Pavement compaction degree monitoring method and device based on FBG optical fiber and electronic equipment

Abstract

The application discloses a FBG optical fiber-based road surface compactness monitoring method and device and electronic equipment. The method studies the compactness of a road surface test piece and the wavelength of the FBG optical fiber buried in the road surface test piece, and finds that the compactness of the road surface and the wavelength have a certain functional relationship. Therefore, based on the functional relationship between the compactness of the road surface and the wavelength, the compactness of the road surface is monitored in real time according to the wavelength of the FBG optical fiber buried in the road surface. In addition, the relationship between the compactness and the wavelength obtained through the road surface test piece experiment can effectively guarantee the accuracy of the compactness of the road surface.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of compaction monitoring, in particular to a road surface compaction monitoring method and device based on FBG optical fiber and electronic equipment. BACKGROUND

[0002] Compaction is a very important process in road construction, which has a great influence on the performance of asphalt pavement. For the design of composite construction standards or high-performance materials, improper compaction of asphalt mixture, such as insufficient compaction or excessive compaction, will damage the pavement performance and easily cause some pavement diseases, such as rutting, water seepage, and cracks on the asphalt pavement with insufficient compaction. Only when the asphalt pavement is fully compacted, can the strength, stiffness and flatness of the pavement be ensured, the service life of the roadbed and pavement can be ensured and prolonged, and the waste of funds can be reduced.

[0003] The existing asphalt pavement compaction detection mainly adopts core sampling, nuclear density detection technology or pavement radar detection technology, the former of which will damage the pavement and induce pavement diseases; the latter of which generally has limited precision, cannot monitor continuous pavement strain response and cannot monitor long-term continuous pavement internal response. In addition, these technologies cannot detect the compaction degree of the asphalt pavement structure during paving and rolling.

[0004] Therefore, there is a problem in the prior art that the compaction degree of the pavement cannot be monitored in real time. SUMMARY

[0005] Therefore, it is necessary to provide a road surface compaction monitoring method and device based on FBG optical fiber, electronic equipment and storage medium, to solve the problem that the prior art cannot monitor the compaction degree of the pavement in real time.

[0006] In order to solve the above problems, the present application provides a road surface compaction monitoring method based on FBG optical fiber, comprising:

[0007] Embedding the FBG optical fiber into a plurality of road surface test pieces, compacting the plurality of road surface test pieces, and determining a plurality of wavelength data of the FBG optical fiber;

[0008] Obtaining the compaction degree of the plurality of road surface test pieces, determining the functional relationship between the compaction degree and the wavelength through linear fitting according to the plurality of wavelength data;

[0009] Embedding the FBG optical fiber into the road surface to be measured, obtaining the wavelength data of the road surface to be measured, and determining the compaction degree of the road surface to be measured based on the relationship between the compaction degree and the wavelength.

[0010] Further, obtaining the compaction degree of the plurality of road surface test pieces, determining the functional relationship between the compaction degree and the wavelength through linear fitting according to the plurality of wavelength data, comprises:

[0011] According to the multiple sets of wavelength data, a plurality of sets of maximum wavelength variation values of the FBG optical fiber are determined;

[0012] According to the multiple sets of maximum wavelength variation values and the corresponding multiple degrees of compaction, a functional relationship between the degree of compaction and the maximum wavelength variation value is determined through linear fitting.

[0013] Further, according to the multiple sets of wavelength data, a plurality of sets of maximum wavelength variation values of the FBG optical fiber are determined, comprising:

[0014] According to the multiple sets of wavelength data, a plurality of sets of wavelength shifts of the FBG optical fiber are determined based on the photoelastic effect;

[0015] According to the multiple sets of wavelength shifts, a plurality of sets of center wavelengths of the FBG optical fiber are determined based on the relationship between the grating wavelength and the strain;

[0016] According to the multiple sets of center wavelengths, a plurality of sets of maximum wavelength variation values of the FBG optical fiber are determined.

[0017] Further, according to the multiple sets of maximum wavelength variation values and the corresponding multiple degrees of compaction, a functional relationship between the degree of compaction and the maximum wavelength variation value is determined through linear fitting, comprising:

[0018] A plurality of sets of number pairs of the degree of compaction and the corresponding multiple sets of maximum wavelength variation values are formed, and the multiple sets of number pairs are represented one by one in a coordinate system to obtain a curve of the degree of compaction and the maximum wavelength variation value;

[0019] The curve is corrected to determine the functional relationship between the degree of compaction and the maximum wavelength variation value.

[0020] Further, the FBG optical fiber is embedded in a plurality of pavement test pieces, and the plurality of pavement test pieces are compacted, comprising:

[0021] The pavement mixture is obtained;

[0022] The pavement mixture and the FBG optical fiber are arranged in a plurality of roadbed test pieces, and are rotationally compacted to obtain a plurality of pavement test pieces.

[0023] Further, the pavement mixture and the FBG optical fiber are arranged in a plurality of roadbed test pieces, comprising:

[0024] The pavement mixture is arranged in a plurality of roadbed test pieces;

[0025] The plurality of roadbed test pieces are respectively divided into an upper surface layer, a middle surface layer and a lower surface layer at a predetermined ratio;

[0026] The FBG optical fiber is embedded between the upper surface layer and the middle surface layer.

[0027] Further, the plurality of pavement test pieces are obtained by rotationally compacting, comprising:

[0028] The upper layer, the middle layer and the lower layer of the plurality of road test pieces are sequentially subjected to layered rotary compaction to obtain the plurality of road test pieces.

[0029] To solve the above problems, the application further provides a road compaction degree monitoring device based on FBG optical fiber, comprising:

[0030] A wavelength acquisition module is configured to bury the FBG optical fiber in the plurality of road test pieces, compact the plurality of road test pieces, and determine a plurality of sets of wavelength data of the FBG optical fiber.

[0031] A compaction degree and wavelength relationship determination module is configured to acquire the compaction degree of the plurality of road test pieces, and determine a functional relationship between the compaction degree and the wavelength by linear fitting based on the plurality of sets of wavelength data.

[0032] A compaction degree monitoring module is configured to bury the FBG optical fiber in a road to be measured, acquire wavelength data of the road to be measured, and determine the compaction degree of the road to be measured based on the relationship between the compaction degree and the wavelength.

[0033] To solve the above problems, the application further provides an electronic device comprising a processor and a memory, wherein the memory stores a computer program, and the computer program is executed by the processor to implement the road compaction degree monitoring method based on FBG optical fiber as described above.

[0034] To solve the above problems, the application further provides a storage medium storing computer program instructions, which, when executed by a computer, cause the computer to execute the road compaction degree monitoring method based on FBG optical fiber as described above.

[0035] The beneficial effects of the above technical solutions are as follows: the application provides a road compaction degree monitoring method, device and electronic device based on FBG optical fiber, which discovers a certain functional relationship between the compaction degree of the road and the wavelength by studying the compaction degree of the road test piece and the wavelength of the FBG optical fiber buried in the road test piece. Therefore, based on the functional relationship between the compaction degree of the road and the wavelength, the compaction degree of the road is monitored in real time according to the wavelength of the FBG optical fiber buried in the road. In addition, the relationship between the compaction degree and the wavelength obtained from the road test piece experiment can effectively ensure the accuracy of the compaction degree of the road. BRIEF DESCRIPTION OF DRAWINGS

[0036] Figure 1 A flowchart of an embodiment of the road compaction degree monitoring method based on FBG optical fiber provided by the application is shown in the figure.

[0037] Figure 2 A flowchart of an embodiment of the method for determining the relationship between the compaction degree and the wavelength provided by the application is shown in the figure.

[0038] Figure 3A flowchart of an embodiment of determining the maximum wavelength change value of the FBG optical fiber provided by the present application is shown in the figure;

[0039] Figure 4 A flowchart of an embodiment of determining the functional relationship between the compaction degree and the maximum wavelength change value provided by the present application is shown in the figure;

[0040] Figure 5 A structural diagram of the pavement compaction monitoring device based on the FBG optical fiber provided by the present application is shown in the figure.

[0041] Figure 6 A structural diagram of the pavement compaction monitoring device based on the FBG optical fiber provided by the present application is shown in the figure. DETAILED DESCRIPTION

[0042] The preferred embodiments of the present application will be described in detail below with reference to the accompanying drawings, which form a part of this application. The accompanying drawings together with the detailed description below are used to illustrate the principles of the present application, and are not intended to limit the scope of the present application.

[0043] Before the embodiments are described, the pavement, pavement compaction, are described:

[0044] The pavement is a layered structure made of various materials laid on the roadbed for vehicles to travel. Although the roadbed without pavement can also travel vehicles, it has poor ability to resist natural factors and vehicle load. When the sun is shining, dust flies, when it rains, it is muddy, and when vehicles travel, the surface will be rough, causing vehicles to vibrate, slip, travel at low speed, and even unable to travel, and oil and machine parts are severely damaged. After laying pavement, the road conditions are improved, so that vehicles can travel all day, and cars can travel on the road at a certain speed, safely, comfortably and economically.

[0045] The pavement is a major component of the highway, and its quality will directly affect the driving speed, safety and transportation cost. A well-built pavement on a high-grade highway can ensure that vehicles travel at high speed, safely and comfortably, and can save transportation costs to a greater extent, fully realizing the function of the high-grade highway.

[0046] Pavement compaction is a construction work that uses human or mechanical force to force the particles of the materials that make up the roadbed to be compressed and tightly packed, increasing the density of the roadbed. Compaction work can remove some air from the roadbed, increase the density, shear strength, reduce the compressibility, improve the impermeability and increase the uniformity of the roadbed. The compaction methods generally include rolling, ramming and vibration compaction.

[0047] Therefore, it is of great practical significance to monitor the compaction degree of the pavement. At present, the compaction degree of the asphalt pavement is mainly obtained by using core sampling, nuclear density detection technology or pavement radar detection technology, which cannot realize real-time monitoring of the pavement compaction degree.

[0048] In order to solve the problem in the prior art that it is impossible to monitor the road compaction in real time, the present invention provides a road compaction monitoring method, device and electronic equipment based on FBG optical fiber, which are described in detail below.

[0049] like Figure 1 As shown, Figure 1 The present invention provides a flow chart of an embodiment of a method for monitoring road compaction based on FBG optical fibers, including:

[0050] Step S101: burying the FBG optical fiber into a plurality of path test pieces, compacting the plurality of path test pieces, and determining a plurality of groups of wavelength data of the FBG optical fiber.

[0051] Step S102: Obtain the compaction degrees of a plurality of road test specimens, and determine the functional relationship between the compaction degrees and the wavelength through linear fitting based on the plurality of wavelength data sets.

[0052] Step S103: burying the FBG optical fiber in the road surface to be measured, obtaining wavelength data of the road surface to be measured, and determining the compaction degree of the road surface to be measured based on the relationship between the compaction degree and the wavelength.

[0053] In this embodiment, first, the wavelength data of the FBG optical fibers in multiple road test specimens and their corresponding compaction degrees are measured, and the relationship between the compaction degree and wavelength of the road test specimens is determined through linear fitting; then, the wavelength of the road surface to be tested is measured, and the compaction degree of the road surface to be tested is determined based on the relationship between the compaction degree and the wavelength.

[0054] It can be understood that the above embodiment realizes real-time acquisition of the wavelength of the FBG optical fiber by burying the FBG optical fiber in the road surface, and realizes real-time monitoring of the compaction of the road surface based on the inherent relationship between the compaction degree and the wavelength. Moreover, since the relationship between the compaction degree and the wavelength is obtained based on multiple road test specimen experiments, that is, the result is obtained through a large number of experiments, it can effectively ensure the accuracy of the compaction degree of the road surface.

[0055] As a preferred embodiment, in step S102, in order to determine the relationship between the compaction degree and the wavelength, as shown in FIG. Figure 2 As shown, Figure 2 A schematic flow chart of an embodiment of determining the relationship between compaction degree and wavelength provided by the present invention includes:

[0056] Step S121: determining multiple groups of maximum wavelength change values ​​of the FBG optical fiber according to the multiple groups of wavelength data.

[0057] Step S122: According to the multiple groups of maximum wavelength change values ​​and their corresponding multiple compaction degrees, a functional relationship between the compaction degree and the maximum wavelength change value is determined by linear fitting.

[0058] In the embodiment, first, according to the multiple sets of wavelength data monitored by the FBG optical fiber embedded in multiple pavement test pieces, the maximum wavelength change value of the FBG optical fiber is determined; then, multiple compaction degrees corresponding to the multiple sets of maximum wavelength change values are obtained, multiple data pairs are obtained, and function fitting is performed, and finally the function relationship between the compaction degree and the maximum wavelength change value is determined.

[0059] In the above embodiment, it is found through exploration that the maximum wavelength change value has a function relationship with the compaction degree, therefore, the maximum wavelength change value of the FBG optical fiber is obtained first; then, the relationship between the compaction degree and the maximum wavelength change value is functionized through function fitting, so as to facilitate subsequent real-time monitoring of the compaction degree, and the accuracy of the obtained compaction degree can be effectively ensured.

[0060] Further, in step S121, in order to determine the maximum wavelength change value of the FBG optical fiber, as shown in Figure 3 , Figure 3 The flowchart of the embodiment for determining the maximum wavelength change value of the FBG optical fiber provided by the application comprises:

[0061] Step S1211: According to the multiple sets of wavelength data, based on the photoelastic effect, multiple sets of wavelength drifts of the FBG optical fiber are determined.

[0062] Step S1212: According to the multiple sets of wavelength drifts, based on the relationship between the grating wavelength and the strain, multiple sets of center wavelengths of the FBG optical fiber are determined.

[0063] Step S1213: According to the multiple sets of center wavelengths, multiple sets of maximum wavelength change values of the FBG optical fiber are determined.

[0064] In a specific embodiment, the reflection and projection wavelength drift of the FBG optical fiber satisfies the formula of: eff

[0065] Δλ B =2n eff

[0066] When the sensor is deformed under the action of the load, the stretching or compression of the grating will cause the change of the grating period, and at the same time, the photoelastic effect will be caused, which will cause the change of the refractive index n eff , and further cause the wavelength drift. In the case of not considering the coupling effect of the temperature and the strain of the FBG, and not considering the temperature, the relationship between the Bragg wavelength and the strain is:

[0067]

[0068] Wherein, p 11 , p 12 is the photoelastic constant, v is the Poisson's ratio, and ε is the strain.

[0069] If:​

[0070]

[0071] α ε is the conversion coefficient between strain and wavelength, and the conversion relationship between single factor strain and central wavelength under constant temperature conditions is obtained as follows:

[0072] Δλ B =α ε ε

[0073] Since the conversion factor α ε It will directly affect the results of the sensor, so different sensors need to be calibrated with different coefficients.

[0074] Through the above embodiment, the central wavelength of the FBG fiber is determined by the photoelastic effect and the relationship between the grating wavelength and strain. The central wavelength of the FBG fiber includes an initial value and a maximum value. The difference between the maximum value and the initial value is the maximum wavelength change of the FBG fiber.

[0075] Furthermore, after determining the maximum wavelength change value of the FBG optical fiber, in order to determine the functional relationship between the compaction degree and the maximum wavelength change value, as shown in FIG. Figure 4 As shown, Figure 4 A flow chart of an embodiment of determining the functional relationship between the degree of compaction and the maximum wavelength change value provided by the present invention includes:

[0076] Step S1221: The compaction degree and its corresponding multiple groups of maximum wavelength change values ​​are grouped into multiple number pairs, and the multiple number pairs are represented one by one in the coordinate system to obtain a curve of the compaction degree and the maximum wavelength change value.

[0077] Step S1222: Correct the curve to determine the functional relationship between the degree of compaction and the maximum wavelength change value.

[0078] In this embodiment, multiple groups of number pairs consisting of multiple sets of compaction degrees and their corresponding multiple maximum wavelength change values ​​are represented in a coordinate system to obtain a scatter image of the compaction degree and the maximum wavelength change value; then, based on the scatter image, the corresponding curve of the compaction degree and the maximum wavelength change value is extracted; finally, due to errors and other reasons, the curve is corrected to obtain a more reasonable functional relationship between the compaction degree and the wavelength.

[0079] It can be understood that the above embodiment uses the function fitting method to express the relationship between compaction and wavelength through a functional relationship, thereby simplifying the relationship between compaction and wavelength and facilitating subsequent compaction monitoring based on the functional relationship.

[0080] In a specific embodiment, the functional relationship between the compaction degree and the wavelength is expressed as follows:

[0081] y = -0.0029x2+0.4581x-17.538

[0082] It is found by observation that the wavelength of the optical fiber after the specimen is formed is related to the compaction degree, and during the process of 90% to 100% of the compaction degree, the greater the compaction degree, the greater the maximum wavelength change value of the optical fiber, and the greater the strain of the specimen after the specimen is formed.

[0083] With the increase of the rotation number of the rotary compactor, the compaction degree gradually increases, and the increase of the compaction degree gradually slows down in the later stage, which shows that the result of real-time compaction monitoring of the asphalt mixture by the fiber Bragg grating strain sensor is consistent with the compaction degree change trend of the mixture in the later stage of rolling, and the fiber Bragg grating strain sensor can monitor the compaction degree of the asphalt mixture in real time, effectively and stably during the whole construction process.

[0084] As a preferred embodiment, different compaction methods have different effects on the compaction degree of the pavement, in order to obtain a compacted pavement specimen, in this embodiment, first, the pavement mixture is obtained; then, the pavement mixture and the FBG optical fiber are arranged in the pavement specimen, and the pavement specimen is rotated and compacted.

[0085] In a specific embodiment, the pavement specimen is a cylindrical specimen with a diameter of 150 mm and a height of 160 mm, and the density of the formed specimen meets the requirement of 100% ± 1 of the density of the Marshall standard compaction sample.

[0086] Considering that the fiber Bragg grating sensor is externally arranged on both sides of the specimen, and the measurement direction and position are consistent with the fiber Bragg grating sensor as much as possible, the ordinary mold has a through vertical groove with a width of 8 mm on both sides, which facilitates the embedding of the fiber Bragg grating sensor and the demolding of the specimen.

[0087] As a preferred embodiment, in order to standardize the position of the FBG optical fiber, the pavement specimen is divided into an upper layer, a middle layer and a lower layer in a preset ratio; and the FBG optical fiber is embedded between the upper layer and the middle layer.

[0088] In a specific embodiment, the preset ratio can be set to 1:2:1.

[0089] As a preferred embodiment, in order to ensure the uniformity of the pavement specimen and the quality of the pavement, the upper layer, the middle layer and the lower layer of the pavement specimen are sequentially and respectively subjected to layered rotary compaction.

[0090] In a specific embodiment, the pavement specimen is subjected to layered rotary compaction by a rotary compactor.

[0091] The rotating compaction instrument is an instrument for controlling or detecting mixture quality by measuring rotating shear, which is composed of displacement sensors, rotating encoders and the like; the built-in mold angle measurement can measure rotating shear for controlling or detecting mixture quality, is easy to compact and demold, and provides mixture compaction design software for facilitating test variable control.

[0092] In a specific embodiment, the raw materials of the middle and lower layers and the upper layer are consistent, and the specifications and test results are shown in the following table. The coarse aggregate is diabase and limestone produced by Zhongshan Aggregate Processing Factory, the fine aggregate is stone chips produced by Zhongshan Aggregate Processing Factory, and the asphalt is SBS modified asphalt. The test results of the performance of the aggregate and asphalt are shown in Tables 1, 2 and 3:

[0093] Table 1 Test results of coarse aggregate performance

[0094]

[0095] Table 2 Test results of fine aggregate performance

[0096] Experimental Project Measured value Technical requirements Apparent density 2.696 ≥2.5 Apparent relative density 2.702 / Sand equivalent 78 ≥60 Less than 0.075mm mass percentage (%) 7.5 ≤12.5

[0097] Table 3 Main technical indexes of SBS modified asphalt

[0098]

[0099] According to some embodiments of the present application, the aggregate used in the test piece meets the following grading range requirements as shown in Table 4. The asphalt and aggregate are mixed according to the T0702 method in JTG E20-2911:

[0100] Table 4 Aggregate grading requirements

[0101]

[0102] In a specific embodiment, the oil-stone ratio of the rubber asphalt mixture is 5.0%.

[0103] In the above manner, the relationship between the compaction degree and the wavelength is obtained, and the implementation monitoring of the road surface compaction degree is realized through the relationship between the compaction degree and the wavelength, effectively improving the monitoring efficiency of the road surface compaction degree and ensuring the monitoring accuracy.

[0104] In order to solve the above problems, the present application further provides a road surface compaction degree monitoring device based on an FBG optical fiber, as shown in Figure 5 Figure 5 ​A structural schematic diagram of the FBG optical fiber based road surface compactness monitoring device is provided in the present application, and the FBG optical fiber based road surface compactness monitoring device 500 comprises:

[0105] The wavelength acquisition module 501 is configured to bury the FBG optical fiber in a plurality of road surface test pieces, compact the plurality of road surface test pieces, and determine a plurality of sets of wavelength data of the FBG optical fiber.

[0106] The compactness and wavelength relationship determination module 502 is configured to acquire compactness of the plurality of road surface test pieces, and determine a function relationship between the compactness and the wavelength by linear fitting according to the plurality of sets of wavelength data.

[0107] The compactness monitoring module 503 is configured to bury the FBG optical fiber in a road surface to be measured, acquire wavelength data of the road surface to be measured, and determine compactness of the road surface to be measured based on the relationship between the compactness and the wavelength.

[0108] The present application also provides an electronic device, as shown in Figure 6 Figure 6 A structural block diagram of an embodiment of the electronic device provided in the present application is shown. The electronic device 600 can be a mobile terminal, a desktop computer, a notebook computer, a palm computer, a server, or the like. The electronic device 600 comprises a processor 601 and a memory 602, wherein the memory 602 stores a FBG optical fiber based road surface compactness monitoring program 603.

[0109] The memory 602 can be an internal storage unit of the computer device in some embodiments, such as a hard disk or a memory of the computer device. The memory 602 can also be an external storage device of the computer device in other embodiments, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, or the like. Further, the memory 602 can comprise both the internal storage unit and the external storage device of the computer device. The memory 602 is configured to store application software and various data installed in the computer device, such as program codes. The memory 602 can also be configured to temporarily store data that has been output or will be output. In an embodiment, the FBG optical fiber based road surface compactness monitoring program 603 can be executed by the processor 601, thereby realizing the FBG optical fiber based road surface compactness monitoring method of the embodiments of the present application.

[0110] ​The processor 601 may, in some embodiments, be a central processing unit (CPU), a microprocessor, or other data processing chip, used to run program codes stored in the memory 602 or process data, such as executing the FBG optical fiber-based road surface compactness monitoring program.

[0111] The embodiment also provides a computer readable storage medium, which stores the FBG optical fiber-based road surface compactness monitoring program, and the computer program is executed by the processor to implement the FBG optical fiber-based road surface compactness monitoring method according to any of the above technical solutions.

[0112] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by a computer program instructing related hardware, and the computer program can be stored in a non-volatile computer readable storage medium, and when the computer program is executed, the processes of the above-mentioned embodiments can be included. Any reference to memory, storage, database or other medium used in each embodiment provided by the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0113] The above description is only a preferred embodiment of the present application, but the protection scope of the present application is not limited thereto, and any changes or replacements within the technical scope disclosed by the present application can be easily thought by those skilled in the art, which should be covered within the protection scope of the present application.

Claims

1. A road surface compaction monitoring method based on FBG optical fiber, characterized in that: include: burying the FBG optical fiber into a plurality of path test pieces, compacting the plurality of path test pieces, and determining a plurality of groups of wavelength data of the FBG optical fiber; Obtaining the compaction degree of the plurality of road test specimens, and determining a functional relationship between the compaction degree and the wavelength by linear fitting based on the plurality of sets of wavelength data; burying the FBG optical fiber in a road surface to be measured, obtaining wavelength data of the road surface to be measured, and determining the compaction degree of the road surface to be measured based on the relationship between the compaction degree and the wavelength; The obtaining of the compaction degree of the plurality of road test specimens and determining a functional relationship between the compaction degree and the wavelength by linear fitting based on the plurality of sets of wavelength data include: Determining multiple groups of maximum wavelength change values ​​of the FBG optical fiber according to the multiple groups of wavelength data; Determining a functional relationship between the compaction degree and the maximum wavelength change value by linear fitting based on the multiple groups of maximum wavelength change values ​​and the multiple compaction degrees corresponding thereto; Determining multiple groups of maximum wavelength change values ​​of the FBG optical fiber according to the multiple groups of wavelength data includes: Determining, based on the multiple sets of wavelength data and the photoelastic effect, multiple sets of wavelength drifts of the FBG optical fiber; Determining multiple sets of center wavelengths of the FBG optical fiber according to the multiple sets of wavelength drifts and based on a relationship between grating wavelength and strain; According to the multiple groups of center wavelengths, multiple groups of maximum wavelength change values ​​of the FBG optical fiber are determined.

2. The road surface compaction monitoring method based on FBG optical fiber according to claim 1, characterized in that: Determining the functional relationship between the compaction degree and the maximum wavelength change value by linear fitting based on the multiple groups of maximum wavelength change values ​​and the corresponding multiple compaction degrees includes: The compaction degree and the corresponding multiple groups of maximum wavelength change values ​​are grouped into multiple number pairs, and the multiple number pairs are expressed one by one in a coordinate system to obtain a curve of the compaction degree and the maximum wavelength change value; The curve is corrected to determine the functional relationship between the degree of compaction and the maximum wavelength change value.

3. The road surface compaction monitoring method based on FBG optical fiber according to claim 1, characterized in that: The step of embedding the FBG optical fiber into a plurality of test specimens and compacting the plurality of test specimens comprises: obtaining road mix; The pavement mixture and the FBG optical fiber are placed in a plurality of roadbed test specimens, and are rotated and compacted to obtain the plurality of roadbed test specimens.

4. The road surface compaction monitoring method based on FBG optical fiber according to claim 3, characterized in that: The step of placing the pavement mixture and the FBG optical fiber in a plurality of roadbed test pieces comprises: placing the pavement mixture in the plurality of roadbed test pieces; Dividing the plurality of roadbed specimens into an upper layer, a middle layer and a lower layer according to a preset ratio; The FBG optical fiber is buried between the upper surface layer and the middle surface layer.

5. The road surface compaction monitoring method based on FBG optical fiber according to claim 4, characterized in that: The rotary compaction to obtain the plurality of road test pieces includes: The upper layer, the middle layer and the lower layer of the plurality of pavement test pieces are respectively and sequentially subjected to layered rotational compaction to obtain the plurality of pavement test pieces.

6. A road surface compaction monitoring device based on FBG optical fiber, characterized in that: include: A wavelength acquisition module is used to bury the FBG optical fiber into a plurality of path test pieces, compact the plurality of path test pieces, and determine a plurality of groups of wavelength data of the FBG optical fiber; a module for determining the relationship between compaction and wavelength, configured to obtain the compaction of the plurality of road test specimens and determine the functional relationship between the compaction and wavelength by linear fitting based on the plurality of sets of wavelength data; A compaction monitoring module is used to bury the FBG optical fiber in the road surface to be tested, obtain wavelength data of the road surface to be tested, and determine the compaction of the road surface to be tested based on the relationship between the compaction and the wavelength; The obtaining of the compaction degree of the plurality of road test specimens and determining a functional relationship between the compaction degree and the wavelength by linear fitting based on the plurality of sets of wavelength data include: Determining multiple groups of maximum wavelength change values ​​of the FBG optical fiber according to the multiple groups of wavelength data; Determining a functional relationship between the compaction degree and the maximum wavelength change value by linear fitting based on the multiple groups of maximum wavelength change values ​​and the multiple compaction degrees corresponding thereto; Determining multiple groups of maximum wavelength change values ​​of the FBG optical fiber according to the multiple groups of wavelength data includes: Determining, based on the multiple sets of wavelength data and the photoelastic effect, multiple sets of wavelength drifts of the FBG optical fiber; Determining multiple sets of center wavelengths of the FBG optical fiber according to the multiple sets of wavelength drifts and based on a relationship between grating wavelength and strain; According to the multiple groups of center wavelengths, multiple groups of maximum wavelength change values ​​of the FBG optical fiber are determined.

7. An electronic device, characterized in that: The method comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the method for monitoring road compaction based on FBG optical fiber according to any one of claims 1 to 5 is implemented.

8. A storage medium, characterized in that: The storage medium stores computer program instructions, and when the computer program instructions are executed by a computer, the computer is caused to execute the road surface compaction monitoring method based on FBG optical fiber according to any one of claims 1 to 5.

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