confidence of the fitting deformation curve . represents the target position The relative positioning difference of the sensor at when the environmental data is , that is, the relative positioning difference corresponding to the deformation data detected by the sensor at the target position at the moment . represents the total number of fiber optic sensors installed on the road bridge, that is, the number of target positions set on the road bridge. represents the inverse proportional normalization function, which is used to perform inverse proportional normalization processing on to describe the similarity between the initial deformation data detected at this sensor and the theoretical deformation data of the road bridge. Traverse all moments and calculate the fitting confidence of the fitting deformation curve obtained by fitting at each moment.

[0039] Further, as an optional embodiment of the present invention, determining the detection accuracy of the initial deformation data of the target position at each moment according to the initial deformation data of the target position at each moment and the average deformation data of the initial deformation data of other positions adjacent to the target position includes: calculating the absolute value of the second difference between the initial deformation data and the average deformation data, and performing inverse proportional normalization on the absolute value of the second difference to obtain the detection accuracy.

[0040] Specifically, since the environmental change is slow and the environment of adjacent positions is relatively consistent, the interference brought by it is approximately the same. Similarly, the bending of a road bridge changes with the change of the load on it. However, due to the rigidity of the road bridge material, the load at each part of the road bridge also changes slowly, resulting in similar bending deformation situations at adjacent positions. This leads to similar deformation data detected at several adjacent positions. Accordingly, the embodiments of the present invention use the following formula to calculate the target position of the road bridge at the target moment of the detection accuracy of the initial deformation data detected: In the above formula, represents the detection accuracy of the initial deformation data detected at the target position at the moment . represents at the moment the initial deformation data detected by the sensor at the target position . represents when the moment is the initial deformation data detected by the sensor at the target position and the average deformation data of the initial deformation data detected by several (such as 3) sensors around it. represents the inverse proportional normalization data, which is used to perform inverse proportional normalization on .

[0041] Further, through the above embodiments of the present invention, the fitting confidence degrees corresponding to each fitting deformation curve are analyzed, which can relatively explain the credibility of the theoretical deformation data of each sensor at this moment, that is, the more credible the theoretical deformation data is at each moment, the more credible the corresponding relative positioning difference is. Similarly, the more credible the actually detected deformation data is, the more credible the corresponding relative positioning difference is. Accordingly, a weighted average of many relative positioning differences is obtained by weighting them according to their credibility.

[0042] As an alternative embodiment of the present invention, determining the weighted average of each relative positioning difference according to the relative positioning differences of the target position at each moment when in each piece of the environmental data, the fitting confidence, and the detection accuracy includes: calculating the first product among the relative positioning difference, the fitting confidence, and the detection accuracy, and superimposing each first product to obtain a first superimposed value; calculating the second product between the fitting confidence and the detection accuracy, and superimposing each second product to obtain a second superimposed value; determining that the first ratio between the first superimposed value and the second superimposed value is the weighted average.

[0043] Specifically, the embodiment of the present invention specifically calculates the weighted average using the following formula: In the above formula, represents the weighted average of the relative positioning difference of the sensor at the target position when the environmental data at the th time is . represents the relative positioning difference of the sensor at the target position when the environmental data at the th time is . represents the fitting confidence of the fitting deformation curve corresponding to the environmental data at the th time being . represents the detection accuracy of the initial deformation data detected by the sensor at the target position when the environmental data at the th time is . represents the total number of times when the environmental data is .

[0044] Furthermore, the embodiment of the present invention specifically calculates the standard deviation of numerous relative positioning differences using the following formula: In the above formula, represents the standard deviation of the relative positioning difference of the sensor at the target position when the environmental data at the th time is . represents the relative positioning difference of the sensor at the target position when the environmental data at the th time is . represents the sensor at the target position when the environmental data at the th time is The weighted average of the relative positioning differences at that time. Indicates that the environmental data is The total number of times.

[0045] Furthermore, in the embodiments of the present invention, the following formula is specifically used to calculate the reference weight of the relative positioning difference: In the above formula, Indicates the target position When the environmental data is At the moment The reference weight of the relative positioning difference. Indicates the target sensor When the environmental data is At the moment The relative positioning difference. Indicates the target position The sensor at the location is at the th time when the environmental data is The weighted average of the relative positioning differences. Indicates the target position The sensor at the location is at the th time when the environmental data is The standard deviation of the relative positioning differences. Indicates the inverse proportional normalization function, which is used to Perform inverse proportional normalization processing.

[0046] Step S105: Determine the influence positioning error of the target position under the environmental data according to the relative positioning differences of the target position under each environmental data and the reference weights of each relative positioning difference.

[0047] Specifically, in the same environment, the interference received by the same sensor should be the same. Therefore, the magnitude of this interference is described by the central tendency of the interference detected at many past moments. Due to the differences between the detection data detected at different moments and the fitting deformation curve, the corresponding reference weights are different. Using these as weights, the relative positioning differences are weighted and averaged to obtain the influence positioning error of the corresponding position of the target position Under the target environment.

[0048] Further, as an optional embodiment of the present invention, determining the influence positioning error of the target position under the environmental data according to the relative positioning differences of the target position under each piece of environmental data and the reference weights of the relative positioning differences includes: calculating a third product between the relative positioning differences and the reference weights of the relative positioning differences, and superimposing the third products to obtain a third superimposed value; calculating a fourth superimposed value of the reference weights of the relative positioning differences; and determining a second ratio between the third superimposed value and the fourth superimposed value as the influence positioning error.

[0049] Specifically, the embodiment of the present invention specifically uses the following formula to calculate the influence positioning error: In the above formula, represents the influence positioning error of the sensor corresponding to the target position in the target environment at . represents the relative positioning difference of the sensor corresponding to the target position when the environmental data for the th time is the target environment . represents the reference weight of the relative positioning difference of the sensor corresponding to the target position when the environmental data for the th time is the target environment . represents the total number of times when the environmental data in the past time series is the target environment .

[0050] Step S106: Use the influence positioning error to correct the initial deformation data of the target position under the environmental data to obtain the corrected deformation data of the target position, and use the corrected deformation data as the deflection of the road bridge.

[0051] Specifically, the deformation data detected by the fiber optic sensor is composed of the actual deformation data of the road bridge and the environmental influence error. Accordingly, the embodiment of the present invention corrects the deformation data of the road bridge at the corresponding position.

[0052] Further, as an optional embodiment of the present invention, using the influence positioning error to correct the initial deformation data of the target position under the environmental data to obtain the corrected deformation data of the target position includes: determining a third difference between the initial deformation data and the influence positioning error as the corrected deformation data of the target position.

[0053] In the above formula, Indicate the location of the road bridge Calibrate the deformation data at this point. Indicate the location of the road bridge The initial deformation data detected by the fiber optic sensor at this point. Indicate the target location The influence positioning error of the corresponding sensor in the current environment.

[0054] Similarly, according to the above formula, the calibration compensation of the initial deformation data detected by the fiber optic sensors at various locations of the road bridge can be completed, and the calibrated deformation data at each location can be obtained.

[0055] It should be noted that for the fraction of the calculation formula described above in this embodiment, it is generally impossible for the denominator to be zero. If there is an extreme situation, a non-zero constant, such as 0.01, is added at the denominator position of the fraction.

[0056] Furthermore, the above has completed the deflection measurement at some locations of the road bridge. For the method of obtaining the deflection of other parts of the road bridge, the least squares method can be used to obtain the deflection curve and deflection curve equation of the road bridge at the current moment, and then the deflection values at other locations can be obtained according to the deflection curve equation.

[0057] The embodiment of the present invention can determine the influence positioning error at each position on the road bridge by combining the initial deformation data and environmental data at each position of the road bridge, and correct the initial deformation data at each position on the road bridge under different environments based on this influence positioning error, so as to obtain the calibrated deformation data at each position on the road bridge, that is, the deflection of the road bridge. Therefore, the embodiment of the present invention combines the environmental conditions at each position of the road bridge to perform environmental compensation on the bending condition of the road bridge detected by the fiber optic sensor, ultimately improving the detection accuracy of the deflection condition at each location of the road bridge and more accurately realizing the assessment of the true health condition of the road bridge.

[0058] Embodiment 2: Corresponding to the method for detecting the deflection of a road bridge provided in the above embodiment, based on the same technical concept, the embodiment of the present invention also provides a device for detecting the deflection of a road bridge. This device for detecting the deflection of a road bridge is used to execute the above method for detecting the deflection of a road bridge. Figure 2 This is a schematic structural diagram of a device for detecting the deflection of a road bridge provided in another embodiment of the present invention, as Figure 2As shown in the figure, the deflection detection device 200 for a road bridge includes: an acquisition module 201, configured to acquire initial deformation data and environmental data of a target position of the road bridge to be detected; a fitting module 202, configured to fit the initial deformation data of each target position at each moment under the environmental data to obtain a fitting deformation curve; a determination module 203, configured to determine the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position on the fitting deformation curve; the determination module 203 is further configured to determine a reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data of each target position at each moment under the corresponding environmental data; the determination module 203 is further configured to determine the influence positioning error of the target position under the environmental data according to the relative positioning difference of the target position under each environmental data and the reference weights of each relative positioning difference; a correction module 204, configured to correct the initial deformation data of the target position under the environmental data by using the influence positioning error to obtain corrected deformation data of the target position, and use the corrected deformation data as the deflection of the road bridge.

[0059] The embodiment of the present invention can determine the influence positioning error at each position on the road bridge by combining the initial deformation data and environmental data of each position on the road bridge, and correct the initial deformation data of each position on the road bridge under different environments based on the influence positioning error, so as to obtain the corrected deformation data of each position on the road bridge, that is, the deflection of the road bridge. Therefore, the embodiment of the present invention corrects the bending condition of the road bridge detected by the fiber optic sensor in combination with the environmental conditions of each position on the road bridge, and finally improves the detection accuracy of the deflection conditions at each place on the road bridge, and more accurately realizes the assessment of the true health condition of the road bridge.

[0060] Embodiment 3: Corresponding to the deflection detection method for a road bridge provided in the above embodiment, based on the same technical concept, the embodiment of the present invention further provides a deflection detection system for a road bridge, and the deflection detection system for a road bridge is used to execute the above deflection detection method for a road bridge.

[0061] Specifically, in this embodiment, the deflection detection system for a road bridge includes a processor, a communication interface, a memory, and a communication bus; wherein, the processor, the communication interface, and the memory complete communication with each other through the bus; the memory is used to store a computer program; the processor is used to execute the program stored on the memory to implement the above Figure 1Each step in the method embodiments, and having the beneficial effects of the above method embodiments, for the sake of avoiding repetition, the embodiments of the present invention will not be described in detail herein again.

[0062] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

[0063] The embodiments of the present invention also propose a computer-readable storage medium. The computer-readable medium stores one or more programs. When the one or more programs are executed by an electronic device including a plurality of application programs, the electronic device is caused to execute Figure 1 the methods disclosed in the illustrated embodiments and realize the functions and beneficial effects of the methods in the foregoing method embodiments, which will not be described in detail herein again.

[0064] Among them, the computer-readable storage medium includes read-only memory (ROM for short), random access memory (RAM for short), magnetic disk or optical disc, etc.

[0065] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A deflection detection method for road bridges, characterized in that, The deflection detection method for road bridges includes: Obtaining the initial deformation data and environmental data of the target positions of the road bridge to be detected; Fitting the initial deformation data of each target position at each moment under the environmental data to obtain a fitted deformation curve; Determining the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position on the fitted deformation curve; Determining the reference weights of the relative positioning differences according to the relative positioning differences and the initial deformation data of each target position at each moment under the corresponding environmental data; Determining the influence positioning error of the target position under the environmental data according to the relative positioning differences of the target position under each environmental data and the reference weights of the relative positioning differences; Using the influence positioning error to correct the initial deformation data of the target position under the environmental data to obtain the corrected deformation data of the target position, and taking the corrected deformation data as the deflection of the road bridge.

2. The deflection detection method for road bridges according to claim 1, characterized in that, The determining the relative positioning difference of each target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the deformation of the road bridge at each target position on the fitted deformation curve includes: Calculating the first difference between the initial deformation data and the theoretical value of the deformation of the road bridge as the relative positioning difference.

3. The deflection detection method for road bridges according to claim 1, characterized in that, The determining the reference weights of the relative positioning differences according to the relative positioning differences and the initial deformation data of each target position at each moment under the corresponding environmental data includes: Determining the fitting confidence of the fitted deformation curve according to the relative positioning difference; Determining the detection accuracy of the initial deformation data of each target position at each moment according to the initial deformation data of each target position at each moment and the average deformation data of the initial deformation data of other positions adjacent to the target position; Determining the weighted average value of the relative positioning differences according to the relative positioning differences of the target position at each moment under each environmental data, the fitting confidence, and the detection accuracy; Using the relative positioning differences of the target position at each moment under each environmental data, the weighted average value, and the total number of times of the same environmental data to determine the standard deviation of the relative positioning differences of the target position under the environmental data; Determining the reference weights of the relative positioning differences according to the standard deviation and the weighted average value of the relative positioning differences.

4. The deflection detection method for road bridges according to claim 3, characterized in that, The determining the fitting confidence of the fitted deformation curve according to the relative positioning difference includes: Performing inverse proportional normalization processing on each relative positioning difference to obtain a first normalized value; Superposing the first normalized values to obtain the fitting confidence of the fitted deformation curve.

5. The deflection detection method for road bridges according to claim 3, characterized in that, Determining the detection accuracy of the initial deformation data of the target position at each moment according to the initial deformation data of the target position at each moment and the average deformation data of the initial deformation data of other positions adjacent to the target position includes: Calculating the absolute value of the second difference between the initial deformation data and the average deformation data, and performing inverse proportional normalization processing on the absolute value of the second difference to obtain the detection accuracy.

6. The deflection detection method for road bridges according to claim 3, characterized in that, Determining the weighted average of the relative positioning differences according to the relative positioning differences of the target position at each moment under each piece of environmental data, the fitting confidence level, and the detection accuracy includes: Calculating the first product between the relative positioning difference, the fitting confidence level, and the detection accuracy, and superimposing each first product to obtain a first superimposed value; Calculating the second product between the fitting confidence level and the detection accuracy, and superimposing each second product to obtain a second superimposed value; Determining the first ratio between the first superimposed value and the second superimposed value as the weighted average.

7. The deflection detection method for road bridges according to claim 1, characterized in that, Determining the influence positioning error of the target position under the environmental data according to the relative positioning differences of the target position under each piece of environmental data and the reference weights of the relative positioning differences includes: Calculating the third product between the relative positioning difference and the reference weights of the relative positioning differences, and superimposing each third product to obtain a third superimposed value; Calculating the fourth superimposed value of the reference weights of the relative positioning differences; Determining the second ratio between the third superimposed value and the fourth superimposed value as the influence positioning error.

8. The deflection detection method for road bridges according to claim 1, characterized in that, Using the influence positioning error to correct the initial deformation data of the target position under the environmental data to obtain the corrected deformation data of the target position includes: Determining the third difference between the initial deformation data and the influence positioning error as the corrected deformation data of the target position.

9. A deflection detection device for road bridges, characterized in that, Including: An acquisition module for acquiring the initial deformation data and environmental data of the target position of the road and bridge to be detected; A fitting module for fitting the initial deformation data of each target position at each moment under the environmental data to obtain a fitted deformation curve; A determination module for determining the relative positioning difference of the target position at each moment under the environmental data according to the initial deformation data of each target position at each moment under the corresponding environmental data and the theoretical values of the road and bridge deformations of each target position on the fitted deformation curve; The determination module is further configured to determine the reference weight of each relative positioning difference according to the relative positioning difference and the initial deformation data of each target position at each moment under the corresponding environmental data; The determination module is further configured to determine the influence positioning error of the target position under the environmental data according to the relative positioning differences of the target position under each piece of environmental data and the reference weights of the relative positioning differences; A calibration module, configured to calibrate the initial deformation data of the target position under the environmental data by using the influence on the positioning error, so as to obtain the calibrated deformation data of the target position, and use the calibrated deformation data as the deflection of the road bridge.

10. A deflection detection system for road bridges, characterized in that, It includes: A processor and a memory; wherein, the memory is used to store a computer program that can run on the processor; The processor is configured to execute the program stored on the memory to implement the steps of the method for detecting the deflection of a road bridge according to any one of claims 1-8.

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