A construction quality detection method and system for roadbed reconstruction and expansion

Abstract

The present invention discloses a method and system for inspecting the construction quality of a rebuilt or expanded roadbed. The method comprises: acquiring image information of at least one rebuilt or expanded roadbed subregion to obtain at least one rebuilt or expanded roadbed subregion image; analyzing the at least one rebuilt or expanded roadbed subregion image based on location information of the at least one rebuilt or expanded roadbed subregion to obtain at least one rebuilt or expanded roadbed subregion image sequence; extracting a target rebuilt or expanded roadbed subregion image from each of the at least one rebuilt or expanded roadbed subregion image sequences, and defining the rebuilt or expanded roadbed subregion corresponding to each target rebuilt or expanded roadbed subregion image as a target rebuilt or expanded roadbed subregion; determining a construction quality index for each target rebuilt or expanded roadbed subregion, and fusing the individual construction quality indexes to obtain a target construction quality index for the rebuilt or expanded roadbed area. This method effectively improves the efficiency of inspecting the construction quality of the rebuilt or expanded roadbed.

Description

Technical Field

[0001] The present invention belongs to the technical field of roadbed detection, and in particular relates to a construction quality detection method and system for roadbed reconstruction and expansion. Background Art

[0002] In highway reconstruction and expansion projects, the quality of roadbed splicing directly impacts the overall stability and service life of the road. Traditional construction quality inspection methods rely primarily on manual sampling (such as cross-section elevation measurement and compaction spot checks), which suffer from low coverage, high subjectivity, and discrete data.

[0003] In the existing technology, the surface flatness of the entire rebuilt and expanded roadbed is analyzed and detected based on image recognition. However, the influence of the slope design of the original road surface on the surface flatness of the rebuilt and expanded roadbed is often ignored, resulting in the surface of a certain section of the rebuilt and expanded roadbed being uneven compared to the surfaces of other sections of the rebuilt and expanded roadbed, but this may also meet the construction quality requirements. The occurrence of this phenomenon will cause the construction quality inspection results to deviate from the actual construction quality inspection results, and there is a problem of low construction quality inspection accuracy. Summary of the Invention

[0004] The present invention provides a construction quality detection method and system for roadbed reconstruction and expansion, which are used to solve the technical problem that the construction quality detection result deviates from the actual construction quality detection result and the construction quality detection accuracy is low.

[0005] In a first aspect, the present invention provides a method for detecting the construction quality of a roadbed reconstruction and expansion, comprising:

[0006] Obtaining at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and dividing the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is the road surface connected to the rebuilt and expanded roadbed area and not rebuilt and expanded;

[0007] Acquiring image information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image, and analyzing the at least one renovated and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image sequence;

[0008] extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and defining the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region;

[0009] The construction quality index of each target reconstruction and expansion roadbed sub-area is determined, and according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area, the various construction quality indexes are fused to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0010] In a second aspect, the present invention provides a construction quality detection system for roadbed reconstruction and expansion, comprising:

[0011] a division module configured to obtain at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and divide the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is a road surface connected to the rebuilt and expanded roadbed and not rebuilt and expanded;

[0012] an analysis module configured to acquire image information of the at least one rebuilt and expanded roadbed sub-region, obtain at least one rebuilt and expanded roadbed sub-region image, and analyze the at least one rebuilt and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-region, to obtain at least one rebuilt and expanded roadbed sub-region image sequence;

[0013] an extraction module configured to extract a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and define the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region;

[0014] The fusion module is configured to determine the construction quality index of each target reconstruction and expansion roadbed sub-area, and fuse the various construction quality indexes according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0015] In a third aspect, an electronic device is provided, comprising: at least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can perform the steps of the construction quality inspection method for roadbed reconstruction and expansion of any embodiment of the present invention.

[0016] In a fourth aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the program instructions are executed by a processor, the processor executes the steps of the construction quality inspection method for roadbed reconstruction and expansion according to any embodiment of the present invention.

[0017] The construction quality inspection method and system for a rebuilt and expanded roadbed of the present application analyzes at least one rebuilt and expanded roadbed sub-region image based on the location information of at least one rebuilt and expanded roadbed sub-region and a preset image processing strategy to obtain at least one rebuilt and expanded roadbed sub-region image sequence. This achieves clustering of identical or similar roadbed structural feature lines. Consequently, only one target rebuilt and expanded roadbed sub-region image needs to be extracted from the at least one rebuilt and expanded roadbed sub-region image sequence according to a preset image extraction strategy. The construction quality index of the target rebuilt and expanded roadbed sub-region corresponding to the target rebuilt and expanded roadbed sub-region image is determined simultaneously. This allows for relatively rapid determination of the construction quality index of the rebuilt and expanded roadbed sub-region corresponding to each rebuilt and expanded roadbed sub-region image in the same rebuilt and expanded roadbed sub-region image sequence. Furthermore, based on the number of images in each rebuilt and expanded roadbed sub-region image sequence, the construction quality indexes are fused to obtain a target construction quality index for the entire rebuilt and expanded roadbed area, thereby effectively improving the efficiency of construction quality inspection of the rebuilt and expanded roadbed. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0019] Figure 1 A flow chart of a method for detecting the construction quality of a roadbed reconstruction and expansion provided by one embodiment of the present invention;

[0020] Figure 2 A schematic diagram of the splicing degree of each monitoring point in a two-dimensional coordinate system is provided for one embodiment of the present invention;

[0021] Figure 3 A structural block diagram of a construction quality inspection system for roadbed reconstruction and expansion provided by one embodiment of the present invention;

[0022] Figure 4 It is a structural diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0024] See also Figure 1 , which shows a flow chart of a construction quality inspection method for roadbed reconstruction and expansion of the present application.

[0025] like Figure 1 As shown in FIG, the construction quality inspection method of the roadbed reconstruction and expansion specifically includes the following steps:

[0026] Step S101: obtaining at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and dividing the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is the road surface connected to the rebuilt and expanded roadbed area and has not been rebuilt or expanded.

[0027] In this step, at least one monitoring point is set on the rebuilt and expanded roadbed area, and at least one monitoring point is evenly distributed along the length direction of the rebuilt and expanded roadbed area; the vertical distance between each monitoring point and the original road surface is obtained, and each vertical distance is defined as at least one splicing degree between the original road surface and the rebuilt and expanded roadbed area, wherein the vertical distance is the shortest length of the vertical line from the monitoring point to the original road surface.

[0028] By evenly distributing monitoring points and measuring vertical distances, the connection between the original road surface and the expanded roadbed can be quantified, avoiding manual visual errors. In a specific application scenario, a highway expansion project had an original road surface width of 10 meters and required a new 5-meter-wide roadbed.

[0029] Steps: Set up monitoring points every 2 meters in the roadbed reconstruction area (a total of 3 points: A, B, and C). Measure the vertical distance from each point to the original road surface (e.g., A = 5 cm, B = 8 cm, C = 4 cm) and record this as the splicing degree.

[0030] Furthermore, a cross section is set, moved along the length of the original road surface, and the original road surface is intercepted. The original road surface between two adjacent cross sections is defined as an original road surface sub-area, resulting in at least one original road surface sub-area, wherein the distance the cross section moves each time is a monitoring length, and the monitoring length is the distance between two adjacent monitoring points. During each movement, the cross section is perpendicular to the original road surface and contains one monitoring point. Each splicing degree is set in a preset two-dimensional coordinate system, and the splicing degrees in the two-dimensional coordinate system are sequentially connected to obtain a broken line segment. All inflection points in the broken line segment are selected, and the splicing degrees at the inflection points are defined as questionable splicing degrees, wherein the horizontal coordinate of the two-dimensional coordinate system is the location information of each monitoring point, and the vertical coordinate is the splicing degree at each monitoring point.

[0031] For example, based on their location information, the monitoring points are ranked in order: monitoring point A (splicing degree a is 5 cm), monitoring point B (splicing degree b is 5 cm), monitoring point C (splicing degree c is 6 cm), monitoring point D (splicing degree d is 7 cm), monitoring point E (splicing degree e is 7 cm), monitoring point F (splicing degree f is 5 cm), monitoring point G (splicing degree g is 6 cm), and monitoring point H (splicing degree h is 6 cm). The resulting splicing degree sequence is (splicing degree a, splicing degree b, splicing degree c, splicing degree d, splicing degree e, splicing degree f, splicing degree g, splicing degree h).

[0032] So, if Figure 2 As shown, the inflection points in the broken line segment include monitoring point B (splicing degree b), monitoring point D (splicing degree d), monitoring point E (splicing degree e), monitoring point F (splicing degree f) and monitoring point G (splicing degree g).

[0033] The monitoring location corresponding to the suspected splicing degree is defined as a suspected monitoring point, and a determination is made as to whether the height difference between the two original pavement sub-areas adjacent to the suspected monitoring point is greater than a preset height threshold. If so, the reconstruction and expansion roadbed area is not divided using the splitting plane containing the suspected monitoring point, and a determination is made as to whether the height difference between the two original pavement sub-areas adjacent to the next suspected monitoring point is greater than the preset height threshold. If not, the reconstruction and expansion roadbed area is divided using the splitting plane containing the suspected monitoring point to obtain at least one reconstruction and expansion roadbed sub-area, wherein the splitting plane is perpendicular to the plane of the reconstruction and expansion roadbed area.

[0034] Specifically, if it is greater than the preset height threshold, it means that the two original pavement sub-areas corresponding to the questionable monitoring point are not level. At this time, the splicing degree set for the questionable monitoring point may be specially set to adapt to the uneven original pavement sub-areas. Therefore, the reconstruction and expansion roadbed area is not divided by the segmentation plane containing the questionable monitoring point, and it is continued to be judged whether the height difference between the two original pavement sub-areas adjacent to the next questionable monitoring point is greater than the preset height threshold; if it is not greater than the preset height threshold, it means that the two original pavement sub-areas corresponding to the questionable monitoring point are level. At this time, the splicing degree on the questionable monitoring point fluctuates compared with other splicing degrees, which may be caused by the uneven roadbed. Therefore, the reconstruction and expansion roadbed area is divided by the segmentation plane containing the questionable monitoring point to obtain at least one reconstruction and expansion roadbed sub-area.

[0035] In this embodiment, by defining the original pavement sub-area and dividing the reconstruction and expansion roadbed area according to the height difference of the original pavement sub-area and the suspicious monitoring points, at least one reconstruction and expansion roadbed sub-area is obtained, which effectively reduces the phenomenon of misdivision caused by changes in the design slope, thereby facilitating subsequent construction quality inspection of the reconstruction and expansion roadbed area.

[0036] Step S102: Acquire image information of the at least one rebuilt and expanded roadbed sub-area to obtain at least one rebuilt and expanded roadbed sub-area image; and analyze the at least one rebuilt and expanded roadbed sub-area image based on a preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-area to obtain at least one rebuilt and expanded roadbed sub-area image sequence.

[0037] In this step, the at least one rebuilt and expanded roadbed sub-region image is spatially arranged based on its splicing position relative to the original road surface to generate an initial image sequence. Each rebuilt and expanded roadbed sub-region image in the initial image sequence is grayscaled, and an edge detection algorithm is used to extract roadbed structural feature lines. The feature line similarity between each roadbed structural feature line is calculated, and at least two roadbed structural feature lines with feature line similarity greater than a preset similarity threshold are grouped into the same rebuilt and expanded roadbed sub-region image sequence, thereby obtaining at least one rebuilt and expanded roadbed sub-region image sequence. In one feasible embodiment, the Hausdorff distance algorithm is used to calculate the feature line similarity between each roadbed structural feature line.

[0038] It should be noted that the image of the reconstructed and expanded roadbed sub-area is first converted into a grayscale image, and the weighted average method (such as R:G:B=0.299:0.587:0.114) is used to calculate the grayscale value of each pixel to eliminate color interference.

[0039] Gaussian filtering denoising: A 5×5 Gaussian kernel is used to smooth the image (σ=1.4) to remove granular noise and fine texture interference commonly found in construction images.

[0040] Sobel edge detection: Apply the horizontal Sobel operator and the vertical Sobel operator to perform convolution operations respectively;

[0041] Calculate the gradient magnitude for each pixel: , is the gradient amplitude of the pixel point, Gx is the Sobel operator of the pixel point in the horizontal direction, and Gy is the Sobel operator of the pixel point in the vertical direction;

[0042] Set a gradient threshold (usually 15-20% of the grayscale value range) to retain significant edges.

[0043] Non-maximum suppression:

[0044] Compare adjacent pixels along the gradient direction and retain only the local gradient maximum points to keep the edge width at the single-pixel level.

[0045] Dual Threshold Connection:

[0046] Set a high threshold (e.g. 30% of the maximum gradient value) and a low threshold (50% of the high threshold);

[0047] Strong edge points are retained directly, and weak edge points are retained only when they are connected to strong edge points;

[0048] Finally, a 1-pixel-wide single-connected edge line is output;

[0049] Feature line extraction:

[0050] Perform Hough transform on the edge image to detect straight line segments;

[0051] Screening for horizontal line segments with a length greater than 50 pixels and an angle within the range of ±15°;

[0052] Merge horizontal line segments with a spacing of less than 10 pixels as roadbed structure feature lines.

[0053] Step S103 , extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and defining the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as a target reconstruction and expansion roadbed sub-region.

[0054] In this step, the target feature line similarity of each rebuilt and expanded roadbed sub-region image in a certain rebuilt and expanded roadbed sub-region image sequence is calculated, wherein a certain target feature line similarity is the sum of the feature line similarities between a certain roadbed structure feature line of a certain rebuilt and expanded roadbed sub-region image and other roadbed structure feature lines of other rebuilt and expanded roadbed sub-region images in a certain rebuilt and expanded roadbed sub-region image; and the rebuilt and expanded roadbed sub-region image corresponding to the maximum target similarity is defined as a certain target rebuilt and expanded roadbed sub-region image.

[0055] Step S104 , determining the construction quality index of each target reconstruction and expansion roadbed sub-area, and fusing the construction quality indexes according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0056] In this step, the compaction stability of each target reconstruction and expansion sub-area is calculated based on the standard deviation of the vibration VCV value, rolling speed, and number of passes of each target reconstruction and expansion sub-area, and the compaction uniformity of each target reconstruction and expansion sub-area is calculated based on the sample proportion of the specific value of the minimum grid rolling pass of each target reconstruction and expansion sub-area.

[0057] The expression for calculating the compaction stability of the target roadbed sub-area for reconstruction and expansion is:

[0058] ,

[0059] Where, To improve the compaction stability of the sub-area of ​​the roadbed, 、 、 are the normalized functions of rolling speed, number of passes, and VCV value, respectively. 、 、 They are the weight coefficients of rolling speed, number of passes and VCV value respectively;

[0060] It should be noted that the VCV value (Vibratory Compaction Value) is a key indicator reflecting the rheological properties of roller-compacted concrete (RCC) or roadbed materials during vibration compaction.

[0061] The expression for calculating the compaction uniformity of the target reconstruction and expansion sub-area is:

[0062] ,

[0063] ,

[0064] ,

[0065] Where, The compaction uniformity of the sub-area of ​​the roadbed to be renovated and expanded is the target. is the weight coefficient, usually ranging from 0.8 to 1.2, reflecting the relative importance of the VCV value and the number of rolling passes. [a, b] is the design allowable range, such as 8 to 12 seconds.

[0066] The construction quality index of each target reconstruction and expansion roadbed sub-area is calculated based on the compaction stability and compaction uniformity.

[0067] The expression for calculating the construction quality index of the target roadbed sub-area for reconstruction and expansion is:

[0068] ,

[0069] Where, The construction quality index of the target roadbed sub-area for renovation and expansion is: and are the weight coefficients of compaction stability and compaction uniformity respectively.

[0070] Furthermore, the number of images of the renovated and expanded roadbed sub-area in each renovated and expanded roadbed sub-area image sequence is obtained; a weight coefficient is assigned to each construction quality indicator according to the ratio of the number of images corresponding to each renovated and expanded roadbed sub-area image sequence to the total number of images, wherein the total number of images is the sum of the number of images of the renovated and expanded roadbed sub-area in all renovated and expanded roadbed sub-area image sequences; and each construction quality indicator is weightedly fused according to each weight coefficient to obtain the target construction quality of the renovated and expanded roadbed area.

[0071] In summary, the method of the present application analyzes at least one modified and expanded roadbed sub-area image based on the location information of at least one modified and expanded roadbed sub-area based on a preset image processing strategy to obtain at least one modified and expanded roadbed sub-area image sequence, thereby realizing clustering of the same or similar roadbed structure feature lines. Therefore, it is only necessary to subsequently extract a target modified and expanded roadbed sub-area image from at least one modified and expanded roadbed sub-area image sequence according to the preset image extraction strategy, and by determining the construction quality index of the target modified and expanded roadbed sub-area corresponding to the target modified and expanded roadbed sub-area image at one time, it is possible to relatively quickly determine the construction quality index of the modified and expanded roadbed sub-area corresponding to each modified and expanded roadbed sub-area image in the same modified and expanded roadbed sub-area image sequence, and according to the number of images in each modified and expanded roadbed sub-area image sequence, perform an index fusion on each construction quality index to obtain the target construction quality index of the entire modified and expanded roadbed area, thereby effectively improving the construction quality detection efficiency of the modified and expanded roadbed.

[0072] See also Figure 3 , which shows a structural block diagram of a construction quality inspection system for roadbed reconstruction and expansion of the present application.

[0073] like Figure 3 As shown, the construction quality inspection system 200 includes a division module 210 , an analysis module 220 , an extraction module 230 and a fusion module 240 .

[0074] The division module 210 is configured to obtain at least one degree of splicing between the original road surface and the rebuilt and expanded roadbed area, and divide the rebuilt and expanded roadbed area according to the at least one degree of splicing using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is a road surface connected to the rebuilt and expanded roadbed and not rebuilt and expanded; the analysis module 220 is configured to obtain image information of the at least one rebuilt and expanded roadbed sub-area, obtain at least one rebuilt and expanded roadbed sub-area image, and perform image processing on the at least one rebuilt and expanded roadbed sub-area image based on the position information of the at least one rebuilt and expanded roadbed sub-area based on a preset image processing strategy. The image sequence of the at least one reconstruction and expansion roadbed sub-region is analyzed to obtain at least one reconstruction and expansion roadbed sub-region image sequence; the extraction module 230 is configured to extract a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and define the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as a target reconstruction and expansion roadbed sub-region; the fusion module 240 is configured to determine the construction quality index of each target reconstruction and expansion roadbed sub-region, and fuse the construction quality indexes according to the number of images in each reconstruction and expansion roadbed sub-region image sequence to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0075] It should be understood that Figure 3 Modules and references documented in Figure 1 Therefore, the operations and features described above for the method and the corresponding technical effects also apply to Figure 3 The modules in it will not be described in detail here.

[0076] In other embodiments, embodiments of the present invention further provide a computer-readable storage medium having a computer program stored thereon, wherein when the program instructions are executed by a processor, the processor is caused to execute the construction quality inspection method for roadbed reconstruction and expansion in any of the above method embodiments;

[0077] As an embodiment, the computer-readable storage medium of the present invention stores computer-executable instructions, and the computer-executable instructions are configured as follows:

[0078] Obtaining at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and dividing the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is the road surface connected to the rebuilt and expanded roadbed area and not rebuilt and expanded;

[0079] Acquiring image information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image, and analyzing the at least one renovated and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image sequence;

[0080] extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and defining the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region;

[0081] The construction quality index of each target reconstruction and expansion roadbed sub-area is determined, and according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area, the various construction quality indexes are fused to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0082] The computer-readable storage medium may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the roadbed reconstruction and expansion construction quality inspection system, etc. In addition, the computer-readable storage medium may include a high-speed random access memory and may also include a memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state memory device. In some embodiments, the computer-readable storage medium may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the roadbed reconstruction and expansion construction quality inspection system via a network. Examples of the aforementioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0083] Figure 4 Schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Figure 4 As shown, the device includes: a processor 310 and a memory 320. The electronic device may also include: an input device 330 and an output device 340. The processor 310, the memory 320, the input device 330 and the output device 340 may be connected via a bus or other means. Figure 4The example of the bus connection is taken. The memory 320 is the computer-readable storage medium mentioned above. The processor 310 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions and modules stored in the memory 320, that is, implements the construction quality inspection method for the reconstruction and expansion of the roadbed in the above-mentioned method embodiment. The input device 330 can receive input digital or character information, and generate key signal input related to the user settings and function control of the construction quality inspection system for the reconstruction and expansion of the roadbed. The output device 340 may include a display device such as a display screen.

[0084] The electronic device can execute the method provided by the embodiment of the present invention, and has the functional modules and beneficial effects corresponding to the execution method. For technical details not fully described in this embodiment, please refer to the method provided by the embodiment of the present invention.

[0085] As an embodiment, the electronic device is applied to a construction quality inspection system for roadbed reconstruction and expansion, and is used for a client, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to:

[0086] Obtaining at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and dividing the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is the road surface connected to the rebuilt and expanded roadbed area and not rebuilt and expanded;

[0087] Acquiring image information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image, and analyzing the at least one renovated and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one renovated and expanded roadbed sub-region to obtain at least one renovated and expanded roadbed sub-region image sequence;

[0088] extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and defining the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region;

[0089] The construction quality index of each target reconstruction and expansion roadbed sub-area is determined, and according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area, the various construction quality indexes are fused to obtain the target construction quality index of the reconstruction and expansion roadbed area.

[0090] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods of each embodiment or certain portions of the embodiments.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for detecting the construction quality of a roadbed renovation and expansion, characterized in that: include: Obtaining at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and dividing the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is the road surface connected to the rebuilt and expanded roadbed area and not rebuilt and expanded; Acquiring image information of the at least one rebuilt and expanded roadbed sub-region to obtain at least one rebuilt and expanded roadbed sub-region image, and analyzing the at least one rebuilt and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-region to obtain at least one rebuilt and expanded roadbed sub-region image sequence, wherein analyzing the at least one rebuilt and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-region to obtain at least one rebuilt and expanded roadbed sub-region image sequence includes: Arranging the at least one rebuilt and expanded roadbed sub-region image in spatial order according to a splicing position of the rebuilt and expanded roadbed sub-region relative to the original road surface to generate an initial image sequence; Grayscale processing is performed on each of the reconstructed and expanded roadbed sub-region images in the initial image sequence, and an edge detection algorithm is used to extract the roadbed structure characteristic lines; Calculating the characteristic line similarity between each roadbed structure characteristic line, and dividing at least two roadbed structure characteristic lines whose characteristic line similarity is greater than a preset similarity threshold into the same reconstruction and expansion roadbed sub-region image sequence, to obtain at least one reconstruction and expansion roadbed sub-region image sequence; extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and defining the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region; Determine the construction quality index of each target reconstruction and expansion roadbed sub-area, and perform an index fusion on each construction quality index based on the number of images in the image sequence of each reconstruction and expansion roadbed sub-area to obtain a target construction quality index of the reconstruction and expansion roadbed area, wherein the target construction quality index of the reconstruction and expansion roadbed area obtained by performing an index fusion on each construction quality index based on the number of images in the image sequence of each reconstruction and expansion roadbed sub-area includes: Obtaining the number of images of the rebuilt and expanded roadbed sub-area in each rebuilt and expanded roadbed sub-area image sequence; Assigning a weight coefficient to each construction quality indicator according to a ratio of the number of images corresponding to each reconstruction and expansion roadbed sub-area image sequence to the total number of images, wherein the total number of images is the sum of the number of images of the reconstruction and expansion roadbed sub-area in all reconstruction and expansion roadbed sub-area image sequences; The various construction quality indicators are weighted and integrated according to the various weight coefficients to obtain the target construction quality indicators of the roadbed reconstruction and expansion area.

2. A construction quality inspection method for roadbed reconstruction and expansion according to claim 1, characterized in that: The step of obtaining at least one degree of connection between the original road surface and the reconstructed and expanded roadbed area includes: Setting at least one monitoring point on the renovated and expanded roadbed area, wherein the at least one monitoring point is evenly distributed along the length direction of the renovated and expanded roadbed area; Obtain the vertical distance between each monitoring point and the original road surface, and define each vertical distance as at least one splicing degree between the original road surface and the reconstructed and expanded roadbed area, wherein the vertical distance is the shortest length of a perpendicular line from the monitoring point to the original road surface.

3. A construction quality inspection method for roadbed reconstruction and expansion according to claim 2, characterized in that: The step of dividing the reconstruction and expansion roadbed area according to the at least one splicing degree using a preset area division rule to obtain at least one reconstruction and expansion roadbed sub-area includes: Setting a cross section, moving the cross section along the length direction of the original road surface, and intercepting the original road surface, defining the original road surface between two adjacent cross sections as an original road surface sub-region, and obtaining at least one original road surface sub-region, wherein the distance each time the cross section moves is a monitoring length, and the monitoring length is the distance between two adjacent monitoring points. During each movement, the cross section is perpendicular to the original road surface and contains one monitoring point. Each splicing degree is set in a preset two-dimensional coordinate system, the splicing degrees in the two-dimensional coordinate system are sequentially connected to obtain a broken line segment, and all inflection points are selected in the broken line segment, and the splicing degrees at the inflection points are defined as questionable splicing degrees, wherein the abscissa of the two-dimensional coordinate system is the position information of each monitoring point, and the ordinate is the splicing degree at each monitoring point; defining the monitoring location corresponding to the questionable splicing degree as a questionable monitoring point, and determining whether the height difference between two original road surface sub-areas adjacent to the questionable monitoring point is greater than a preset height threshold; If the height difference is greater than the preset height threshold, the reconstruction and expansion roadbed area is not divided by the segmentation plane containing the questionable monitoring point, and the height difference between the two original road surface sub-areas adjacent to the next questionable monitoring point is further determined to be greater than the preset height threshold; If it is not greater than a preset height threshold, the expanded roadbed area is divided by a dividing plane containing the questionable monitoring point to obtain at least one expanded roadbed sub-area, wherein the dividing plane is perpendicular to the plane of the expanded roadbed area.

4. The construction quality inspection method for roadbed reconstruction and expansion according to claim 1 is characterized in that: The step of extracting a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy comprises: Calculating target feature line similarities of each renovated and expanded roadbed sub-region image in a sequence of renovated and expanded roadbed sub-region images, wherein a target feature line similarity is the sum of feature line similarities between a certain roadbed structure feature line of a certain renovated and expanded roadbed sub-region image and other roadbed structure feature lines of other renovated and expanded roadbed sub-region images in the sequence of renovated and expanded roadbed sub-region images; The reconstruction and expansion roadbed sub-region image corresponding to the maximum target similarity is defined as a target reconstruction and expansion roadbed sub-region image.

5. The construction quality inspection method for roadbed reconstruction and expansion according to claim 1 is characterized in that: The construction quality indicators for each target roadbed reconstruction and expansion sub-area include: The compaction stability of each target sub-area of ​​the roadbed for reconstruction and expansion is calculated based on the standard deviation of the vibration VCV value, rolling speed, and number of passes of each target sub-area of ​​the roadbed for reconstruction and expansion, and the compaction uniformity of each target sub-area of ​​the roadbed for reconstruction and expansion is calculated based on the sample proportion of the specific value of the minimum grid number of rolling passes of each target sub-area of ​​the roadbed for reconstruction and expansion; The construction quality index of each target reconstruction and expansion roadbed sub-area is calculated based on the compaction stability and compaction uniformity.

6. A construction quality inspection system for roadbed reconstruction and expansion, characterized in that: include: a division module configured to obtain at least one degree of connection between the original road surface and the rebuilt and expanded roadbed area, and divide the rebuilt and expanded roadbed area according to the at least one degree of connection using a preset area division rule to obtain at least one rebuilt and expanded roadbed sub-area, wherein the original road surface is a road surface connected to the rebuilt and expanded roadbed and not rebuilt and expanded; The analysis module is configured to obtain image information of the at least one rebuilt and expanded roadbed sub-region, obtain at least one rebuilt and expanded roadbed sub-region image, and analyze the at least one rebuilt and expanded roadbed sub-region image based on a preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-region to obtain at least one rebuilt and expanded roadbed sub-region image sequence, wherein the analyzing the at least one rebuilt and expanded roadbed sub-region image based on the preset image processing strategy according to the position information of the at least one rebuilt and expanded roadbed sub-region to obtain at least one rebuilt and expanded roadbed sub-region image sequence includes: Arranging the at least one rebuilt and expanded roadbed sub-region image in spatial order according to a splicing position of the rebuilt and expanded roadbed sub-region relative to the original road surface to generate an initial image sequence; Grayscale processing is performed on each of the reconstructed and expanded roadbed sub-region images in the initial image sequence, and an edge detection algorithm is used to extract the roadbed structure characteristic lines; Calculating the characteristic line similarity between each roadbed structure characteristic line, and dividing at least two roadbed structure characteristic lines whose characteristic line similarity is greater than a preset similarity threshold into the same reconstruction and expansion roadbed sub-region image sequence, to obtain at least one reconstruction and expansion roadbed sub-region image sequence; an extraction module configured to extract a target reconstruction and expansion roadbed sub-region image from the at least one reconstruction and expansion roadbed sub-region image sequence according to a preset image extraction strategy, and define the reconstruction and expansion roadbed sub-region corresponding to each target reconstruction and expansion roadbed sub-region image as the target reconstruction and expansion roadbed sub-region; The fusion module is configured to determine the construction quality index of each target reconstruction and expansion roadbed sub-area, and fuse the construction quality indexes according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area to obtain the target construction quality index of the reconstruction and expansion roadbed area, wherein the target construction quality index of the reconstruction and expansion roadbed area obtained by fusing the construction quality indexes according to the number of images in the image sequence of each reconstruction and expansion roadbed sub-area includes: Obtaining the number of images of the rebuilt and expanded roadbed sub-area in each rebuilt and expanded roadbed sub-area image sequence; Assigning a weight coefficient to each construction quality indicator according to a ratio of the number of images corresponding to each reconstruction and expansion roadbed sub-area image sequence to the total number of images, wherein the total number of images is the sum of the number of images of the reconstruction and expansion roadbed sub-area in all reconstruction and expansion roadbed sub-area image sequences; The various construction quality indicators are weighted and integrated according to the various weight coefficients to obtain the target construction quality indicators of the roadbed reconstruction and expansion area.

7. An electronic device, characterized in that: include: At least one processor, and a memory communicatively connected to the at least one processor, wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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