Roadbed compaction quality detection method and device based on three-dimensional laser scanning

Abstract

The invention provides a roadbed compaction quality detection method and device based on three-dimensional laser scanning, and relates to the technical field of roadbed quality detection.The method comprises the steps that a roadbed to be compacted is subjected to regional division; performing a pre-test on the pre-test area based on three-dimensional laser scanning to obtain a compaction degree calculation formula about the compression amount; performing interval division and roadbed compaction on the to-be-compacted area, and performing compaction quality detection based on a compaction degree calculation formula and real-time three-dimensional laser scanning to obtain a compaction quality result of each interval; and according to the compaction quality result, obtaining an interval with unqualified quality, performing pressure supplement on the interval with unqualified quality, and stopping pressure supplement until the compaction quality result of each interval of the to-be-pressed area is qualified. The method solves the problems that a traditional quality detection method cannot well reflect the compaction quality of the whole site, and meanwhile the quality detection efficiency is low due to the fact that the traditional method is long in consumed time, proficiency of detection personnel, weather and the like.

Description

Technical Field

[0001] The present invention relates to the technical field of roadbed quality detection, and in particular to a roadbed compaction quality detection method and device based on three-dimensional laser scanning. Background Art

[0002] The roadbed is an important basic structure under the upper load. A qualified roadbed foundation is an important guarantee for the safety and durability of the upper structure. At present, the commonly used methods for detecting whether the roadbed is compacted include sand filling method, water filling method, and knife changing method. In the traditional compaction quality technology, after the vibratory roller has rolled, the operator selects a point on the roadbed plane and starts digging a pit. Then, the sand is filled to measure the volume of the pit, and the actual density, moisture content and maximum indoor dry density of the excavated soil particles are measured. Finally, the compaction degree is obtained, and then it is judged whether the roadbed layer meets the compaction standard.

[0003] However, traditional compaction quality technology uses point-to-surface detection to reflect the overall compaction quality, which is poorly representative. Secondly, measuring the on-site density of each layer and the maximum dry density in the room consumes a lot of manpower and time, and sometimes even requires stopping work to wait for the measurement results, which is inefficient. In addition, the weather at the compaction site is uncertain, so the measured compaction degree and the real-time on-site density may not correspond in real time. At the same time, the sampling samples on site are affected by factors such as the location of the sampling point, the proficiency of the inspection personnel, and the weather, resulting in large discreteness of the test results, affecting the reliability of the compaction quality evaluation. Summary of the invention

[0004] The purpose of the present invention is to provide a roadbed compaction quality detection method and device based on three-dimensional laser scanning to improve the above problems. In order to achieve the above purpose, the technical solution adopted by the present invention is as follows: In a first aspect, the present application provides a roadbed compaction quality detection method based on three-dimensional laser scanning, comprising: Divide the roadbed to be compacted into regions to obtain a pre-test area and an area to be compacted; A preliminary test was conducted on the preliminary test area based on 3D laser scanning to obtain a compaction calculation formula for the compression amount; The area to be compacted is divided into sections and the roadbed is compacted. The compaction quality is tested based on the compaction degree calculation formula and real-time 3D laser scanning to obtain the compaction quality results of each section. According to the compaction quality results, the intervals with unqualified quality are obtained, and the intervals with unqualified quality are supplemented with compaction until the compaction quality results of each interval in the area to be compacted are all of qualified quality, and then the supplementary compaction is stopped.

[0005] In a second aspect, the present application also provides a roadbed compaction quality detection device based on three-dimensional laser scanning, comprising: A partitioning module for partitioning the subgrade to be compacted into regions, obtaining a pre-test region and a region to be compacted; A pre-test module for conducting a pre-test on the pre-test region based on three-dimensional laser scanning to obtain a compaction degree calculation formula for the compression amount; A detection module for partitioning intervals and compacting the subgrade in the region to be compacted, and conducting compaction quality detection based on the compaction degree calculation formula and real-time three-dimensional laser scanning to obtain the compaction quality results for each interval; A judgment module for obtaining the intervals with unqualified quality according to the compaction quality results, and re-compacting the intervals with unqualified quality until the compaction quality results for each interval in the region to be compacted are all qualified, then stopping the re-compaction.

[0006] The beneficial effects of the present invention are as follows: The present invention uses a three-dimensional laser scanner to conduct full-coverage scanning of the compaction site, replacing the traditional point-by-point detection method, significantly improving the accuracy and representativeness of detection. At the same time, non-contact measurement is adopted, with a fast scanning speed, capable of collecting data in real time during the compaction process, realizing synchronous compaction and measurement, and greatly improving the detection efficiency. Meanwhile, by constructing a compaction degree calculation formula for the compression amount, the compaction quality results can be quickly obtained, realizing non-destructive detection and providing a scientific basis for construction decision-making. In addition, the method of the present invention has strong environmental adaptability, can work stably under different construction conditions, reduces manual operation and downtime waiting time, reduces construction costs, and has a wide application prospect.

[0007] Other features and advantages of the present invention will be described in the subsequent specification, and part of them will become obvious from the specification, or can be understood by implementing the embodiments of the present invention. The objectives and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in the written specification, claims, and drawings. Description of the Drawings

[0008] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0009] Figure 1 It is a schematic flow chart of the subgrade compaction quality detection method based on three-dimensional laser scanning described in the embodiments of the present invention; Figure 2 It is a schematic diagram of the pre-test region in the embodiments of the present invention; Figure 3 It is a schematic diagram of the compaction degree at different measurement points in the embodiments of the present invention; Figure 4 Schematic diagram of the partition of the area to be compacted in the embodiment of the present invention. Detailed implementation manners

[0010] In order to make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but is merely representative of selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0011] It should be noted that: similar reference numerals and letters denote similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive distinction and cannot be construed as indicating or implying relative importance.

[0012] Embodiment 1: This embodiment provides a method for detecting the compaction quality of a roadbed based on three-dimensional laser scanning.

[0013] Refer to Figure 1 , which shows that this method includes step S100, step S200, step S300 and step S400.

[0014] Step S100: Divide the roadbed to be compacted into areas to obtain a pre-test area and an area to be compacted; In this embodiment, according to the specification requirements, a test site should be selected for pre-test before roadbed compaction to provide guidance for a series of subsequent indicators. A rectangular site is selected as the pre-test area. Considering that the scanning range of the scanner should not be too large, the obtained pre-test area is as shown in Figure 2 , where the length is 50 m and the width is 30 m.

[0015] Step S200: Conduct a pre-test on the pre-test area based on three-dimensional laser scanning to obtain a compaction degree calculation formula for the compression amount; The step S200 includes: Step S201: Divide the pre-test area into a plurality of equally spaced test intervals, and set measuring points in each test interval; In this embodiment, the four vertices of the pre-test area are respectively set as boundary points, and then boundary points are also set at the midpoints of each side. Secondly, one or more points are set outside the pre-test area for placing 3D laser scanners, so that the scanning ranges of one or more 3D laser scanners can cover the entire pre-test area. As shown in Figure 2 Select a point 10 m outside the pre-test area to place the 3D laser scanner.

[0016] Multiple boundary points are used to clarify the range of 3D laser scanning, define the working area of the scanner, ensure that the scanner can cover the entire test site, and avoid missing or duplicate scanning. At the same time, as calibration points, they are used to correct the measurement errors of the scanner. If the site of the pre-test area is large, multiple scanners may be required to cover the entire area. The boundary points can be used as reference points to splice the data of multiple scanners to obtain complete 3D point cloud information.

[0017] Step S202: After static compaction of the pre-test area, obtain the initial average height of each test interval through 3D laser scanning, and measure the compaction degree of each measuring point by the sand replacement method; In this embodiment, a vibratory roller is selected, for example, the Sany roller SSR330c-6 is selected to start the first pass of static compaction. After the pre-test area is compacted and leveled by static compaction, a 3D laser scanner is used for scanning. When scanning, the 3D laser scanner emits laser light. After the laser beam irradiates the filler surface in the pre-test area, it is reflected and returns to the receiver of the 3D laser scanner. The 3D laser scanner calculates the distance from the laser to the filler surface according to the laser light speed and the time difference between emission and reception, obtains the position information of each point in the pre-test area, and generates dense 3D point cloud information. Then, the initial average height of each test interval is calculated through the dense 3D point cloud information.

[0018] At the same time, the compaction degree of the measuring points is measured. A pit is dug and sampled at each measuring point on site, and the sampling volume is , and its dry density and maximum dry density are measured in the laboratory. The compaction degree of each measuring point is calculated through the sand replacement method formula, that is, it represents the compaction degree of the corresponding test interval. Among them, the calculation of the compaction degree through the sand replacement method formula is specifically: ; In the formula, represents the compaction degree measured by the sand replacement method for the th compaction at the th measuring point, represents the dry density measured in the laboratory for the th compaction at the th measuring point, represents the th compaction at the The maximum dry density measured at each measuring point in the laboratory. Among them, the compaction degree measured by the sand replacement method for the th measuring point is represented by .

[0019] Step S203: Compact the pre-test area after static compaction multiple times, and calculate the compression amount of each test interval and the compaction degree of each measuring point after each compaction based on the initial average height; The said step S203 includes: Step A100: Compact the pre-test area after static compaction multiple times according to the preset number of compaction times, and obtain the three-dimensional point cloud information of each test interval after each compaction through three-dimensional laser scanning; Step A200: Measure the compaction degree of each measuring point after each compaction by the sand replacement method; Step A300: Calculate the average height of each test interval after each compaction through the three-dimensional point cloud information of each test interval; Step A400: Calculate the compression amount of each test interval after each compaction based on the initial average height and the average height.

[0020] In this embodiment, the calculation formula for the compression amount is: ; In the formula, represents the compression amount of the th measuring point after the th compaction, represents the average height of the th measuring point after the th compaction, represents the initial average height of the th measuring point after static compaction, where the compression amount of the th measuring point actually represents the compression amount of the test interval where the th measuring point is located.

[0021] Step S204: Perform linear fitting based on the compression amount and compaction degree information to obtain the compaction degree calculation formula.

[0022] The said step S204 includes: Step B100: Calculate the correlation between the compaction degree of each measuring point and the compression amount of the corresponding test interval after each compaction to obtain the correlation result; In this embodiment, the formula for correlation calculation is: ; In the formula, represents the correlation result of the th measuring point after the th compaction, represents the The compression amount of the th measurement point after the second compaction, represents the th compaction, and the compaction degree measured by the sand replacement method at the measurement point, represents the covariance, represents the variance.

[0023] Step B200: Determine whether the correlation requirement is met according to the correlation result. If so, calculate the average compaction degree after each compaction through the compaction degrees of multiple measurement points, and calculate the average compression amount after each compaction through the compression amounts of multiple test intervals. Otherwise, perform the pre-test again; In this embodiment, the most standardized measurement of the compaction degree is the measurement of the sand replacement method type. All the detection indexes existing in the current market and research need to be analyzed through the correlation with the actual compaction degree before the feasibility of the corresponding index can be verified. According to the specification, the correlation calculation greater than 0.7 can meet the requirement. Therefore, in this step, when , it indicates that the correlation between the compression amount and the compaction degree is relatively high and can be used to guide the actual compaction quality detection work. If the requirement is not yet met, the pre-test needs to be carried out again. Generally speaking, the requirement can be met, but due to reasons such as measurement errors and calculation mistakes, there is also a probability that the requirement is not met.

[0024] At the same time, due to the existence of errors, the measured compaction degree cannot fit perfectly with the actual compaction degree by 100%. And for the same compaction times, the compaction degrees obtained at different measurement points by the sand replacement method are also inconsistent, as Figure 3 shown. Therefore, it is necessary to calculate the average compaction degree through the compaction degrees of multiple measurement points to represent the compaction degree after each compaction, and at the same time calculate the average compression amount through the compression amounts of multiple test intervals to represent the compression amount after each compaction.

[0025] B300: Perform function fitting according to the average compaction degree and the average compression amount after each compaction to obtain the compaction degree calculation formula for the compression amount.

[0026] In this embodiment, various fitting methods can be selected for function fitting. It is found through experimental data that the relationship between the compression amount and the compaction degree as a whole shows a linear growth trend, which means that as the compression amount increases, the compaction degree also approximately increases linearly. Therefore, the linear fitting method is selected to obtain the compaction degree calculation formula, which is specifically: ; In the formula, represents the compaction degree, and both represent fitting parameters, represents the compression amount.

[0027] Step S300: Divide the area to be compacted into intervals and compact the subgrade, and perform compaction quality detection based on the compaction degree calculation formula and real-time three-dimensional laser scanning to obtain the compaction quality results of each interval; In this embodiment, the same boundary point settings as those in the pre-test area are also performed on the area to be compacted, and a three-dimensional laser scanner is arranged outside the area to be compacted.

[0028] The step S300 includes: Step S301: After static compaction of the area to be compacted, obtain the three-dimensional point cloud information after static compaction through three-dimensional laser scanning, and divide the area to be compacted to obtain multiple intervals; In this embodiment, the smaller the length of the divided intervals, the higher the accuracy, and the more comprehensively the compaction degree can be reflected. When actually dividing the intervals, a spacing of 4m - 10m is selected to divide the intervals. For example, Figure 4 as shown, the area to be compacted is divided into 10 intervals.

[0029] Step S302: Obtain the initial average height information of each interval after static compaction through the three-dimensional point cloud information after static compaction; In this embodiment, according to the divided intervals, calculate the average height within the intervals, that is, the initial average height information.

[0030] Step S303: Compact the area to be compacted after static compaction, and perform compaction quality detection on each interval based on the compaction degree calculation formula and the initial average height information to obtain the compaction quality results of each interval.

[0031] The step S303 includes: Step C100: Obtain the average height information of each interval after compaction through the three-dimensional laser scanner; Step C200: Calculate the standard compression amount corresponding to the target compaction degree based on the target compaction degree and the compaction degree calculation formula; In this embodiment, substitute the target compaction degree into the compaction degree calculation formula to obtain the target compression amount, and at the same time, considering the calculation error, adjust the target compression amount to obtain the standard compression amount. Among them, the standard compression amount is specifically: ; ; In the formula, represents the target compression amount, represents the target compaction degree, and both represent fitting parameters, represents the standard compression amount.

[0032] Target compaction degree Set according to actual requirements. For example, the target compaction degree needs to reach 0.91, 0.92, 0.94, 0.96, etc.

[0033] Step C300: Calculate the actual compression amount of each interval through the initial average height information and the average height information. Step C400: Obtain the compaction quality result of each interval by comparing the actual compression amount with the standard compression amount. The compaction quality result includes qualified quality and unqualified quality.

[0034] Step S400: Obtain the intervals with unqualified quality according to the compaction quality result, and perform supplementary compaction on the intervals with unqualified quality until the compaction quality result of each interval in the area to be compacted is qualified, then stop the supplementary compaction.

[0035] In this embodiment, due to different sites and regions, the required number of compaction times is also inconsistent, which is one of the reasons for the frequent occurrence of under-compaction and over-compaction during the compaction process. Since the number of compaction times is generally uniformly specified during compaction, some regions cannot reach or are lower than the actual compaction requirements, and it is difficult to obtain the under-compacted part during actual measurement.

[0036] Therefore, after obtaining the actual compression amount of each interval in this step, it is compared with the standard compression amount. Lower than the standard compression amount indicates that the compaction degree has not reached the requirement, and higher than the standard compression amount indicates that the requirement is met. According to the actual requirements, supplementary compaction is performed on the uncompacted part, and the qualified part does not need to be compacted. Through this step, after reaching the number of compaction times, the areas with unqualified quality can be quickly detected, and the unqualified areas can be compacted.

[0037] In summary, the present invention adopts 3D laser scanning technology, and performs full-coverage scanning on the entire compaction site by setting boundary points, avoiding the limitation of substituting points for surfaces in traditional methods, and significantly improving the accuracy and reliability of the detection results. At the same time, using 3D laser scanning technology can quickly collect target information, with a fast scanning speed, greatly shortening the detection time, improving the detection efficiency, and avoiding the need for a large amount of manpower and time in traditional compaction quality detection methods. Especially when measuring the in-situ dry density of each layer and the maximum dry density indoors, it often requires stopping work to wait for the measurement results, seriously affecting the construction efficiency.

[0038] And using 3D laser scanning technology for non-contact compaction quality detection enables the measurement personnel to complete data collection only through the scanner without having to frequently run around the site, saving labor costs. At the same time, non-contact measurement also avoids errors caused by improper manual operation, realizes non-destructive detection, and improves the stability and reliability of the detection.

[0039] The method of the present invention also collects data in real time during the compaction process through 3D laser scanning technology, realizing the synchronization of compaction and measurement, being able to detect problems in a timely manner, and avoiding rework caused by unqualified compaction. At the same time, by constructing a compaction degree calculation formula for the compression amount, the compaction quality result can be quickly obtained, providing a scientific basis for construction decision-making. While realizing non-destructive testing, it provides guidance for construction personnel through real-time feedback, further improving the construction quality and efficiency.

[0040] Embodiment 2: This embodiment provides a subgrade compaction quality detection device based on 3D laser scanning. The device includes: A division module, used for dividing the subgrade to be compacted into regions to obtain a pre-test region and a region to be compacted; A pre-test module, used for performing a pre-test on the pre-test region based on 3D laser scanning to obtain a compaction degree calculation formula for the compression amount; A detection module, used for dividing the region to be compacted into intervals and compacting the subgrade, and performing compaction quality detection based on the compaction degree calculation formula and real-time 3D laser scanning to obtain the compaction quality result of each interval; A judgment module, used for obtaining the intervals with unqualified quality according to the compaction quality result, and performing additional compaction on the intervals with unqualified quality until the compaction quality results of each interval in the region to be compacted are all qualified, then stopping the additional compaction.

[0041] The pre-test module includes: A setting unit, used for dividing the pre-test region into multiple equally spaced test intervals and setting measuring points in each test interval; A measurement unit, used for obtaining the initial average height of each test interval through 3D laser scanning after static compaction of the pre-test region, and measuring the compaction degree of each measuring point by the sand replacement method; A compaction unit, used for performing multiple compactions on the statically compacted pre-test region, and calculating the compression amount of each test interval and the compaction degree of each measuring point after each compaction based on the initial average height; A fitting unit, used for performing linear fitting based on the compression amount and compaction degree information to obtain the compaction degree calculation formula.

[0042] The compaction unit includes: A compaction subunit, used for performing multiple compactions on the statically compacted pre-test region according to the preset number of compaction times, and obtaining the 3D point cloud information of each test interval after each compaction through 3D laser scanning; A measurement subunit, used for measuring the compaction degree of each measuring point after each compaction by the sand replacement method; A first calculation subunit, used for calculating the average height of each test interval after each compaction through the 3D point cloud information of each test interval; A second calculation subunit, configured to calculate the compression amount of each test interval after each compaction based on the initial average height and the average height.

[0043] The detection module includes: A scanning unit, configured to obtain three-dimensional point cloud information after static pressure by performing three-dimensional laser scanning on the area to be compacted after static pressure, and partition the area to be compacted to obtain a plurality of intervals; An obtaining unit, configured to obtain the initial average height information of each interval after static pressure through the three-dimensional point cloud information after static pressure; A detection unit, configured to compact the area to be compacted after static pressure, and perform compaction quality detection on each interval through a compaction degree calculation formula and the initial average height information to obtain a compaction quality result for each interval.

[0044] It should be noted that regarding the device in the above embodiments, the specific manners in which each module performs operations have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0045] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention may have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

[0046] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed by the present invention, and all should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for detecting the compaction quality of a roadbed based on three-dimensional laser scanning, characterized in that, Including: Dividing the subgrade to be compacted into regions to obtain a pre-test region and a region to be compacted; Conducting a pre-test on the pre-test region based on 3D laser scanning to obtain a compaction degree calculation formula for the compression amount; Dividing the region to be compacted into intervals and compacting the subgrade, and conducting compaction quality detection based on the compaction degree calculation formula and real-time 3D laser scanning to obtain the compaction quality results for each interval; Obtaining the intervals with unqualified quality according to the compaction quality results, and performing supplementary compaction on the intervals with unqualified quality until the compaction quality results of each interval in the region to be compacted are all qualified, then stopping the supplementary compaction.

2. The method for detecting the subgrade compaction quality based on 3D laser scanning according to claim 1, wherein Conducting a pre-test on the pre-test region based on 3D laser scanning to obtain a compaction degree calculation formula for the compression amount, including: Dividing the pre-test region into multiple equally spaced test intervals and setting measuring points in each test interval; After static compaction of the pre-test region, obtaining the initial average height of each test interval through 3D laser scanning, and measuring the compaction degree of each measuring point by the sand replacement method; Performing multiple compactions on the statically compacted pre-test region, and calculating the compression amount of each test interval and the compaction degree of each measuring point after each compaction based on the initial average height; Performing linear fitting based on the compression amount and compaction degree information to obtain the compaction degree calculation formula.

3. The method for detecting the subgrade compaction quality based on three-dimensional laser scanning according to claim 2, wherein Performing multiple compactions on the statically compacted pre-test region, and calculating the compression amount of each test interval and the compaction degree of each measuring point after each compaction based on the initial average height, including: Performing multiple compactions on the statically compacted pre-test region according to the preset number of compaction times, and obtaining the 3D point cloud information of each test interval after each compaction through 3D laser scanning; Measuring the compaction degree of each measuring point after each compaction by the sand replacement method; Calculating the average height of each test interval after each compaction through the 3D point cloud information of each test interval; Calculating the compression amount of each test interval after each compaction based on the initial average height and the average height.

4. The method for detecting the subgrade compaction quality based on three-dimensional laser scanning according to claim 2, characterized in that Performing linear fitting based on the compression amount and compaction degree information to obtain the compaction degree calculation formula, including: Calculating the correlation between the compaction degree of each measuring point and the compression amount of the corresponding test interval after each compaction to obtain the correlation result; Judging whether the correlation requirement is met according to the correlation result. If so, calculating the average compaction degree after each compaction through the compaction degrees of multiple measuring points, and calculating the average compression amount after each compaction through the compression amounts of multiple test intervals. Otherwise, re-performing the pre-test; Performing function fitting according to the average compaction degree and average compression amount after each compaction to obtain the compaction degree calculation formula for the compression amount.

5. The method for detecting the subgrade compaction quality based on three-dimensional laser scanning according to claim 1, wherein Dividing the region to be compacted into intervals and compacting the subgrade, and conducting compaction quality detection based on the compaction degree calculation formula and real-time 3D laser scanning to obtain the compaction quality results for each interval, including: After static compaction of the region to be compacted, obtaining the 3D point cloud information after static compaction through 3D laser scanning, and partitioning the region to be compacted to obtain multiple intervals; Obtaining the initial average height information of each interval after static compaction through the 3D point cloud information after static compaction; Compacting the statically compacted region to be compacted, and conducting compaction quality detection on each interval based on the compaction degree calculation formula and the initial average height information to obtain the compaction quality results for each interval.

6. The method for detecting the subgrade compaction quality based on 3D laser scanning according to claim 5, characterized in that, Compact the area to be pressed after static pressure, and perform compaction quality detection on each interval through the compaction degree calculation formula and the initial average height information to obtain the compaction quality results of each interval, including: Obtain the average height information of each interval after compaction through a three-dimensional laser scanner; Calculate the standard compression amount corresponding to the target compaction degree based on the target compaction degree and the compaction degree calculation formula; Calculate the actual compression amount of each interval through the initial average height information and the average height information; Obtain the compaction quality results of each interval by comparing the actual compression amount and the standard compression amount, and the compaction quality results include qualified quality and unqualified quality.

7. A subgrade compaction quality detection device based on 3D laser scanning, characterized in that, Including: A division module for dividing the subgrade to be compacted into areas to obtain a pre-test area and an area to be pressed; A pre-test module for performing a pre-test on the pre-test area based on three-dimensional laser scanning to obtain a compaction degree calculation formula for the compression amount; A detection module for dividing the area to be pressed into intervals and compacting the subgrade, and performing compaction quality detection based on the compaction degree calculation formula and real-time three-dimensional laser scanning to obtain the compaction quality results of each interval; A judgment module for obtaining the intervals with unqualified quality according to the compaction quality results, and performing additional compaction on the intervals with unqualified quality until the compaction quality results of each interval in the area to be pressed are all qualified and then stop the additional compaction.

8. The subgrade compaction quality detection device based on 3D laser scanning according to claim 7, characterized in that, The pre-test module includes: A setting unit for dividing the pre-test area into multiple equally spaced test intervals and setting measuring points in each test interval; A measuring unit for obtaining the initial average height of each test interval through three-dimensional laser scanning after static pressure on the pre-test area, and measuring the compaction degree of each measuring point through the sand replacement method; A compaction unit for performing multiple compactions on the pre-test area after static pressure, and calculating the compression amount of each test interval and the compaction degree of each measuring point after each compaction based on the initial average height; A fitting unit for performing linear fitting based on the compression amount and compaction degree information to obtain the compaction degree calculation formula.

9. The device for detecting the subgrade compaction quality based on three-dimensional laser scanning according to claim 8, characterized in that, The compaction unit includes: A compaction subunit for performing multiple compactions on the pre-test area after static pressure according to the preset number of compaction times, and obtaining the three-dimensional point cloud information of each test interval after each compaction through three-dimensional laser scanning; A measuring subunit for measuring the compaction degree of each measuring point after each compaction through the sand replacement method; A first calculation subunit for calculating the average height of each test interval after each compaction through the three-dimensional point cloud information of each test interval; A second calculation subunit for calculating the compression amount of each test interval after each compaction based on the initial average height and the average height.

10. The subgrade compaction quality detection device based on three-dimensional laser scanning according to claim 7, characterized in that, The detection module includes: A scanning unit for obtaining the three-dimensional point cloud information after static pressure through three-dimensional laser scanning after static pressure on the area to be pressed, and dividing the area to be pressed to obtain multiple intervals; An obtaining unit for obtaining the initial average height information of each interval after static pressure through the three-dimensional point cloud information after static pressure; A detection unit for compacting the area to be pressed after static pressure, and performing compaction quality detection on each interval through the compaction degree calculation formula and the initial average height information to obtain the compaction quality results of each interval.

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