Compaction quality detection method of road roller and road roller detection system

Abstract

The invention discloses a compaction quality detection method of a road roller and a road roller detection system.The road area rolled by the road roller comprises a plurality of grids, and the compaction quality detection method is characterized by comprising the steps that S1, the rolling area between continuous coordinate points is determined; s2, assigning an elevation value to the grid in the rolling area; and S3, the rolling layer position and the number of times of compaction of the grid Pi are determined. And the intelligent rolling layer position is automatically identified, and the compaction times, the compaction thickness and the compaction degree are calculated.

Description

Technical Field

[0001] This invention relates to the field of compaction quality testing of road rollers and a road roller testing system. Background Technology

[0002] In recent years, research on compaction trajectory monitoring and related algorithms based on high-precision GPS has become a hot topic. Some researchers, both domestically and internationally, have used algorithms to monitor compaction trajectories and the number of compaction passes by installing high-precision positioning modules on road rollers. However, few of these methods address the crucial aspects of automatic identification of compaction layers and calculation of compaction thickness. Most intelligent compaction systems treat compaction layers as part of the engineering information, requiring manual input. During the horizontal layered construction of roadbeds, compaction quality is specific to a particular layer. Failure to identify different compaction layers will lead to confusion in the statistical analysis of compaction passes between layers, making it impossible to match compaction test indicators with the compaction layers. Manually dividing layers defeats the purpose of intelligent compaction and hinders its practical application.

[0003] Furthermore, compaction state refers to the distribution of physical and mechanical properties during the formation of the subgrade system, characterizing the subgrade structure's behavior during this process. Compaction quality is monitored through the collection and analysis of various information during the compaction construction process to ensure it meets prescribed standards. Compaction quality assessment is divided into physical and mechanical indicators. Mechanical indicators mainly include subgrade coefficient, deflection, and CBR, and are applied in railway engineering; the physical indicator is the degree of compaction, which is the primary indicator used for highway quality assessment. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for detecting the compaction quality of a road roller, in order to solve the problems existing in the prior art.

[0005] To address the aforementioned problems, a first aspect of the present invention provides a method for detecting the compaction quality of a road roller, wherein the road area compacted by the road roller comprises multiple grids, and the method for detecting the compaction quality includes:

[0006] S1: Determine the compaction zone between consecutive coordinate points.

[0007] The coordinates of the road roller A were continuously acquired. n The compaction area and the grid within the compaction area are determined based on two consecutive coordinate points.

[0008] S2: Assign elevation values ​​to the grid within the compaction area.

[0009] In step S1, the two consecutive coordinate points A n and A n+1 The elevation values ​​are known and are respectively HAn and H An+1 All grid cells within the compaction area are assigned an elevation value H, where H = (H... An +H An+1 ) / 2, any one of the grids P within the compaction area i The raster information is P i (X) i Y i H), X i Y i H and H represent the x-coordinate, y-coordinate, and elevation value, respectively.

[0010] S3: Determine the grid P i The compaction layers and the number of compaction passes,

[0011] S31: Search the database for all the grids within the compaction area; if all the grids within the compaction area have historical data, proceed to S32; if all the grids within the compaction area do not have historical data, proceed to S33; if some of the grids within the compaction area have historical data, proceed to S32 to preferentially determine the compaction layer and number of compaction passes for the grids with historical data, and proceed to S34 to determine the compaction layer and number of compaction passes for the grids without historical data;

[0012] S32: Transfer the grid P i The most recent historical data serves as the basis for subsequent identification of compacted layers, and the grid P i The basic data is P i (X) i Y i H', L i B i ), where X i Y i H', L i B i These represent the x-axis, y-axis, historical elevation values, historical compaction layers, and historical number of compaction passes, respectively; using the critical elevation difference index H... aim For the grid P i The layer determination, if the grid P i Satisfying H-H'>H aim At that time, the grid P i The compacted layer is L i+1 The number of compaction passes is 1, and the grid P i The raster information is P i (X) i Y i H, L i+1 , 1); if the grid P i Satisfying H-H'≤Haim At that time, the grid P i The compacted layer is L i The number of compaction passes is B. i+1 The grid P i The raster information is P i (X) i Y i H, L i B i+1 );

[0013] S33: The grid P i The compaction layer is 1, the number of compaction passes is 1, and the grid P i The raster information is P i (X) i Y i H, 1, 1);

[0014] S34: The raster P without historical data i The compaction layer is the same as the compaction layer of the grid with historical data in the compaction area, the number of compaction passes is 1, and the grid P i The raster information is P i (X) i Y i H, L i or L i+1 ,1).

[0015] Optionally, the compaction quality testing method further includes:

[0016] S4: Determine the grid P i The compaction thickness,

[0017] The grid P within the compaction area is analyzed using the inverse distance weighting method. i The optimized elevation value is assigned, and the compaction thickness is calculated.

[0018] Optionally, step "using the inverse distance weighting method to calculate the grid P within the compaction area" i "Assigning the optimized elevation value" includes:

[0019] Any one of the grids P within the road area i The raster information is P i (X) i Y i H i ), X i Y i H i These represent the x-axis, y-axis, and optimized elevation values, respectively; (X... i Y iA circular region is identified with the coordinate point A as the center, and the circular region includes at least one coordinate point A with a known elevation value. n (X) n Y n H An The grid P i to the coordinate point A n Distance D n and the grid P i The optimized elevation value H i They are respectively:

[0020]

[0021]

[0022] Optionally, the step "Calculate compaction thickness" includes:

[0023] Any one of the grids P within the road area i The optimized elevation values ​​for the Lth and L+1th layers are respectively H i (L+1) and H i (L), the grid P i The compaction thickness ΔH=H i (L+1)-H i (L).

[0024] Optionally, the critical elevation difference index H aim Less than the minimum height difference between layers (minimum compacted thickness).

[0025] Optionally, the step "continuously acquires the coordinates A of the road roller" n "Determining the compaction area and the grid within the compaction area based on two consecutive coordinate points" includes:

[0026] The coordinates of the road roller A were continuously acquired. n Based on two consecutive coordinate points A1(X1, Y1) and A2(X2, Y2), a rectangular compaction area and the grid within the rectangular compaction area are determined. The four vertices of the rectangular compaction area are O1, O2, O3, and O4, respectively. The width of the roller wheel is 2L. With the two coordinate points A1 and A2 as the feet of the perpendicular, a perpendicular line is drawn to line segment A1A2. The perpendicular lines are extended along both sides by half the length of the wheel width L, thus obtaining the rectangular compaction area enclosed by the four points O1, O2, O3, and O4.

[0027] If the area of ​​the grid within the rectangular compaction area exceeds 1 / 2 of the area of ​​a single grid, then the grid is determined to be within the rectangular compaction area.

[0028] Optionally, the formula for calculating the compaction degree (CMV) of the road area is as follows:

[0029]

[0030] Wherein, K is a constant value, calibrated through actual engineering; A1 is the amplitude of the first harmonic of the vibration acceleration response signal of the roller; and A0 is the amplitude of the excitation frequency of the vibration acceleration response signal of the roller.

[0031] Optionally, when the roller is working continuously, steps S1 to S3 are repeated to calculate the compaction layer position and the number of compaction passes of the grid in at least one of the compaction areas; when the roller stops working, step S4 is executed to calculate the compaction thickness of the grid.

[0032] Optionally, after completing the identification of a compaction layer and the calculation of the number of compaction passes for all the grids in a compaction area, the grid information of all the grids is stored in the database as historical data for the next time the roller passes through the compaction area.

[0033] A second aspect of the present invention provides a road roller detection system, wherein the road area compacted by the road roller comprises multiple grids, and the road roller controller includes a signal acquisition unit and a processing unit, wherein the signal acquisition unit continuously acquires the coordinates A of the road roller. n The processing unit receives the coordinate point A. n Coordinate information A n (X) n Y n H An ), X n Y n H An The x-axis, y-axis, and known elevation values ​​are respectively used to calculate one or more of the following: the compaction layer position, number of compaction passes, compaction thickness, and degree of compaction of the grid, according to the compaction quality detection method described in the first aspect of the invention.

[0034] The beneficial effects of this invention are: intelligent automatic identification of compaction layers and calculation of the number of compaction passes, compaction thickness and compaction degree. Attached Figure Description

[0035] Figure 1 A model diagram of the calculation method for determining the compaction area and the grid within the compaction area based on two consecutive coordinate points in Embodiment 1 of the present invention; Figure 2 This invention, in Embodiment 1, utilizes the inverse distance weighting method to analyze the grid P within the compaction area. i A model diagram of the method for calculating optimized elevation values; Figure 3This is a schematic diagram of the minimum height difference (minimum compacted thickness) between layers in Embodiment 1 of the present invention; Figure 4 The spectral characteristics of the vibration wheel response signal under different compaction states in Embodiment 1 of the present invention; Figure 5 This is a schematic diagram of the test points in the first compacted layer of the experimental example of the present invention; Figure 6 This is a schematic diagram of the test points in the second compacted layer of the experimental example of the present invention. Detailed Implementation

[0036] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so as to better understand the purpose, features and advantages of the present invention. It should be understood that the embodiments shown in the drawings are not intended to limit the scope of the present invention, but are only for illustrating the essential spirit of the technical solution of the present invention.

[0037] In the following description, certain specific details are set forth for the purpose of illustrating various disclosed embodiments in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the art will recognize that the embodiments may be practiced without one or more of these specific details. In other instances, well-known apparatuses, components, and techniques associated with this application may not have been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0038] Throughout this specification, references to "an embodiment" or "an embodiment" indicate that a particular feature, component, or characteristic described in connection with the embodiment is included in at least one embodiment. Therefore, the appearance of "in an embodiment" or "an embodiment" in various places throughout the specification does not necessarily refer to the same embodiment. Furthermore, a particular feature, component, or characteristic may be combined in any manner in one or more embodiments.

[0039] In the following description, in order to clearly demonstrate the components and working method of the present invention, a number of directional terms will be used. However, terms such as "front", "back", "left", "right", "outer", "inner", "outward", "inward", "up", and "down" should be understood as convenient terms and not as limiting terms.

[0040] Furthermore, terms such as "horizontal," "vertical," and "sag" do not imply that a component must be absolutely horizontal or suspended, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal relative to "vertical," and does not mean that the component must be completely horizontal, but can be slightly tilted.

[0041] In the description of this application, it should also be noted that, unless otherwise expressly specified and limited, the terms "set up," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0042] Example 1

[0043] This embodiment provides a method for detecting the compaction quality of a road roller. The road area compacted by the road roller includes multiple grids. The method for detecting the compaction quality includes:

[0044] S1: Determine the compaction zone between consecutive coordinate points.

[0045] Continuously acquire the coordinates of point A of the road roller n The compaction zone and the grid within the compaction zone are determined based on two consecutive coordinate points.

[0046] S2: Assign elevation values ​​to the grid within the compaction area.

[0047] In step S1, two consecutive coordinate points A n and A n+1 The elevation values ​​are known and are respectively H An and H An+1 All grid cells within the compaction area are assigned an elevation value H, where H = (H An +H An+1 ) / 2, any grid P within the compaction area i The raster information is P i (X) i Y i H), X i Y i H and H represent the x-coordinate, y-coordinate, and elevation value, respectively.

[0048] S3: Determine grid P i The compaction layers and the number of compaction passes,

[0049] S31: Search the database for all grids within the compaction area; if all grids within the compaction area have historical data, proceed to S32; if all grids within the compaction area do not have historical data, proceed to S33; if some grids within the compaction area have historical data, proceed to S32 to prioritize determining the compaction layer and number of compaction passes for grids with historical data, and proceed to S34 to determine the compaction layer and number of compaction passes for grids without historical data.

[0050] S32: Move grid Pi Recent historical data serves as the foundation for subsequent layer identification; raster P i The basic data is P i (X) i Y i H', L i B i ), where X i Y i H', L i B i These represent the x-axis, y-axis, historical elevation values, historical compaction layers, and historical number of compaction passes, respectively; using the critical elevation difference index H... aim For grid P i Layer determination, if grid P i Satisfying H-H'>H aim At that time, grid P i The current compacted layer is L i+1 The current compaction pass count is 1, grid P i The raster information is P i (X) i Y i H, L i+1 ,1); if grid P i Satisfying H-H'≤H aim At that time, grid P i The current compacted layer is L i The current number of compaction passes is B. i+1 , grid P i The raster information is P i (X) i Y i H, L i B i+1 );

[0051] S33: Grid P i The current compaction layer is 1, the current compaction pass is 1, and the grid P... i The raster information is P i (X) i Y i H, 1, 1);

[0052] S34: Raster P with no historical data i The current compaction layer is the same as the current compaction layer with historical data grids in the compaction area, and the current compaction pass count is 1. Grid P i The raster information is P i (X) i Y i H, L i or L i+1 ,1).

[0053] It should be noted that if the compaction position of individual grids within the same compaction zone does not match the actual situation, it can be manually corrected after inspection and confirmation. It is understood that the compaction positions of grids within the same compaction zone should remain consistent after implementing the same construction plan.

[0054] In one embodiment of the present invention, the step "continuously acquires the coordinates of the road roller A" n "Determining the compaction zone and the grid within the compaction zone based on two consecutive coordinate points" includes:

[0055] Continuously acquire the coordinates of the road roller at point A n Based on two consecutive coordinate points A1(X1, Y1) and A2(X2, Y2), a rectangular compaction area and a grid within the rectangular compaction area are determined. The four vertices of the rectangular compaction area are O1, O2, O3, and O4, and the roller wheel width is 2L. A perpendicular line to line segment A1A2 is drawn with the two coordinate points A1 and A2 as the feet of the perpendicular. The perpendicular line is extended along both sides by half the length of the roller wheel width L, resulting in a rectangular compaction area enclosed by the four points O1, O2, O3, and O4. If the area of ​​a grid within the rectangular compaction area exceeds 1 / 2 of the area of ​​a single grid, then the grid is determined to be within the rectangular compaction area.

[0056] Specifically, a compaction zone can be formed between every two coordinate points, and the road area compacted by the road roller can be considered as a superposition of multiple compaction zones. Because the road roller travels at a low speed and the distance between adjacent coordinate points is relatively short, the compaction zone between consecutive coordinate points can be approximated as a rectangle. Using GPS antenna coordinates to represent the actual position of the road roller for simplified calculation, the calculation method for the compaction zone between two consecutive coordinate points (A1 and A2) is as follows: Figure 1 As shown

[0057] The roller wheel width is 2L. Draw perpendicular lines from points A1(X1, Y1) and A2(X2, Y2) to line segment A1A2. Extend these perpendicular lines along both sides by half the wheel width L. This results in a rectangle bounded by points O1, O2, O3, and O4. This rectangle represents the wheel track area formed by the roller from A1 to A2. Geometric calculations yield the coordinates of the four points as follows:

[0058] O1(X) O1 ,Y O1 The coordinates of point ) are:

[0059]

[0060] O2 (X) O2 ,Y O2 The coordinates of point ) are:

[0061]

[0062] O3 (X) O3 ,Y O3 The coordinates of point ) are:

[0063]

[0064] O4(X) O4 ,Y O4 The coordinates of point ) are:

[0065]

[0066] After the compaction zone is determined, all grids within the compaction zone are determined using the area dominance method. The area of ​​a grid can be 0.04m². 2 If the area of ​​a grid cell located within the rectangle formed by points O1, O2, O3, and O4 exceeds half the area of ​​a single grid cell (i.e., 0.02m), then... 2 If the grid is located within the compaction area, then all grid points within the compaction area can be identified. This provides the basis for further counting of compaction passes for the grid points within the wheel track range, and is the foundation for intelligent stratification and compaction thickness calculation.

[0067] In one embodiment of the present invention, the coordinates of the road roller A are continuously acquired. n The real-time GPS coordinates of the road roller can be obtained by continuously collecting data at a frequency of 1Hz. The grid size can be 20cm × 20cm. After coordinate transformation, the planar position of each point in the grid coordinate system is determined. Considering factors such as the width of the road roller and the antenna installation position, geometric calculations are used to determine all grids within the compaction area between every two consecutive points. The range of the compaction wheel tracks formed by consecutive GPS points is used as the research object for layer identification and calculation of related indicators. The GPS can be installed at the center of the top of the road roller.

[0068] In one embodiment of the present invention, the compaction quality testing method further includes:

[0069] S4: Determine the grid P i The compaction thickness,

[0070] The grid P within the compaction area is analyzed using the inverse distance weighting method. i Assign optimized elevation values ​​and calculate compaction thickness.

[0071] Specifically, during the identification of compaction layers, all P layers within the compaction area have been preliminarily identified. iInitial elevation values ​​were assigned to the points, but this method of setting the same elevation value for all points within the same area does not conform to the characteristic of continuous change in ground elevation. To obtain more accurate ground elevations, after construction, the elevations of all grid points within the compacted area were recalculated, and the elevations of unknown points were obtained by interpolation using the inverse distance weighting method to calculate the elevations of known points. Figure 2 As shown, step "using the inverse distance weighting method to calculate the grid P within the compaction area" i "Assigning optimized elevation values" includes:

[0072] Any grid P within the road area i The raster information is P i (X) i Y i H i ), X i Y i , h are the x-axis, y-axis, and optimized elevation values, respectively; with (X) i Y i A circular region is identified with the coordinate point A as the center, and the circular region includes at least one coordinate point A with a known elevation value. n (X) n Y n H An The grid P i to the coordinate point A n Distance D n and the grid P i Optimized elevation value H i They are respectively:

[0073]

[0074]

[0075] Specifically, the optimal elevation value for each unknown point in different compaction layers can be obtained using the inverse distance weighting method. The step "Calculate compaction thickness" includes:

[0076] Any grid P within the road area i The optimized elevation values ​​for the Lth and L+1th layers are H, respectively. i (L+1) and H i (L), the grid P i The compaction thickness ΔH=H i (L+1)-H i (L).

[0077] In one embodiment of the present invention, the critical elevation difference index H aim Slightly smaller than the minimum height difference (minimum compacted thickness) between layers.

[0078] Specifically, such as Figure 3 As shown, at the same location, the elevation value of layer L+1 is always greater than that of layer L, and there must be areas with small compaction thickness between different compaction layers. This provides the possibility of using elevation differences for layer identification. H aim The value of H should not be too large or too small. aim If the value is greater than the elevation difference between two compacted layers, it will not be effective in identifying the stratigraphic position, and will even classify situations where there is a change in stratigraphic position as having no change. aim The value should not be too small. If a slight increase in elevation at a certain location is used to determine a change in the compacted stratum, GPS elevation positioning errors might lead to areas without any increase in the compacted stratum being incorrectly identified as having such an increase. In summary, H... aim The value can be slightly smaller than the minimum height difference (minimum compacted thickness) between layers to ensure that all areas are correctly identified. The minimum elevation difference between layers can be obtained through field testing.

[0079] In one embodiment of the present invention, the formula for calculating the compaction degree (CMV) of the road area is as follows:

[0080]

[0081] Wherein, K is a constant value, calibrated through actual engineering; A1 is the amplitude of the first harmonic of the vibration acceleration response signal of the roller; and A0 is the amplitude of the excitation frequency of the vibration acceleration response signal of the roller.

[0082] Specifically, the Compaction Meter Value (CMV) index is used to assess the compaction degree of road areas. A vibration acceleration sensor is placed on the frame inside the vibratory drum of the roller. When the fill material is relatively loose, only the fundamental frequency component is present. As the number of compaction passes increases, the reaction force on the vibratory drum also intensifies, resulting in other frequency components besides the fundamental frequency. The first harmonic component is the main influencing factor. The CMV index reflects the compaction degree by assessing the degree of waveform distortion, which is expressed by the ratio of the first harmonic of the vibration response signal to the fundamental frequency. Figure 4 To illustrate the spectral characteristics of the vibratory wheel response signal under different compaction conditions, without vibration jumping, the first harmonic amplitude gradually increases as the packing becomes denser. The vibration acceleration sensor collects the vibration acceleration information of the vibratory wheel into the intelligent compaction monitoring system terminal. The system amplifies and filters the vibration acceleration signal, performs A / D digital-to-analog conversion, and then performs a fast Fourier transform to obtain the excitation frequency f0, the first harmonic frequency f1, the amplitude A0 of the excitation frequency, and the amplitude A1 of the first harmonic. Finally, the CMV value is calculated.

[0083] In one embodiment of the present invention, after identifying a compaction layer and calculating the number of compaction passes for all grids in a compaction area, the grid information (horizontal coordinate, vertical coordinate, elevation value, compaction layer and number of compaction passes) of all grids is stored in a database as historical data for the next time the roller passes through the compaction area.

[0084] In one embodiment of the present invention, when the roller is working continuously, steps S1 to S3 are repeated to calculate all rolling layers and all compaction passes of the grid in at least one rolling area; when the roller stops working (the server can use the fact that it has not received the roller's positioning data for a period of time as a criterion), step S4 is executed to calculate the compaction thickness of the grid.

[0085] In one embodiment of the present invention, the number of compaction passes and the compaction thickness within the road area of ​​the road roller are summarized as the basis for intelligent compaction detection index data matching and subgrade compaction quality control.

[0086] Example 2

[0087] This embodiment provides a road roller detection system. The road area compacted by the road roller includes multiple grids. The road roller controller includes a signal acquisition unit and a processing unit. The signal acquisition unit continuously acquires the coordinates A of the road roller. n The processing unit receives coordinate point A n Coordinate information A n (X) n Y n H An According to the compaction quality testing method in Example 1, calculate one or more of the following: the compaction layer position, the number of compaction passes, the compaction thickness, and the degree of compaction of the grid.

[0088] Experimental Example

[0089] To verify the accuracy of the compaction quality testing method described in Example 1, a test was conducted on the Tian'e to Beihai Highway (Pingtang to Tian'e Guangxi section), a financing + engineering general contracting section, with chainages from K0+000 to K15+635 and a total length of 15.621 km. A CLG6622E model road roller with a wheel width of 2.2 meters and a vehicle height of 3.13 meters was selected. A 50-meter-long and 5-meter-wide area was selected for testing, and the test was conducted in two layers. The first layer of compaction was performed first, as follows... Figure 5As shown, the vibratory roller's left wheel compacts twice along the left side line, then twice along the right side line, creating a 1.2-meter-wide overlapping area. This overlapping area is compacted four times. The first layer of compaction is then completed. A level is used to determine the relative elevation values ​​of 20 test points shown in the diagram. A handheld GPS device is used to record the planar positions of these points, which are then numbered: the 10 points on the left are numbered 1-10 from top to bottom, and the 10 points on the right are numbered 11-20 from top to bottom. Loose filling is then carried out in this area, followed by the second layer test. The compaction route for the second layer is the same as that for the first layer. Figure 6 As shown, for ease of comparison, the number of compaction passes for both routes in the two layers was adjusted to 3, creating a 1.2-meter-wide overlapping area of ​​wheel tracks. The overlapping area was compacted 6 times. After the two layers were compacted, a handheld GPS was used to lay out the previous 20 test points, and the relative elevation values ​​of these test points were recorded again with a level. The difference between the elevation values ​​of the first and second layers at each point was taken as the measured compaction thickness.

[0090] The test results are as follows:

[0091] (1) Automatic identification of rolling layers and calculation of the number of compaction passes

[0092] An automated stratification algorithm for subgrade construction was used to statistically analyze the stratification and compaction pass counts at 20 test points. As shown in Table 1, the actual compaction layer position at each test point was completely consistent with the calculated compaction layer position, and the calculated compaction pass count for each layer at each point was the same as the actual compaction pass count.

[0093] Table 1. Statistics on compaction layers and number of compaction passes

[0094]

[0095] (2) Compaction thickness error analysis

[0096] The measured compacted thickness and the calculated compacted thickness at 20 test points were compared, and the results are shown in Table 2. The error between the measured and calculated compacted thickness is less than ±5cm, which meets the requirements of actual engineering for compaction thickness control accuracy. The calculated elevations of layer 1 and layer 2 are the optimized elevation values ​​described in Example 1, which can be understood as the optimized elevation values ​​of layer 1 and layer 2, respectively.

[0097] Table 2. Statistics on Compacted Thickness Error

[0098]

[0099] The preferred embodiments of the present invention have been described in detail above. However, it should be understood that after reading the above teachings, those skilled in the art can make various alterations or modifications to the present invention. These equivalent forms also fall within the scope defined by the appended claims.

Claims

1. A method of detecting a compaction quality of a road roller, a road region to be rolled by the road roller including a plurality of grids, characterized by, The compaction quality detection method comprises: S1: determining a rolling area between continuous coordinate points, determining the rolling area and the grid in the rolling area according to two continuous coordinate points; S2: assigning an elevation value to the grid in the rolling area, The elevation values of two consecutive coordinate points A n and A n+1 in step S1 are H An and H An+1 , all the grid assignment elevation values in the rolling area are assigned the value H = (H An + H An+1 ) / 2; S3: determining the grid P i of the compacted layer position and the compaction passes, S31: in the rolling area, if all the grids have historical data, execute S32; if all the grids have no historical data, execute S33; if part of the grids have historical data, execute S32 first and then execute S34; S32: Transfer the grid P i The most recent historical data P i (X) i Y i H', L i B i ) as the basic data, where X i Y i H', L i B i These represent the x-axis, y-axis, historical elevation values, historical compaction layers, and historical number of compaction passes, respectively; using the critical elevation difference index H... aim For the grid P i The layer determination, if the grid P i Satisfying H-H'>H aim At that time, the grid P i The compacted layer is L i+1 The number of compaction passes is 1, P i (X) i Y i H, L i+1 , 1); if the grid P i Satisfying H-H'≤H aim At that time, the grid P i The compacted layer is L i The number of compaction passes is B. i+1 P i (X) i Y i H, L i B i+1 ); S33: the grid P i The rolling layer position is 1, and the compaction pass number is 1, P i (X i , Y i , H, 1, 1); S34: the grid P without historical data i The compaction horizon of the grid P is the same as the compaction horizon of the grid with historical data in the compaction area, the compaction pass is 1, P i (X i , Y i , H, L i or L i+1 , 1).

2. The method of claim 1, wherein The compaction quality detection method further comprises: S4: determining the compaction thickness of the grid P i of the grid P, using inverse distance weighting method on the grid P i Assign an optimized elevation value and calculate the thickness of the compacted layer.

3. The method of claim 2, wherein Step "using said inverse distance weighting method to the grid P i assigning the optimized elevation value" comprises: Any one of the grid P in the road area i Grid information is P i (X i , Y i , H i ), X i , Y i , H i is the abscissa, ordinate and optimization elevation value respectively; (X i , Y i ) as the center of the circular area identification, the circular area includes at least one known elevation value of the coordinate point A n (X n , Y n , H An ), the distance D i from the grid P n to the coordinate point A n and the optimization elevation value H i of the grid P i is respectively: ； 。 4. The method of claim 3, wherein The step of "calculating the compaction thickness" comprises: Any one of the grids P within the road area i The optimized elevation values ​​for the Lth and L+1th layers are respectively H i (L+1) and H i (L), the grid P i The compaction thickness ΔH=H i (L+1)-H i (L).

5. The method of claim 3, wherein The critical height difference indicator H aim Less than the minimum height difference between horizons.

6. The method of claim 1, wherein Step "continuously acquiring the coordinate points A of the road roller" n determining the rolling area and the grid within the rolling area according to two consecutive coordinate points A comprises: Continuously acquiring coordinate points A of the road roller n , determining a rectangular rolling area and the grid in the rectangular rolling area according to two continuous coordinate points A1 (X1, Y1) and A2 (X2, Y2), four vertices of the rectangular rolling area are O1, O2, O3 and O4 respectively, the road roller wheel width is 2L, the perpendicular line of line segment A1A2 is drawn with A1 and A2 as the foot points, and the length of half wheel width L is extended along two sides respectively, so that the rectangular rolling area surrounded by O1, O2, O3 and O4 is obtained; If the area of the grid located within the rectangular rolling area exceeds 1 / 2 of the area of a single grid, it is determined that the grid is located within the rectangular rolling area.

7. The method of claim 1, wherein The formula for calculating the compaction degree CMV of the road area is as follows: ； Wherein, K is a constant value; A1 is the amplitude of the first harmonic of the vibration acceleration response signal of the roller of the road roller; A0 is the amplitude of the excitation frequency of the vibration acceleration response signal of the roller of the road roller.

8. The method of claim 2, wherein When the road roller is continuously working, steps S1 to S3 are repeated to calculate the rolling layer position and the compaction number of the grid of at least one rolling area; when the road roller stops working, step S4 is executed to calculate the compaction thickness of the grid.

9. The method of claim 1, wherein After completing the rolling layer position identification and the compaction number calculation of all the grids of one rolling area, the grid information of all the grids is stored in a database as historical data for the next time the road roller passes through the rolling area.

10. A road roller detection system, a road area rolled by the road roller including a plurality of grids, characterized by, The road roller controller includes a signal acquisition unit and a processing unit. The signal acquisition unit continuously acquires the coordinates A of the road roller. n The processing unit receives the coordinate point A. n Coordinate information A n (X) n Y n H An ), X n Y n H An The horizontal axis, vertical axis, and known elevation value are respectively used to calculate one or more of the following in the compaction quality testing method according to any one of claims 1 to 9: the compaction layer position, number of compaction passes, compaction thickness, and compaction degree of the grid.

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