Image recognition-based identification method for the entire process of road compaction construction

Abstract

The present application relates to the field of asphalt paving technology and discloses a method for identifying the entire process of pavement compaction construction based on image recognition, comprising: collecting a first three-dimensional image of the road before compaction by a roller and a second three-dimensional image of the road after compaction by the roller; obtaining a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule; evaluating the compaction and smoothness of the compacted pavement based on the first cross-section set and the second cross-section set; and determining the current construction position based on the compaction and smoothness of the compacted pavement. In this way, the current compaction process can be accurately identified directly through changes in the pavement surface, avoiding data statistical errors caused by roller position relocation, allowing the pavement compaction process to proceed in an orderly manner, reducing the possibility of missed compaction or overcompaction, improving the efficiency of pavement compaction, and helping to prevent a decline in the pavement compaction effect.

Description

Technical Field

[0001] The present application relates to the field of asphalt paving technology, for example, to a method for identifying the entire process of road compaction construction based on image recognition. Background Art

[0002] During the paving process of asphalt pavement, initial compaction, secondary compaction and final compaction need to be carried out in different layers. At the same time, the compaction areas of the rollers for initial compaction, secondary compaction and final compaction are different. In the paving process of the same section of road surface, due to the progress and segmented paving, various rollers will appear on the road surface at the same time to compact the road surface. At the same time, the rollers for initial compaction and final compaction will be swapped with the rollers in the initial compaction position and the rollers in the final compaction position to swap the compaction order and work. Because the initial compaction roller requires continuous compaction operation, the final compaction does not. The final compaction is an intermittent compaction operation. After completing a section of compaction, a short rest can be taken. During the long compaction operation, the operator of the initial compaction roller is prone to mental fatigue, so the final compaction and initial compaction rollers need to swap their working positions during the construction operation.

[0003] In the traditional road compaction process, the operator remembers the current initial compaction, re-compaction and final compaction processes and operates the corresponding roller to compact the road surface. The collection equipment is also pre-programmed in sequence. However, once the position is changed, the statistical data is prone to errors. The collected and statistical data do not meet the operation requirements. The statistical data analysis results show errors, which reduces the efficiency of the road compaction and causes a decrease in the effect of the road compaction.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical elements or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] In some embodiments, a method for identifying the entire road compaction construction process based on image recognition includes:

[0007] collecting a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled;

[0008] Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule;

[0009] evaluating the compaction degree and smoothness of the rolled pavement based on the first cross-section set and the second cross-section set;

[0010] The current construction position is determined based on the compaction and flatness of the rolled road surface.

[0011] In some embodiments, obtaining a first cross-section set of images of the road surface before rolling and a second cross-section set of images of the road surface after rolling according to a preset first rule includes:

[0012] Cutting out cross-sectional views of the first three-dimensional image and the second three-dimensional image respectively according to a preset first plane, wherein the first plane is vertically arranged and has a length direction that is the same as a length direction of the road;

[0013] Setting the section plane of the first three-dimensional image as the first cross section and setting the section plane of the second three-dimensional image as the second cross section;

[0014] The first section and the second section are intercepted multiple times continuously along the width direction of the road according to a preset first accuracy to generate a first section set and a second section set; wherein the positions of the first section and the second section are the same each time, and the first section and the second section at the same position are set as a group of sections.

[0015] In some embodiments, after obtaining the first cross-section set of the first three-dimensional image and the second cross-section set of the second three-dimensional image according to a preset first rule, the method further includes:

[0016] Obtaining contour lines of the tops of the first and second sections, generating a first contour line of the first section and a second contour line of the second section set;

[0017] Differentiating the first contour line and the second contour line respectively according to a preset second precision to generate a first differential point set of the first contour line and a second differential point set of the second contour line;

[0018] The longitudinal height of each differential point in the first differential point set and the second differential point set is recorded.

[0019] In some embodiments, evaluating the compaction of the rolled pavement according to the first set of cross sections and the second set of cross sections includes:

[0020] For each set of cross sections, calculate the average height h1 of the first differential point in the first differential point set and the average height h2 of the second differential point in the second differential point set;

[0021] Get the change h between the average height h1 and the average height h2 of the same set of sections a ;

[0022] The change h a Compare with the preset compaction amount to generate the compaction degree.

[0023] In some embodiments, evaluating the smoothness of the rolled pavement according to the first cross-sectional set and the second cross-sectional set includes:

[0024] In each set of cross sections, the variance of the longitudinal heights of the first differential point in the first differential point set and the second differential point in the second differential point set is calculated, and the difference m is calculated;

[0025] Calculating the variance of the longitudinal heights of a plurality of differential points at the same position of the continuous first section and the second section along the width direction of the road surface and calculating the difference n;

[0026] The difference m and the difference n are compared with the preset range respectively to generate the smoothness of the road surface.

[0027] In some embodiments, before determining the current construction position according to the compaction and flatness of the rolled road surface, the method further includes:

[0028] Divide the road into multiple areas along the width direction according to the width of the roller tires;

[0029] Record the number and interval of roller rolling in each area;

[0030] If the interval is less than or equal to the set interval, the rolling before and after the interval will be recorded as the same rolling; if the interval is greater than the set interval, the rolling before and after the interval will be recorded as different rolling;

[0031] Determine the category of the first rolling in the same rolling according to the compaction degree and flatness.

[0032] In some embodiments, determining the current construction position according to the compaction and flatness of the rolled road surface further includes:

[0033] If the compaction degree is within the set first compaction range, the difference m is within the set first longitudinal flatness range, and the difference n is within the set first transverse flatness range, then the current construction position is determined to be initial compaction;

[0034] If the compaction degree is within the set second compaction range, the difference m is within the set second longitudinal leveling range, and the difference n is within the set second transverse leveling range, then the current construction position is determined to be re-compaction;

[0035] If the compaction degree is within the set third compaction range, the difference m is within the set third longitudinal leveling range, and the difference n is within the set third transverse leveling range, then the current construction position is determined to be final compaction;

[0036] Among them, the first compaction range, the second compaction range and the third compaction range are continuous.

[0037] In some embodiments, after determining the current construction position according to the compaction and flatness of the rolled road surface, the method further includes:

[0038] Dividing the second contour point set of each second cross section according to a preset third precision to generate a multi-segment point set;

[0039] Calculate the variance of each segment of the point set and determine the flatness of the current point set based on the variance of each segment of the point set;

[0040] If the flatness of the current point set is lower than the set flatness, a reminder will be issued.

[0041] The method for identifying the entire road compaction construction process based on image recognition provided by the embodiments of the present disclosure can achieve the following technical effects:

[0042] It can accurately identify the current rolling process directly through changes in the road surface, avoid data statistical errors caused by the position change of the roller, make the road rolling process proceed in an orderly manner, reduce the possibility of missed or over-rolling, improve the efficiency of road rolling, and help prevent the decline of road rolling effect.

[0043] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] One or more embodiments are exemplarily described by corresponding drawings. These exemplary descriptions and drawings do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation. In addition,

[0045] Figure 1 Schematic diagram of a method for identifying the entire process of road compaction construction based on image recognition provided by an embodiment of the present disclosure;

[0046] Figure 2 is a schematic diagram of another method for identifying the entire process of road compaction construction based on image recognition provided by an embodiment of the present disclosure;

[0047] Figure 3 is a schematic diagram of another method for identifying the entire process of road compaction construction based on image recognition provided by an embodiment of the present disclosure;

[0048] Figure 4 It is a schematic diagram of another method for identifying the entire process of road compaction construction based on image recognition provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The accompanying drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0050] In the description and claims of the embodiments of the present disclosure, as well as in the accompanying drawings, the terms "first," "second," and the like are used to distinguish similar items and are not necessarily used to describe a particular order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate to describe the embodiments of the present disclosure herein. In addition, the terms "including," "having," and any variations thereof are intended to cover non-exclusive inclusions.

[0051] Unless otherwise stated, the term "plurality" means two or more.

[0052] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0053] The term "and / or" describes an association between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or A and B.

[0054] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0055] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure can be combined with each other.

[0056] Reference Figure 1 The present disclosure provides a method for identifying the entire process of road compaction construction based on image recognition, including:

[0057] S101: Collect a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled.

[0058] S102: Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule.

[0059] S103: Evaluate the compaction degree and flatness of the rolled road surface according to the first cross-section set and the second cross-section set.

[0060] S104: Determine the current construction position according to the compaction degree and flatness of the rolled road surface.

[0061] 3D acquisition technology is used to capture 3D images of the road surface both before and after the roller has been rolled, generating a first 3D image of the road surface before rolling and a second 3D image of the road surface after rolling, respectively. The accuracy of the 3D images of the road surface is a primary consideration in generating the first and second 3D images. The first and second 3D images are then cut according to a pre-set first rule. The resulting cross-sections are set as the cross-sections of the corresponding 3D images, and corresponding first interface sets and second cross-section sets are generated. The road surface's compaction and smoothness are assessed based on the contour lines corresponding to the first and second cross-sections in the first and second cross-section sets. Construction locations are then determined based on the compaction and smoothness.

[0062] In this way, the current rolling process can be accurately identified directly through changes in the road surface, avoiding data statistical errors caused by the position change of the roller, allowing the road rolling process to proceed in an orderly manner, reducing the possibility of missed or excessive rolling, improving the efficiency of road rolling, and helping to prevent the decline of road rolling effect.

[0063] Optionally, obtaining a first cross-section set of the road surface image before rolling and a second cross-section set of the road surface image after rolling according to a preset first rule includes:

[0064] According to a preset first plane, cross-sectional views of the first three-dimensional image and the second three-dimensional image are respectively cut off, where the first plane is vertically arranged and the length direction is the same as the length direction of the road; the cross-sectional plane of the first three-dimensional image is set as the first cross-sectional view, and the cross-sectional plane of the second three-dimensional image is set as the second cross-sectional view.

[0065] The first plane can be a regular rectangular plane with a length greater than the road length; the first plane is moved vertically from top to bottom and cuts the first three-dimensional image and the second three-dimensional image, and the cutting surface cross-sections formed by the cutting are set as the first section and the second section respectively.

[0066] The first section and the second section are intercepted multiple times continuously along the width direction of the road according to a preset first accuracy to generate a first section set and a second section set; wherein the positions of the first section and the second section are the same each time, and the first section and the second section at the same position are set as a group of sections.

[0067] When intercepting the first cross-section set and the second cross-section set, the higher the first precision is and the greater the number of first cross-sections and second cross-sections collected is, the more accurate the compaction and flatness estimation is.

[0068] Reference Figure 2 The method for identifying the entire process of road compaction construction based on image recognition provided by the embodiment of the present disclosure further includes:

[0069] S201 , collecting a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled.

[0070] S202 : Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule.

[0071] S203 , obtaining contour lines of the tops of the first and second cross sections, and generating a first contour line of the first cross section and a second contour line of the second cross section set.

[0072] The contour lines at the top of the first section and the second section are the contour lines of the corresponding road surface.

[0073] S204 , differentiating the first contour line and the second contour line respectively according to a preset second precision to generate a first differential point set of the first contour line and a second differential point set of the second contour line.

[0074] S205 , recording the longitudinal height of each differential point in the first differential point set and the second differential point set, wherein the longitudinal height of each differential point is used to evaluate the compaction degree and the flatness of the rolled road surface.

[0075] A standard plane is preset at the bottom of the road surface, and the longitudinal height of the differential point is the distance between the differential point and the standard plane.

[0076] S206 , evaluating the compaction degree and the flatness of the rolled road surface according to the first cross-section set and the second cross-section set.

[0077] The evaluation process in this step is actually to evaluate the compaction and flatness of the rolled pavement based on the longitudinal heights of the differential points corresponding to the first cross-section set and the second cross-section set.

[0078] S207: Determine the current construction position according to the compaction degree and flatness of the rolled road surface.

[0079] When assessing pavement compaction, the primary method is to measure the overall change in pavement height, that is, the overall vertical height change. When assessing pavement flatness, the primary method is to measure the change in pavement height over a continuous section of a certain width, that is, the curvature of the pavement surface within a certain width. Both the overall vertical height change and the curvature of the pavement surface within a certain width can be reflected by the longitudinal height of the differential point. Therefore, the longitudinal height change of the differential point of the pavement contour line accurately reflects the pavement's compaction and flatness, improving the accuracy of the assessment.

[0080] Optionally, evaluating the compaction degree of the rolled pavement according to the first cross-section set and the second cross-section set includes: for each set of cross-sections, respectively calculating the average height h1 of the first differential point in the first differential point set and the average height h2 of the second differential point in the second differential point set; obtaining the change h between the average height h1 and the average height h2 of the same set of cross-sections. a ; Change h a Compare with the preset compaction amount to generate the compaction degree.

[0081] The average height reflects the overall height within the current road setting range. a When it is larger, it indicates that the compaction degree is low before rolling. a When it is smaller, the surface has a higher degree of compaction before rolling. When generating the compaction, the total change of the road surface from asphalt paving to rolling is estimated, and the total change of the road surface is set as the preset compaction amount. The compaction is:

[0082] Where X is the degree of compaction; H is the preset compaction amount; ∑h a It is the sum of the current change ha and all previous changes ha.

[0083] Optionally, evaluating the smoothness of the rolled road surface according to the first cross-section set and the second cross-section set includes:

[0084] In each group of sections, the variance of the longitudinal heights of the first differential point in the first differential point set and the second differential point in the second differential point set is calculated, and the difference m is calculated; along the width direction of the road surface, the variance of the longitudinal heights of multiple differential points at the same position of the continuous first sections and the second sections is calculated, and the difference n is calculated; the difference m and the difference n are compared with the preset range respectively to generate the flatness of the road surface.

[0085] Variance indicates the degree of dispersion or deviation of the current data. The variance of a differential point set is used to indicate the smoothness of the current differential point set. A larger variance indicates a more unstable differential point set and a lower smoothness. A smaller variance indicates a more stable differential point set and a higher smoothness. The difference in variance is used to indicate the change in smoothness.

[0086] In this way, using variance to represent the smoothness of the current differential point set can accurately reflect the smoothness information of the current road surface, thereby facilitating accurate and real-time monitoring of the road construction process.

[0087] Reference Figure 3 The method for identifying the entire process of road compaction construction based on image recognition provided by the embodiment of the present disclosure further includes:

[0088] S301 , collecting a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled.

[0089] S302: Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule.

[0090] S303: Evaluate the compaction degree and flatness of the rolled road surface according to the first cross-section set and the second cross-section set.

[0091] S304: Divide the road into multiple areas along the width direction according to the width of the roller tires.

[0092] S305, recording the number and interval of roller rolling in each area.

[0093] S306: If the interval is less than or equal to the set interval, the rolling before and after the interval is recorded as the same rolling; if the interval is greater than the set interval, the rolling before and after the interval is recorded as different rolling.

[0094] S307, judging the category of the first rolling in the same rolling according to the compaction degree and the flatness.

[0095] S308: Determine the current construction position according to the compaction degree and flatness of the rolled road surface.

[0096] During the initial compaction, repeated compaction and final compaction processes, in each compaction category, the change in the road surface before and after the first compaction is relatively large, so the first compaction is selected as the typical feature for identification.

[0097] Optionally, the current construction position is determined according to the compaction degree and flatness of the rolled road surface, including: if the compaction degree is within the set first compaction range, the difference m is within the set first longitudinal flatness range, and the difference n is within the set first transverse flatness range, then the current construction position is determined to be initial compaction; if the compaction degree is within the set second compaction range, the difference m is within the set second longitudinal flatness range, and the difference n is within the set second transverse flatness range, then the current construction position is determined to be re-compaction; if the compaction degree is within the set third compaction range, the difference m is within the set third longitudinal flatness range, and the difference n is within the set third transverse flatness range, then the current construction position is determined to be final compaction; wherein, the first compaction range, the second compaction range, and the third compaction range are continuous

[0098] For example, during the initial compaction process, the overall road height changes significantly. If the first area undergoes initial compaction while the second area hasn't, there's a height difference across the width of the road, resulting in a large difference in height, n. While the change in the first initial compaction of a given area is significant, the change in the second initial compaction is smaller. However, the overall height change during initial compaction is greater than during recompacting, indicating that different compaction degrees result in different changes in compaction.

[0099] For example, after the re-pressing is completed but before the final pressing begins, there are some rutting marks on the road surface. After the final pressing is completed, the rutting marks disappear, and the change in compaction degree is smaller than before and after the initial pressing and before and after the re-pressing; the flatness becomes higher, but the change in flatness is smaller than the change in flatness before and after the initial pressing and re-pressing; among them, the changes in the difference m and difference n of the road surface before and after the final pressing are relatively small.

[0100] In the process of judging the initial pressure, repeated pressure and final pressure, not only can the construction position be judged by the compaction degree, difference m and difference n, but also the compaction degree change, the variance of the longitudinal height of the first differential point in the first differential point set and the second differential point in the second differential point set, the variance of the longitudinal height of multiple differential points at the same position of the first section and the second section, and the changes in the road surface before and after the initial pressure, repeated pressure and final pressure are completed can be combined to make a comprehensive judgment.

[0101] Reference Figure 4 The method for identifying the entire process of road compaction construction based on image recognition provided by the embodiment of the present disclosure further includes:

[0102] S401, collecting a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled.

[0103] S402: Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule.

[0104] S403: Evaluate the compaction degree and flatness of the rolled road surface based on the first cross-section set and the second cross-section set.

[0105] S404: Determine the current construction position according to the compaction degree and flatness of the rolled road surface.

[0106] S405 , dividing the second contour point set of each second cross section according to a preset third precision to generate multiple segment point sets.

[0107] S406 , calculating the variance of each segment of the point set and determining the flatness of the current point set based on the variance of each segment of the point set.

[0108] S407: If the flatness of the current point set is lower than the set flatness, a reminder is issued.

[0109] For a set of points in a given section, the system uses the variance to determine the smoothness of the current set after compaction, allowing it to detect whether the road surface within the current section has been compacted. If the variance is large and the smoothness is low, a reminder is issued to the relevant person in charge, indicating that the current road surface has not been compacted as expected. This allows for automatic guidance and monitoring of the entire on-site construction process, providing reminders of any defects.

[0110] When calculating the variance of the current point set after rolling, the average height is calculated using the average height of the entire second contour point set.

[0111] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to also include plural forms. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of one or more associated listings. In addition, when used in this application, the term "comprise" and its variations "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups of these. In the absence of further restrictions, an element defined by the statement "comprises a..." does not exclude the presence of other identical elements in the process, method or device that includes the element. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments can be referenced to each other. For the methods disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can be found in the description of the method part.

[0112] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The skilled person may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the embodiments of the present disclosure.

[0113] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functions, and operations that may be implemented according to the methods of the embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, program segment, or portion of code, which contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the boxes may also occur in an order different from that marked in the drawings. For example, two consecutive boxes may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different boxes may also occur in an order different from that disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. Each box in the block diagram and / or flowchart, as well as combinations of boxes in the block diagram and / or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or action, or may be implemented using a combination of dedicated hardware and computer instructions.

Claims

1. A method for identifying the entire process of road compaction construction based on image recognition, comprising: collecting a first three-dimensional image of the road before the roller is rolled and a second three-dimensional image of the road after the roller is rolled; Acquire a first cross-section set of the first three-dimensional image and a second cross-section set of the second three-dimensional image according to a preset first rule; Obtaining contour lines of the tops of the first and second sections, generating a first contour line of the first section and a second contour line of the second section set; Differentiating the first contour line and the second contour line respectively according to a preset second precision to generate a first differential point set of the first contour line and a second differential point set of the second contour line; Recording the longitudinal height of each differential point in the first differential point set and the second differential point set, wherein the longitudinal height of each differential point is used to evaluate the compaction and smoothness of the rolled road surface; evaluating the compaction degree and smoothness of the rolled pavement based on the first cross-section set and the second cross-section set; include; For each set of cross sections, calculate the average height h1 of the first differential point in the first differential point set and the average height h2 of the second differential point in the second differential point set; Get the change h between the average height h1 and the average height h2 of the same set of sections a ; The change h a Compare with the preset compaction amount to generate the compaction degree; When generating the compaction degree, the total pavement change from asphalt paving to rolling is estimated, and the total pavement change is set as the preset compaction amount. The compaction degree is: Among them, X is the degree of compaction, H is the preset compaction amount, is the sum of the current change ha and all previous changes ha; In each set of cross sections, the variance of the longitudinal heights of the first differential point in the first differential point set and the second differential point in the second differential point set is calculated, and the difference m is calculated; Calculating the variance of the longitudinal heights of a plurality of differential points at the same position of the continuous first section and the second section along the width direction of the road surface and calculating the difference n; Compare the difference m and difference n with the preset range respectively to generate the smoothness of the road surface; The current construction position is determined based on the compaction and flatness of the rolled road surface.

2. The method for identifying the entire process of road compaction construction based on image recognition according to claim 1, characterized in that: Acquiring a first cross-section set of images of the road surface before rolling and a second cross-section set of images of the road surface after rolling according to a preset first rule includes: Cutting out cross-sectional views of the first three-dimensional image and the second three-dimensional image respectively according to a preset first plane, wherein the first plane is vertically arranged and has a length direction that is the same as a length direction of the road; Setting the section plane of the first three-dimensional image as the first cross section and setting the section plane of the second three-dimensional image as the second cross section; The first section and the second section are intercepted multiple times continuously along the width direction of the road according to a preset first accuracy to generate a first section set and a second section set; wherein the positions of the first section and the second section are the same each time, and the first section and the second section at the same position are set as a group of sections.

3. The method for identifying the entire process of road compaction construction based on image recognition according to claim 1, characterized in that: Before determining the current construction position based on the compaction and smoothness of the rolled road surface, it also includes: Divide the road into multiple areas along the width direction according to the width of the roller tires; Record the number and interval of roller rolling in each area; If the interval is less than or equal to the set interval, the rolling before and after the interval will be recorded as the same rolling; if the interval is greater than the set interval, the rolling before and after the interval will be recorded as different rolling; Determine the category of the first rolling in the same rolling according to the compaction degree and flatness.

4. The method for identifying the entire process of road compaction construction based on image recognition according to claim 3, characterized in that: The current construction position is determined based on the compaction and smoothness of the rolled road surface, including: If the compaction degree is within the set first compaction range, the difference m is within the set first longitudinal flatness range, and the difference n is within the set first transverse flatness range, then the current construction position is determined to be initial compaction; If the compaction degree is within the set second compaction range, the difference m is within the set second longitudinal leveling range, and the difference n is within the set second transverse leveling range, then the current construction position is determined to be re-compaction; If the compaction degree is within the set third compaction range, the difference m is within the set third longitudinal leveling range, and the difference n is within the set third transverse leveling range, then the current construction position is determined to be final compaction; Among them, the first compaction range, the second compaction range and the third compaction range are continuous.

5. The method for identifying the entire process of road compaction construction based on image recognition according to claim 3, characterized in that: After determining the current construction position based on the compaction and smoothness of the rolled road surface, it also includes: Dividing the second contour point set of each second cross section according to a preset third precision to generate a multi-segment point set; Calculate the variance of each segment of the point set and determine the flatness of the current point set based on the variance of each segment of the point set; If the flatness of the current point set is lower than the set flatness, a reminder will be issued.

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