Roadbed settlement disease detection method and device based on optical fiber sensor

Abstract

The invention relates to the technical field of measurement calibration, in particular to a roadbed settlement disease detection method and device based on an optical fiber sensor, and the method comprises the steps: dividing different road regions, collecting the internal temperature of an optical fiber, the stress of the optical fiber, the environment humidity and the surface temperature of a roadbed; constructing the optical fiber internal temperature, the environment humidity and the roadbed surface temperature of the road area at the acquisition moment; determining a delay difference coefficient of the road area at the acquisition moment; determining the time lag of the road area at the acquisition time; and obtaining a detection result of roadbed settlement problem detection according to the roadbed surface temperature of the road area at the acquisition moment and the previous acquisition moments, and the time lag and the optical fiber stress of the road area at the target acquisition moment. Accurate temperature compensation can be carried out on the optical fiber sensor, and the accuracy of roadbed settlement detection is improved.

Description

Technical Field

[0001] This application relates to the field of measurement and calibration technology, specifically to a method and device for detecting roadbed settlement defects based on fiber optic sensors. Background Technology

[0002] Roadbed settlement refers to the phenomenon where the roadbed undergoes vertical compression deformation under the influence of factors such as its own weight, vehicle loads, groundwater, and geological conditions, leading to a decrease in road surface elevation. Essentially, it is a cumulative plastic deformation caused by insufficient soil density or strength. Fiber optic sensors can detect road structure settlement at an early stage, and the detection results are stable over the long term, unaffected by electromagnetic interference from high-voltage cables, lightning, vehicle-mounted radar, etc. However, fiber optic sensors are highly sensitive to temperature changes, requiring temperature compensation during roadbed settlement detection to improve the sensitivity and accuracy of monitoring.

[0003] Because temperature changes are affected by heat transfer efficiency, temperature compensation exhibits a certain time lag. Furthermore, the uneven distribution of density, humidity, and temperature fields in different areas of the roadbed leads to variations in heat transfer efficiency. These differences are amplified when settlement defects occur, causing asynchronous temperature compensation and further exacerbating the delay. Particularly in areas with extreme weather or large temperature fluctuations, this lag severely impacts the sensitivity and accuracy of roadbed settlement detection, leading to a decrease in the reliability of fiber optic sensor-based roadbed settlement detection results. Summary of the Invention

[0004] To address the aforementioned technical problems, this application provides a method and apparatus for detecting roadbed settlement defects based on fiber optic sensors. The specific technical solution adopted is as follows: In a first aspect, one embodiment of this application provides a method for detecting roadbed settlement defects based on fiber optic sensors, the method comprising the following steps: The road with structural defects to be detected is divided into different road areas. The internal temperature of the optical fiber, the stress of the optical fiber, the ambient humidity and the surface temperature of the roadbed are collected for each road area at different collection times. Any collection time is recorded as the target collection time, and the internal temperature of the optical fiber, the ambient humidity and the surface temperature of the roadbed of each road area at the target collection time are constructed. Based on the correlation between the fiber internal temperature sequence and the roadbed surface temperature sequence of the same road area and the ambient humidity sequence at the target acquisition time, the correlation between fiber internal temperature and ambient humidity and the correlation between roadbed surface temperature and ambient humidity of the same road area at the target acquisition time are determined respectively. Combining the difference between the correlation between the roadbed surface temperature sequence and the ambient humidity sequence of any one road area and all other road areas at the target acquisition time, the delay difference coefficient of the arbitrary road area at the target acquisition time is determined. Based on the delay difference coefficient between the road area and other road areas at all acquisition times before the target acquisition time, and the similarity between the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time, the time lag of each road area at each acquisition time is determined. Based on the roadbed surface temperature at the target acquisition time and at each acquisition time prior to the target acquisition time, the time lag of the road area at the target acquisition time, and the fiber stress, the detection results of the roadbed settlement problem are obtained.

[0005] Furthermore, the method for obtaining the correlation between the internal temperature and ambient humidity of the optical fiber is as follows: The correlation coefficient between the internal temperature sequence of the optical fiber and the ambient humidity sequence of the same road area at the target acquisition time is denoted as the internal temperature-ambient humidity correlation of the optical fiber in the same road area at the target acquisition time.

[0006] Furthermore, the method for obtaining the correlation between the roadbed surface temperature and ambient humidity is as follows: The correlation coefficient between the roadbed surface temperature sequence and the ambient humidity sequence of the same road area at the target acquisition time is denoted as the roadbed surface temperature-ambient humidity correlation of the same road area at the target acquisition time.

[0007] Furthermore, the method for obtaining the delay difference coefficient of any road area at the target acquisition time is as follows: Define any road area as the target road area; The mean of the absolute values ​​of the differences between the roadbed surface temperature and ambient humidity correlation between the target road area and all other road areas at the target data collection time is denoted as the first correlation difference of the target road area at the target data collection time. Determine the first summation relevance of the target road area at the target acquisition time; The ratio of the first correlation difference of the target road area at the target acquisition time to the first total correlation is denoted as the delay difference coefficient of the target road area at the target acquisition time.

[0008] Furthermore, the method for obtaining the first total relevance is as follows: The sum of the correlation between the roadbed surface temperature and ambient humidity of the target road area at the target acquisition time and the correlation between the internal temperature and ambient humidity of the optical fiber is denoted as the first sum correlation of the target road area at the target acquisition time.

[0009] Furthermore, the method for determining the time lag of each road area at each acquisition time based on the delay difference coefficient between the road area and other road areas at all acquisition times before the target acquisition time, and the similarity between the fiber optic internal temperature sequence and the roadbed surface temperature sequence of the same road area at the same acquisition time, includes the following specific methods: The acquisition time corresponding to the maximum value of the delay difference coefficient of all acquisition times before the target acquisition time in the target road area is recorded as the maximum delay difference time of the target road area at the target acquisition time. The difference in delay difference coefficient between the target road area and other road areas at the target acquisition time is used to determine the second ratio between the target road area and other road areas at the target acquisition time. Calculate the cross-correlation coefficients of the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time under different lag times. The lag time corresponding to the maximum value of all cross-correlation coefficients is recorded as the temperature delay of the same road area at the same acquisition time. Based on the time of maximum delay difference, the second ratio, and the temperature delay, the time lag of each road area at each data collection time is determined.

[0010] Furthermore, the method for obtaining the second ratio is as follows: The ratio of the delay difference coefficient between the target road area and other road areas at the target acquisition time is denoted as the first ratio between the target road area and other road areas at the target acquisition time. The absolute value of the difference between the first ratio between the target road area and other road areas at the target acquisition time and the number 1 is denoted as the first absolute value between the target road area and other road areas at the target acquisition time. The ratio of the first absolute value of the target road area to the first absolute value of the other road areas at the target acquisition time to the previous adjacent acquisition time is denoted as the second ratio of the target road area to the other road areas at the target acquisition time.

[0011] Furthermore, the formula for calculating the time lag is: in, Indicates the first Each road area at the time of data collection Time lag; This represents the rounding function; Indicates the first Each road area at the time of data collection Temperature delay; Indicates the first Each road area at the time of data collection The longitudinal lag coefficient; Indicates the first Each road area at the time of data collection The horizontal hysteresis coefficient; Indicates the first Each road area at the time of data collection The delay difference coefficient; Indicates the first Each road area at the time of data collection and collection time The maximum value of the delay difference coefficient across all previous acquisition times; Indicates the first Each road area at the time of data collection The time lag at the moment of maximum determined delay difference; Indicates the first The road area and the first Each road area at the time of data collection The second ratio, where ; Indicates the number of road zones; Indicates the first Each road area at the time of data collection Time lag; Indicates the first Each road area at the time of data collection The time lag.

[0012] Furthermore, the specific method for obtaining the detection results of roadbed settlement problem detection based on the roadbed surface temperature at the target acquisition time and at each acquisition time prior to the target acquisition time, the time lag of the road area at the target acquisition time, and the fiber stress includes: The road area is selected from the target acquisition time and the adjacent acquisition time before the target acquisition time, totaling a number of acquisition times with time lag, as the adjustment reference time of the road area. The average value of all roadbed surface temperatures at the adjustment reference time of the road area is recorded as the roadbed surface temperature adjustment value of the road area at the target acquisition time. Temperature compensation is performed on the fiber optic stress based on the adjusted surface temperature of the roadbed at the target acquisition time. Based on the temperature-compensated fiber optic stress, the results of the roadbed settlement detection at the target acquisition time are obtained.

[0013] Secondly, another embodiment of this application provides a roadbed settlement disease detection device based on fiber optic sensors, including 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 the steps of the above-described roadbed settlement disease detection method based on fiber optic sensors.

[0014] The embodiments of this application have at least the following beneficial effects: This application considers that fiber optic temperature sensors buried underground are affected by density and humidity, leading to a time lag in both the internal temperature of the fiber and its compensation. Given the varying correlations between the internal fiber temperature and ambient humidity in different road areas due to uneven roadbed or settlement, and the differences in these correlations across different road areas, this application evaluates the differences in heat transfer efficiency and temperature delay between the corresponding road area and other road areas by assessing the correlations between the internal fiber temperature sequence and roadbed surface temperature sequence of the same road area at the target acquisition time and the ambient humidity sequence, as well as the differences in the correlations between the road surface temperature sequence and the ambient humidity sequence of the road area and all other road areas at the target acquisition time. This allows for the determination of the time lag in temperature compensation for each road area at the target acquisition time. The delay difference coefficient at the target acquisition time is determined. Furthermore, based on the distribution characteristics of temperature delay at different acquisition times for the same road area, and the distribution characteristics of temperature delay at the same acquisition time for different road areas, the severity of temperature compensation delay in the internal temperature of the optical fiber acquired at the corresponding acquisition time for each road area is evaluated, and the time lag amount for each road area at each acquisition time is obtained. Finally, based on the roadbed surface temperature at the target acquisition time and at each acquisition time prior to the target acquisition time, the time lag amount for the road area at the target acquisition time, and the optical fiber stress, the detection results for roadbed settlement problems are obtained. This addresses the problem of insufficient reliability of roadbed settlement detection results due to the time lag of temperature compensation in optical fiber sensors, enabling more accurate temperature compensation for optical fiber sensors and improving the accuracy of roadbed settlement problem detection in road structural defects. Attached Figure Description

[0015] To more clearly illustrate the technical solutions and advantages in the embodiments of this application 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 A flowchart illustrating the steps of a roadbed settlement detection method based on fiber optic sensors, provided in one embodiment of this application; Figure 2 This is a flowchart illustrating the process of obtaining the delay difference coefficient according to one embodiment of this application. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by this application in order to achieve the intended purpose of the invention, the following detailed description, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features and effects of the roadbed settlement disease detection method and device based on fiber optic sensors proposed in this application.

[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 application pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the roadbed settlement detection method and device based on fiber optic sensors provided in this application.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a method for detecting roadbed settlement defects based on fiber optic sensors according to an embodiment of this application. The method includes the following steps: Step S001: Divide the road with structural defects to be detected into different road areas, collect the internal temperature of the optical fiber, optical fiber stress, ambient humidity and roadbed surface temperature of each road area at different collection times, record any collection time as the target collection time, and construct the internal temperature of the optical fiber, ambient humidity and roadbed surface temperature of each road area at the target collection time.

[0021] Fiber optic temperature sensors and fiber optic stress sensors are laid on the roadbed of the road to be inspected for structural defects. The fiber optic temperature sensors and fiber optic stress sensors should be laid in parallel. Simultaneously, humidity sensors and infrared temperature sensors are installed on the road to be inspected for structural defects. The fiber optic temperature sensors collect the internal temperature of the fiber optic cable, the fiber optic stress sensors collect the stress of the fiber optic cable, the humidity sensors collect the ambient humidity, and the infrared temperature sensors collect the surface temperature of the roadbed.

[0022] Because the roadbed materials in different areas of the road to be inspected may differ, in order to improve the accuracy of the roadbed settlement test results, the road to be inspected is divided into different road areas.

[0023] In this embodiment, the spatial resolution of the fiber optic temperature sensor is set to 0.2, and the spot size ratio of the infrared temperature sensor is set to 5:1. The length of the road area should be greater than or equal to 5 meters and less than or equal to 10 meters. In this embodiment, the length of each road area is set to 5 meters. If the remaining part of the road to be detected is less than the length of one road area, the remaining part is considered as one road area. In this embodiment, the acquisition time interval for the internal temperature of the fiber optic cable, fiber stress, ambient humidity, and roadbed surface temperature is set to 1 hour. The data of the internal temperature of the fiber optic cable, fiber stress, ambient humidity, and roadbed surface temperature are normalized to eliminate the influence of dimensions. Specifically, this embodiment uses the Z-Score standard normalization method to perform dimensionless processing on the internal temperature of the fiber optic cable, fiber stress, ambient humidity, and roadbed surface temperature. In practical applications, implementers can use other methods such as the existing maximum-minimum value normalization method for dimensionless processing. This is not limited here. Implementers can decide the acquisition time interval and the length of the road area according to the actual situation. This application does not impose any special restrictions.

[0024] Understandably, based on the spatial resolution of the fiber optic temperature sensor, the spot size ratio of the infrared temperature sensor, and the length of the road area, the number of fiber optic internal temperatures and roadbed surface temperatures collected at the same time can be calculated for each road area. However, only one fiber stress and one ambient humidity are collected for each road area at the same time.

[0025] Preferably, as an embodiment of this application, the average internal temperature of the optical fiber collected in the same road area at the same collection time is taken as the internal temperature of the optical fiber collected in the same road area at the same collection time, and the average surface temperature of the roadbed collected in the same road area at the same collection time is taken as the surface temperature of the roadbed collected in the same road area at the same collection time.

[0026] Record any acquisition time as the target acquisition time.

[0027] The same road area will be adjacent to each other at the time of target acquisition and before. The internal temperatures of the optical fibers at each acquisition time are arranged in the order of acquisition to obtain the internal temperature sequence of the optical fibers in the same road area at the target acquisition time; adjacent optical fiber internal temperatures in the same road area at the target acquisition time and before are then grouped together. The ambient humidity at each sampling time is arranged according to the order in which it was collected, thus obtaining the ambient humidity sequence of the same road area at the target sampling time; adjacent ambient humidity values ​​of the same road area at the target sampling time and before are then grouped together. The roadbed surface temperatures at each sampling time are arranged in the order in which they were collected to obtain the roadbed surface temperature sequence for the same road area at the target sampling time.

[0028] in, This represents the first preset threshold. In this embodiment, the value of the first preset threshold is 168, which means that the sequence is constructed based on the target acquisition time and the data collected in the previous week.

[0029] The same method can be used to obtain the fiber optic internal temperature sequence, ambient humidity sequence, and roadbed surface temperature sequence for each road area at each acquisition time.

[0030] It is important to understand that when there are insufficient adjacent acquisition times for the same road area before the target acquisition time... In this embodiment, the mean imputation method is used to fill in the missing data. The mean imputation method is a well-known technique and will not be described further. In practical applications, as other implementation methods, while achieving the goal of filling in missing data, implementers may use other existing methods such as median imputation, mode imputation, random sampling imputation, K-nearest neighbor imputation, and regression imputation to fill in the missing data. This application does not impose any special restrictions.

[0031] Thus, the internal temperature sequence of the optical fiber, the ambient humidity sequence, and the surface temperature sequence of the roadbed are obtained for each road area at each acquisition time.

[0032] Step S002: Based on the correlation between the fiber internal temperature sequence and the roadbed surface temperature sequence of the same road area at the target acquisition time and the ambient humidity sequence, respectively determine the correlation between fiber internal temperature and ambient humidity and the roadbed surface temperature and ambient humidity of the same road area at the target acquisition time. Combined with the difference between the correlation between the roadbed surface temperature sequence and the ambient humidity sequence of any one road area and all other road areas at the target acquisition time, determine the delay difference coefficient of the arbitrary road area at the target acquisition time.

[0033] However, since the fiber optic temperature sensor is buried underground, the internal temperature of the fiber optic cable collected by the fiber optic temperature sensor is determined by the heat transferred to the location of the fiber optic temperature sensor. The heat change caused by temperature is affected by density and humidity when it is transferred underground. Therefore, there is a certain time lag in the internal temperature of the fiber optic cable and the temperature compensation for the internal temperature of the fiber optic cable.

[0034] When the roadbed has high uniformity and no settlement occurs, the density and flatness of each road area are relatively consistent, and the humidity is similarly affected by the environment and road surface conditions. This results in similar heat transfer efficiency between each road area. At this time, the temperature change of the roadbed surface temperature affects the heat received by the roadbed. The temperature delay of the internal temperature of the optical fiber in each road area is consistent, and there is a high correlation between the internal temperature of the optical fiber and the surface temperature of the roadbed.

[0035] When the roadbed is uneven or has settled, the density varies in different road areas. Density affects heat transfer efficiency, leading to differences in the correlation between the internal temperature of the optical fiber and the surface temperature of the roadbed in different road areas. Simultaneously, density also alters the porosity of the road area, affecting its moisture absorption and causing differences in ambient humidity across different road areas. Furthermore, when roadbed settlement defects are found in the road surface under inspection, the ambient humidity at the settlement location will change significantly, causing differences in the correlation between the internal temperature of the optical fiber and ambient humidity in different road areas. Changes in ambient humidity also lead to variations in heat transfer efficiency between different road areas, resulting in different temperature delays in the internal temperature of the optical fiber in each area, further contributing to differences in the correlation between the internal temperature of the optical fiber and ambient humidity in different road areas.

[0036] Based on the correlation between the fiber optic internal temperature sequence and the roadbed surface temperature sequence and the ambient humidity sequence at the target acquisition time for the same road area, the correlation between fiber optic internal temperature and ambient humidity and the correlation between roadbed surface temperature and ambient humidity at the target acquisition time for the same road area are determined respectively.

[0037] Calculate the correlation coefficients between the fiber optic internal temperature sequence and the ambient humidity sequence for the same road area at the target acquisition time. Record the values ​​of these correlation coefficients as the correlation coefficients between the fiber optic internal temperature and ambient humidity for the same road area at the target acquisition time. Also calculate the correlation coefficients between the roadbed surface temperature sequence and the ambient humidity sequence for the same road area at the target acquisition time. Record the values ​​of these correlation coefficients as the correlation coefficients between the roadbed surface temperature and ambient humidity for the same road area at the target acquisition time.

[0038] Determine the delay difference coefficient of the target road area at the target acquisition time by taking any road area as the target road area and the difference between the roadbed surface temperature and ambient humidity of the target road area and all other road areas at the target acquisition time, as well as the correlation between the internal temperature and ambient humidity of the optical fiber of the target road area at the target acquisition time.

[0039] The mean of the absolute values ​​of the differences between the roadbed surface temperature and ambient humidity correlations of the target road area and all other road areas at the target acquisition time is denoted as the first correlation difference of the target road area at the target acquisition time. The sum of the roadbed surface temperature-ambient humidity correlation of the target road area at the target acquisition time and the correlation of fiber optic internal temperature-ambient humidity correlation is denoted as the first sum correlation of the target road area at the target acquisition time. The ratio of the first correlation difference of the target road area at the target acquisition time to the first sum correlation is denoted as the delay difference coefficient of the target road area at the target acquisition time.

[0040] In calculating the ratio of the first correlation difference to the first total correlation, a preset value is added to the denominator to avoid the denominator being zero. In this embodiment, the preset value is 3. This embodiment selects the Pearson correlation coefficient as the correlation coefficient between the two sequences. The calculation of the Pearson correlation coefficient is a well-known technique and will not be described in detail here. As another implementation method, based on achieving the purpose of measuring the correlation coefficient between two sequences, the implementer can use other methods in the prior art, such as cosine similarity or Spearman correlation coefficient, to obtain the correlation coefficient between the two sequences. This application does not impose any special restrictions.

[0041] The delay difference coefficient is used to evaluate the difference in heat conduction efficiency and temperature delay between the corresponding road area and other road areas. The greater the difference, the more severe the time lag in temperature compensation at the target acquisition time, and the more complex the road surface conditions at the target acquisition time, increasing the likelihood of uneven roadbed or settlement defects. The flowchart for obtaining the delay difference coefficient is shown below. Figure 2 As shown.

[0042] The delay difference coefficient for each road area at each acquisition time can be obtained using the same method.

[0043] At this point, the delay difference coefficients for all road areas at all acquisition times are obtained.

[0044] Step S003: Based on the delay difference coefficient between the road area and other road areas at all acquisition times before the target acquisition time, and the similarity between the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time, determine the time lag of each road area at each acquisition time.

[0045] In order to accurately adjust and compensate for the internal temperature of the optical fiber and reduce the different effects caused by different types of errors, it is necessary to continue to analyze the distribution characteristics of temperature delay at different acquisition times in the same road area.

[0046] When there is no roadbed settlement, although there are differences in heat transfer efficiency between different road areas, these differences remain relatively stable. However, when roadbed settlement occurs, it causes changes in the density and geometry of the road area, further affecting the differences in heat transfer efficiency between different road areas, leading to a gradual increase in these differences.

[0047] Based on the delay difference coefficients of the target road area and other road areas at all acquisition times before the target acquisition time, and the similarity of the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time, the maximum delay difference time of the target road area at the target acquisition time, the second ratio of the target road area and other road areas at the target acquisition time, and the temperature delay of the target road area at each acquisition time are determined respectively.

[0048] The acquisition time corresponding to the maximum value of the delay difference coefficient of all acquisition times before the target acquisition time in the target road area is recorded as the maximum delay difference time of the target road area at the target acquisition time.

[0049] The ratio of the delay difference coefficient between the target road area and other road areas at the target acquisition time is denoted as the first ratio between the target road area and other road areas at the target acquisition time. The absolute value of the difference between the first ratio between the target road area and other road areas at the target acquisition time and the number 1 is denoted as the first absolute value between the target road area and other road areas at the target acquisition time. The ratio of the first absolute value between the target road area and other road areas at the target acquisition time and the first absolute value of the previous adjacent acquisition time is denoted as the second ratio between the target road area and other road areas at the target acquisition time.

[0050] In one alternative implementation, when the first absolute value is zero, the second ratio can be determined as a preset value. For example, the preset value can be 0 or 1.

[0051] Calculate the cross-correlation coefficients of the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time under different lag times. The lag time corresponding to the maximum value of all cross-correlation coefficients is recorded as the temperature delay of the same road area at the same acquisition time.

[0052] Calculating the cross-correlation coefficient of two sequences under different time lags is a well-known technique and will not be elaborated further.

[0053] Based on the time of maximum delay difference, the second ratio, and the temperature delay, the time lag of each road area at each data collection time is determined.

[0054] in, Indicates the first Each road area at the time of data collection Time lag; This represents the rounding function, which rounds the value within parentheses to the nearest whole number. Indicates the first Each road area at the time of data collection Temperature delay; Indicates the first Each road area at the time of data collection The longitudinal lag coefficient; Indicates the first Each road area at the time of data collection The horizontal hysteresis coefficient; Indicates the first Each road area at the time of data collection The delay difference coefficient; Indicates the first Each road area at the time of data collection and collection time The maximum value of the delay difference coefficient across all previous acquisition times; Indicates the first Each road area at the time of data collection The time lag at the moment of maximum determined delay difference; Indicates the first The road area and the first Each road area at the time of data collection The second ratio, where ; Indicates the number of road zones; Indicates the first Each road area at the time of data collection Time lag; Indicates the first Each road area at the time of data collection The time lag.

[0055] In this embodiment, the time lag of each road area at the first data collection time is assigned a value of 1.

[0056] Understandably, the more complex the roadbed conditions in a road area, the more drastic the fluctuations in temperature delay, and the greater the corresponding error in temperature delay. Therefore, it is necessary to further evaluate the degree of time lag in the internal temperature of the optical fiber in the road area based on the longitudinal and lateral lag coefficients. The greater the time lag, the more severe the temperature compensation delay in the internal temperature of the optical fiber acquired at the corresponding acquisition time in the road area.

[0057] The same method can be used to obtain the time lag of each road area at each collection time.

[0058] At this point, the time lag of all road areas at all collection times has been obtained.

[0059] Step S004: Based on the roadbed surface temperature at the target acquisition time and at each acquisition time before the target acquisition time, the time lag of the road area at the target acquisition time, and the fiber stress, obtain the detection results of the roadbed settlement problem detection.

[0060] Based on the subgrade surface temperature of the target road area at the target acquisition time and at each acquisition time before the target acquisition time, and the time lag of the target road area at the target acquisition time, determine the adjustment value of the subgrade surface temperature of the road area at the target acquisition time.

[0061] Preferably, as an embodiment of this application, a total of a number of time lags between the target collection time and the time lag before the target collection time are selected as the adjustment reference time of the target road area. The average value of all roadbed surface temperatures at the adjustment reference time of the target road area is recorded as the adjusted value of the roadbed surface temperature of the target road area at the target collection time.

[0062] The dual-grating method is selected. The fiber stress is temperature compensated according to the adjustment value of the subgrade surface temperature of the target road area at the target acquisition time. The fiber stress of the target road area after temperature compensation at the target acquisition time is obtained. Based on the fiber stress after temperature compensation, the results of the subgrade settlement problem detection of the target road area at the target acquisition time are obtained.

[0063] The same method can be used to obtain the results of roadbed settlement detection for each road area at each collection time.

[0064] This embodiment uses a threshold monitoring method to detect roadbed settlement problems. The use of the dual-grating method for temperature compensation and the threshold monitoring method for roadbed settlement problem detection are both well-known technologies and will not be elaborated further. As other implementation methods, while achieving the goal of detecting roadbed settlement problems, implementers can use other methods in the prior art, such as trend analysis and Bragg grating methods, to obtain the results of roadbed settlement problem detection; this application does not impose any special limitations.

[0065] This completes the detection of road structure defects based on fiber optic sensors.

[0066] This application also proposes a roadbed settlement detection device based on fiber optic sensors, including 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 performs the steps described above. Since the method for detecting roadbed settlement based on fiber optic sensors has been described in detail above, it will not be repeated here.

[0067] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments of this specification have been described above. Additionally, the processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired results. In some implementations, multitasking and parallel processing are possible or may be advantageous.

[0068] 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.

[0069] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them; modifications to the technical solutions described in the foregoing embodiments, or equivalent substitutions of some of the technical features, do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for detecting roadbed settlement defects based on fiber optic sensors, characterized in that, The method includes the following steps: The road with structural defects to be detected is divided into different road areas. The internal temperature of the optical fiber, the stress of the optical fiber, the ambient humidity and the surface temperature of the roadbed are collected for each road area at different collection times. Any collection time is recorded as the target collection time, and the internal temperature of the optical fiber, the ambient humidity and the surface temperature of the roadbed of each road area at the target collection time are constructed. Based on the correlation between the fiber internal temperature sequence and the roadbed surface temperature sequence of the same road area and the ambient humidity sequence at the target acquisition time, the correlation between fiber internal temperature and ambient humidity and the correlation between roadbed surface temperature and ambient humidity of the same road area at the target acquisition time are determined respectively. Combining the difference between the correlation between the roadbed surface temperature sequence and the ambient humidity sequence of any one road area and all other road areas at the target acquisition time, the delay difference coefficient of the arbitrary road area at the target acquisition time is determined. Based on the delay difference coefficient between the road area and other road areas at all acquisition times before the target acquisition time, and the similarity between the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time, the time lag of each road area at each acquisition time is determined. Based on the roadbed surface temperature at the target acquisition time and at each acquisition time prior to the target acquisition time, the time lag of the road area at the target acquisition time, and the fiber stress, the detection results of the roadbed settlement problem are obtained.

2. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 1, characterized in that, The method for obtaining the correlation between the internal temperature and ambient humidity of the optical fiber is as follows: The correlation coefficient between the internal temperature sequence of the optical fiber and the ambient humidity sequence of the same road area at the target acquisition time is denoted as the internal temperature-ambient humidity correlation of the optical fiber in the same road area at the target acquisition time.

3. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 1, characterized in that, The method for obtaining the correlation between the roadbed surface temperature and ambient humidity is as follows: The correlation coefficient between the roadbed surface temperature sequence and the ambient humidity sequence of the same road area at the target acquisition time is denoted as the roadbed surface temperature-ambient humidity correlation of the same road area at the target acquisition time.

4. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 1, characterized in that, The method for obtaining the delay difference coefficient of any road area at the target acquisition time is as follows: Define any road area as the target road area; The mean of the absolute values ​​of the differences between the roadbed surface temperature and ambient humidity correlation between the target road area and all other road areas at the target data collection time is denoted as the first correlation difference of the target road area at the target data collection time. Determine the first summation relevance of the target road area at the target acquisition time; The ratio of the first correlation difference of the target road area at the target acquisition time to the first total correlation is denoted as the delay difference coefficient of the target road area at the target acquisition time.

5. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 4, characterized in that, The method for obtaining the first total relevance is as follows: The sum of the correlation between the roadbed surface temperature and ambient humidity of the target road area at the target acquisition time and the correlation between the internal temperature and ambient humidity of the optical fiber is denoted as the first sum correlation of the target road area at the target acquisition time.

6. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 4, characterized in that, The method for determining the time lag of each road area at each acquisition time based on the delay difference coefficient between the road area and other road areas at all acquisition times before the target acquisition time, and the similarity between the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time, includes the following specific methods: The acquisition time corresponding to the maximum value of the delay difference coefficient of all acquisition times before the target acquisition time in the target road area is recorded as the maximum delay difference time of the target road area at the target acquisition time. The difference in delay difference coefficient between the target road area and other road areas at the target acquisition time is used to determine the second ratio between the target road area and other road areas at the target acquisition time. Calculate the cross-correlation coefficients of the internal temperature sequence of the optical fiber and the surface temperature sequence of the roadbed in the same road area at the same acquisition time under different lag times. The lag time corresponding to the maximum value of all cross-correlation coefficients is recorded as the temperature delay of the same road area at the same acquisition time. Based on the time of maximum delay difference, the second ratio, and the temperature delay, the time lag of each road area at each data collection time is determined.

7. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 6, characterized in that, The method for obtaining the second ratio is as follows: The ratio of the delay difference coefficient between the target road area and other road areas at the target acquisition time is denoted as the first ratio between the target road area and other road areas at the target acquisition time. The absolute value of the difference between the first ratio between the target road area and other road areas at the target acquisition time and the number 1 is denoted as the first absolute value between the target road area and other road areas at the target acquisition time. The ratio of the first absolute value of the target road area to the first absolute value of the other road areas at the target acquisition time to the previous adjacent acquisition time is denoted as the second ratio of the target road area to the other road areas at the target acquisition time.

8. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 7, characterized in that, The formula for calculating the time lag is: in, Indicates the first Each road area at the time of data collection Time lag; This represents the rounding function; Indicates the first Each road area at the time of data collection Temperature delay; Indicates the first Each road area at the time of data collection The longitudinal lag coefficient; Indicates the first Each road area at the time of data collection The horizontal hysteresis coefficient; Indicates the first Each road area at the time of data collection The delay difference coefficient; Indicates the first Each road area at the time of data collection and collection time The maximum value of the delay difference coefficient across all previous acquisition times; Indicates the first Each road area at the time of data collection The time lag at the moment of maximum determined delay difference; Indicates the first The road area and the first Each road area at the time of data collection The second ratio, where ; Indicates the number of road zones; Indicates the first Each road area at the time of data collection Time lag; Indicates the first Each road area at the time of data collection The time lag.

9. The method for detecting roadbed settlement defects based on fiber optic sensors according to claim 1, characterized in that, The method for obtaining the detection results of roadbed settlement problem detection based on the roadbed surface temperature at the target acquisition time and at each acquisition time before the target acquisition time, the time lag of the road area at the target acquisition time, and the fiber stress includes the following specific methods: The road area is selected from the target acquisition time and the adjacent acquisition time before the target acquisition time, totaling a number of acquisition times with time lag, as the adjustment reference time of the road area. The average value of all roadbed surface temperatures at the adjustment reference time of the road area is recorded as the roadbed surface temperature adjustment value of the road area at the target acquisition time. Temperature compensation is performed on the fiber optic stress based on the adjusted surface temperature of the roadbed at the target acquisition time. Based on the temperature-compensated fiber optic stress, the results of the roadbed settlement detection at the target acquisition time are obtained.

10. A roadbed settlement detection device based on fiber optic sensors, 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 roadbed settlement disease detection method based on fiber optic sensors as described in any one of claims 1 to 9.

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