CN111583362A - Visual recording method for detecting asphalt pavement disease condition - Google Patents

Abstract

The invention discloses a visual recording method for manual detection of asphalt pavement disease conditions. Excel recording rules for type data, size data, and position data; import the original record table into MATLAB, generate damaged units according to type data, configure unit size according to size data, generate unit coordinates according to location information, and generate a 100-meter damage diagram of asphalt pavement. The invention is mainly used for the visual record of manual detection of asphalt pavement disease conditions, which facilitates the data collection and statistics of pavement disease investigation, and forms the visual original pavement data for manual inspection. Visually reflect the actual disease situation of asphalt pavement, so that management workers can see the intuitive image of pavement condition, help to deeply understand the process of pavement deterioration, and make a correct evaluation of pavement performance.

Description

A Visual Recording Method for Detection of Asphalt Pavement Disease Status

technical field

The invention belongs to the technical field of asphalt pavement use condition detection and evaluation, and is used for manual inspection and data recording of asphalt pavement disease conditions; in particular, it relates to a visual recording method for asphalt pavement disease condition detection.

Background technique

At this stage, the inspection of the usage condition of asphalt pavement still requires a lot of manual inspection. Generally, the "Highway Technical Condition Evaluation Standard" is used as a guide for data collection. The test data results have problems such as poor traceability, poor accuracy and stability. Researchers and managers can only carry out research and decision-making through the segmental calculation results of unit detection data, and lack an intuitive, concrete and visual grasp of the actual use of asphalt pavement.

SUMMARY OF THE INVENTION

Purpose of the invention: In view of the above problems existing in the existing inspection recording methods, a visual recording method of asphalt pavement disease condition detection data proposed by the present invention can truly restore the asphalt pavement disease condition on the premise of not departing from the requirements of the specification, and realize Data visualization of asphalt pavement disease status at the evaluation level. Such a recording method saves the original visual data of manual inspection without increasing the workload of the inspection personnel, which facilitates the statistics and traceability of the data, enables management workers to see an intuitive image of the road surface, and improves the performance of the road surface. Diversity of test data.

Technical solution: In order to achieve the purpose of the present invention, the present invention establishes a visual recording method for the detection of asphalt pavement disease conditions. Statistical results of road sections include the following steps:

(1) According to the type and degree of asphalt pavement disease, select the approximate edge shape of the asphalt pavement disease unit, and use MATLAB to establish the basic unit of the asphalt pavement damage type.

(2) Use Excel to create the "Original Record Table of Asphalt Pavement Damage Condition", the type, degree and center point position information of damaged units are entered by drop-down menu, and the size information of damaged units is entered manually.

(3) Use MATLAB to build a 100×L rectangular 100-meter pavement unit, where L is the width of the pavement, the X direction is the driving direction, the Y direction is the cross-sectional direction, and the 100-meter pavement unit is divided into upper, middle and lower along the X direction. Three parts for configuration and positioning of damaged units.

(4) Import the "Original Record Table of Asphalt Pavement Damage Status" into MATLAB, configure the damaged unit information, and generate the corresponding damaged unit on the 100-meter pavement unit according to the type, degree, center point position and size data of the damaged unit, and establish the asphalt 100-meter road damage icon.

In step (1), use MATLAB to write the basic unit generation file of asphalt pavement damage type. The required parameters are [X_ZB, Y_ZB, Length, Width, degree], which represent the x-coordinate, y-coordinate, length, width and severity, respectively, The basic types of asphalt pavement damage units are divided into 7 categories, and the judging criteria and basic unit generation methods are as follows:

(1-1) Cracking: the crack size is between 0.2 and 0.5m, and the average crack width is less than 2mm, which is a mild crack; the crack size is less than 0.2m, and the average crack width is between 2 and 5mm, which is a moderate crack; The crack size is less than 0.2m, and the average crack width is greater than 5mm as severe cracks.

The diseased cells are approximately converted into quadrilaterals, and the MATLAB program is used to generate the edge boundaries of blue polygons, the length is Length, and the width is Width. Use the UNIFIND function to generate random fractures, and generate random horizontal/longitudinal fractures with a fracture size of 0.2 to 0.5m and a fracture size of less than 0.2m for grid filling. The following two filling colors are selected: pink ([1,0.75294,0.79608] ), dark pink ([1, 0.07843, 0.57647]), indicating slight cracks, moderate/severe cracks.

(1-2) Massive cracks: The major cracks are larger than 1.0m in size, and the average crack width is between 1 and 2mm, which are mild massive cracks; the main cracks are between 0.5 and 1.0m in size, and the average crack width is greater than 2mm. Severe blocky cracks.

The diseased unit is approximately converted into a rectangle, and the MATLAB program is used to generate the edge boundary of the blue polygon. The length and width are configured according to the recorded data, and the length is Length and the width is Width. The green dotted line is used to offset inwardly to generate block cracks, and the offset distances are 0.5m and 1m respectively, indicating mild block cracks and severe block cracks.

(1-3) Cracks: longitudinal cracks are basically parallel to the driving direction, and transverse cracks are basically perpendicular to the driving direction.

The random crack generation function is written by the UNIFIND function, and the unit configuration is performed by using the length Length to generate longitudinal/transverse crack diagrams. Use green lines to generate longitudinal cracks, and sky blue ([0,0.74902,1]) lines to generate transverse cracks. The light crack line width is configured as default pixels, and the severe crack line width is configured as 2 pixels.

(1-4) Pit and groove: the depth of mild pit is less than 25mm, or the area is less than 0.1m2; the depth of severe pit is more than 25mm, or the area is greater than 0.1m2.

Generally, the diffusion form of the pit is circular or elliptical, with an area of less than 0.1m2 and an approximate diameter of less than 0.178m. Configure the length of the main axis according to the dimensions Length and Width of the pit, and generate an orange ([1,0.54902,0]) oval edge boundary. The light pit is filled with the red main shaft, and the heavy pit is filled with the blue main shaft.

(1-5) Repair: The repair adopts the rectangle conversion area method, and the rectangular unit is generated according to the size information Length and Width, and the repair unit is filled with the gray ([0.7451, 0.7451, 0.7451]) surface.

(1-6) For other surface defects such as oil splattering, looseness, etc., the area and position information are uniformly generated by rectangular conversion, and a blue rectangle is generated according to the size Length and Width. The rhombus is filled internally.

(1-7) The surface deformation damage such as subsidence, rutting, and crowding is uniformly used in the rectangular conversion method. The unit is configured according to the size information Length and Width, and a black rectangular boundary is generated. The surface deformation and disease units are filled with red curves.

In step (2), the original recording method is provided in the form of an Excel table, and an "original record table of asphalt pavement damage conditions" is created, in which the length and width information of the diseased unit is manually entered, and the type, degree and center point position information of the diseased unit are entered. Create a drop-down menu through Excel data validation, set limited options, and select the corresponding option to enter.

When creating the "Asphalt Pavement Damage Condition Original Record Sheet", the disease unit type qualification options are set as follows: Cracking Disease, Block Crack, Longitudinal Crack, Transverse Crack, Subsidence Disease, Rutting Disease, Wave Packing, Pothole Disease, Loose Disease , oily disease, repair disease.

The disease location limitation options are set as follows: left driving belt, right driving belt, driving lane center line, left edge line, right edge line (Y direction); upper, middle, lower (X direction).

In step (3), the x coordinate range of the 100-meter pavement unit is X∈[-50, 50], which is divided into upper, middle and lower parts along the X direction, and the upper coordinate range is X∈[-50, -20], The middle coordinate range is X ∈ [-20, 20], and the lower coordinate range is X ∈ [20, 50].

In step (4), the 100-meter damage icon of the asphalt pavement is determined by the following steps:

(4-1) Use MATLAB to read the survey data in the "Original Record Table of Asphalt Pavement Damage Conditions", read the size and shape data raw(i,5) of the damaged unit, judge the unit of measurement of the damaged unit, and extract the length information "length_i" ", width information "width_i", and degree information "degree".

(4-2) Generate the X coordinate of the center point of the damaged unit: judge the longitudinal positioning data of the center point position information recorded by raw(i,8), determine the X coordinate range of the damaged unit, and the damaged unit on the 100-meter road unit and the drawing amplitude (upper/middle/lower), the specific damage element center point x coordinate value matrix "x_ZB" is generated using the spacing constraint of "2(X-Xi)>(length+lengthi)".

(4-3) Generate the Y coordinate of the center point of the damaged unit: judge the cross-sectional positioning data of the center point position information recorded by raw(i,9) (left/right wheel track belt, lane center line, left/right side edge) to generate a matrix "y_ZB" of the y-coordinate value of the center point of the damaged cell.

(4-4) Read the type data of the damaged unit, verify the damaged type data recorded by raw(i, 2), and generate the damage unit type judgment result matrix "degree".

(4-5) Using [X_ZB_i, Y_ZB_i, Length_i, Width_i, degree_i] read in steps (13) to (16) as parameters, call the corresponding MATLAB damage type basic unit to generate a file, and generate a 100-meter damage diagram for asphalt pavement .

Beneficial effects: Compared with the prior art, the technical solution of the present invention has the following beneficial technical effects: the present invention can assist inspectors to save the original inspection data, facilitate the collection and recording of data, and at the same time truly restore the disease state of the asphalt pavement and generate asphalt The 100-meter damage diagram of the pavement provides a visual solution for the manual detection method of asphalt pavement disease investigation.

Description of drawings

Fig. 1 is the flow chart of the method of the present invention;

Figure 2 is a 100-meter pavement unit of asphalt pavement (L=7m);

Figure 3 is a diagram showing the damage of 100 meters of asphalt pavement (L=7m);

Figure 4 is a 100-meter pavement unit of asphalt pavement (L=4m);

Figure 5 is a diagram showing the damage of 100 meters of asphalt pavement (L=4m).

Detailed ways

The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings and embodiments, but the protection scope of the present invention is not limited to the embodiments.

Example 1

The present invention is implemented in the manual inspection of the disease condition of a two-lane asphalt pavement with a width of 7 meters:

1. According to the type and degree of asphalt pavement disease, select the approximate edge shape of the asphalt pavement disease unit, use MATLAB to establish the basic unit of the asphalt pavement disease type, write the basic unit generation file of the asphalt pavement disease type, and set the input parameters as [X_ZB, Y_ZB, Length, Width, degree], representing the x-coordinate, y-coordinate, length, width and severity, respectively. The basic types of asphalt pavement damage units are divided into 7 categories, and the generation methods of the respective basic units are as follows:

(1) Cracks: The diseased unit is approximately converted into a quadrilateral, and the MATLAB program is used to generate the edge boundary of the blue polygon, the length is Length, and the width is Width. Use the UNIFIND function to generate random fractures, and generate random horizontal/longitudinal fractures with a fracture size of 0.2 to 0.5m and a fracture size of less than 0.2m for grid filling. The following two filling colors are selected: pink ([1,0.75294,0.79608] ), dark pink ([1, 0.07843, 0.57647]), indicating slight cracks, moderate/severe cracks.

(2) Block cracks: The diseased unit is approximately converted into a rectangle, and the MATLAB program is used to generate the edge boundary of the blue polygon. The length and width are configured according to the recorded data, and the length is Length and the width is Width. The green dotted line is used to offset inwardly to generate block cracks, and the offset distances are 0.5m and 1m respectively, indicating mild block cracks and severe block cracks.

(3) Cracks: use the UNIFIND function to write a random crack generation function, use the length Length to configure the unit, and generate longitudinal/transverse crack diagrams. Use green lines to generate longitudinal cracks, and sky blue ([0,0.74902,1]) lines to generate transverse cracks. The light crack line width is configured as default pixels, and the severe crack line width is configured as 2 pixels.

(4) Pit and groove: configure the length of the main shaft according to the size of the pit and groove, and generate an orange ([1,0.54902,0]) oval edge boundary. The light pit and groove are filled with the red main shaft, and the heavy pit and groove are filled with blue. The main axis is filled.

(5) Repair: The repair adopts the rectangle conversion area method, and generates a rectangular unit according to the size information Length and Width, and the repair unit is filled with gray ([0.7451, 0.7451, 0.7451]) surface.

(6) Other surface defects such as oil spills and looseness are uniformly generated by rectangular conversion area and position information. A blue rectangle is generated according to the size Length and Width. The oil spill damage unit is filled with random circles, and the looseness is carried out by random diamonds. Internal padding.

(7) The surface deformation damage such as subsidence, rutting, and crowding is uniformly used in the rectangular conversion method. The unit is configured according to the size information Length and Width, and a black rectangular boundary is generated. The surface deformation damage unit is filled with red curves.

2. Use Excel to create the "Original Record Table of Asphalt Pavement Damage Conditions". The type, degree, and center point position information of the diseased unit is entered in a drop-down menu, and the size information of the diseased unit is entered manually. The entry results are shown in Table 1.

Table 1 Original record of damage to asphalt pavement

3. Use MATLAB to build a 100m×7m rectangular 100-meter pavement unit, the X direction is the driving direction, the Y direction is the cross-sectional direction, and the 100-meter pavement unit is divided into upper, middle and lower parts along the X direction, which are used for damage units. The upper coordinate range is X ∈ [-50, -20], the middle coordinate range is X ∈ [-20, 20], and the lower coordinate range is X ∈ [20, 50], as shown in Figure 2.

4. Use MATLAB to read the survey data in Table 1, read the size and shape data of the damaged unit raw(i, 5), determine the measurement unit of the damaged unit, and extract the length information "length_i", width information "width_i" and degree information "degree".

Judge the longitudinal positioning data of the center point position information recorded by raw(i,8), determine the X coordinate range of the damaged unit, and the drawing amplitude (upper/middle/lower) of the damaged unit on the 100-meter pavement unit, The specific x-coordinate value matrix "x_ZB" of the center point of the damaged unit is generated using the spacing constraint of "2(X-Xi)>(length+lengthi)".

Judging the cross-sectional positioning data of the center point position information recorded by raw(i,9) (left/right wheel track belt, lane center line, left/right side edge), and generating the center point y coordinate value matrix of the damaged unit "y_ZB".

Read the type data of the damaged unit, verify the damaged type data recorded by raw(i,2), and generate the damage unit type judgment result matrix "degree".

Table 2 Parameters required to generate files for damaged cells

Numbering x y Length Width degree 1 -6.4451 5.25 3 3 light 2 41.7960 4.00 2 0.5 light 3 46.5604 4.00 2 0 Heavy 4 0.4304 4.00 3 2 middle 5 -30.7717 3.50 3.5 0 light 6 14.0717 5.25 3 0.8 light 7 48.0709 5.25 0.5 1 light 8 25.5634 3.50 2 0 Heavy 9 -37.0244 5.25 2 0.3 Heavy 10 -23.3521 5.25 5 3 light 11 -44.2013 4.00 1 2 light 12 -34.4465 6.50 2 0 light 13 7.0464 6.50 0.4 0.2 light 14 31.7471 4.00 0.3 0.3 Heavy 15 18.1866 6.50 1 0.5 light

5. Taking the generated information matrix X_ZB, Y_ZB, Length, Width, and degree as parameters, call the basic unit of damage type to generate a file, and generate a 100-meter damage diagram of asphalt pavement as shown in Figure 3.

Example 2

The present invention is implemented in the manual inspection of the disease condition of a certain single-lane asphalt pavement with a width of 4 meters:

1. Same as step 1 in Example 1.

2. Use Excel to create the "Original Record of Asphalt Pavement Damage Condition", the results are shown in Table 3.

Table 3 The original record of damage to asphalt pavement

3. Use MATLAB to build a 100m×4m rectangular pavement unit of 100 meters, which is divided into upper, middle and lower parts, as shown in Figure 4.

4. Use MATLAB to read the survey data configuration unit information in Table 3, and generate damaged unit parameters as shown in Table 4.

Table 4 Parameters required to generate files for damaged cells

Numbering x y Length Width degree 1 23.1937 3.00 1 0.5 light 2 -33.7511 3.50 2 0.5 light 3 -40.4669 3.00 0.3 0.5 Heavy 4 37.4312 1.00 3 2 middle 5 47.2081 2.25 3.5 0 light 6 10.8742 2.25 3 0.8 light 7 0.2150 1.00 0.5 1 light 8 30.1787 1.50 2 0.5 Heavy 9 -22.5280 2.25 2 0.8 Heavy 10 -46.1073 3.00 3 1 light 11 18.7188 2.25 2.5 0 light 12 43.3990 1.50 2 0 light 13 -27.8362 2.25 3 3 light 14 -15.4444 1.50 1.5 0 Heavy 15 -11.7925 2.25 1 0.5 light

5. Taking the generated information matrix X_ZB, Y_ZB, Length, Width, and degree as parameters, call the basic unit of damage type to generate a file, and generate a 100-meter damage diagram of asphalt pavement as shown in Figure 5.

Comparing the original record table, the parameter generation table and the 100-meter damage diagram, it can be seen that: in the test link of the asphalt pavement investigation data of different widths, the visualization method of the asphalt pavement damage investigation of the present invention can quickly and accurately restore the damage diagram of the asphalt pavement , which proves the accuracy and universality of the present invention.

The technical means disclosed in the solution of the present invention are not limited to the technical means disclosed in the above embodiments, but also include technical solutions composed of any combination of the above technical features. It should be pointed out that for those skilled in the art, without departing from the principle of the present invention, several improvements and modifications can be made, and these improvements and modifications are also regarded as the protection scope of the present invention.

Claims (5)

1. A visual recording method for detecting asphalt pavement disease conditions is characterized by comprising the following steps:

(1) selecting the edge shape of the asphalt pavement disease unit according to the type and degree of the asphalt pavement disease, and establishing an asphalt pavement damage type basic unit by using MATLAB;

(2) creating an original record table of the asphalt pavement damage condition by using Excel, inputting the type and degree of a damaged unit and the position information of a central point in a pull-down menu mode, and inputting the size information of the damaged unit in a manual mode;

(3) adopting MATLAB to establish a 100 multiplied by L rectangular hectometer pavement unit, wherein L is the width of a pavement, X direction is the driving direction, Y direction is the cross section direction, and the hectometer pavement unit is divided into an upper part, a middle part and a lower part along the X direction and is used for configuring and positioning a damaged unit;

(4) and importing an original record table of the damage condition of the asphalt pavement into MATLAB, configuring damage unit information, generating corresponding damage units on hectometer pavement units according to the type, degree, central point position and size data of the damage units, and establishing a hectometer damage diagram of the asphalt pavement.

2. The visual recording method for detecting the disease condition of the asphalt pavement according to claim 1, wherein in the step (1), MATLAB is used to write basic unit generating files of the damage type of the asphalt pavement, the required parameters are [ X _ ZB, Y _ ZB, Length, Width, depth ], which respectively represent X coordinate, Y coordinate, Length, Width and severity, the basic types of the damage units of the asphalt pavement are classified into 7 categories, and the criteria and the basic unit generating method are as follows:

(1-1) cracking: the crack block degree is 0.2-0.5 m, and the average crack width is less than 2mm, so that the crack is slight; the crack block size is less than 0.2m, and the average crack width is 2-5 mm, so that the crack is moderate; the crack block size is less than 0.2m, and the average crack width is more than 5mm, so that the crack is heavily cracked;

converting the disease unit into a quadrangle, and generating a blue polygon edge boundary by adopting an MATLAB program, wherein the Length is Length, and the Width is Width; generating random cracks by adopting a UNIFIND function, carrying out grid filling on the generated random transverse/longitudinal cracks with the crack block degree of 0.2-0.5 m and the crack block degree of less than 0.2m, and selecting the following 2 filling colors: pink ([1,0.75294,0.79608]), dark pink ([1,0.07843,0.57647]), representing mild cracking, moderate/severe cracking in that order;

(1-2) bulk cracking: the main crack has the bulk degree larger than 1.0m, and the average crack width is 1-2 mm, so that the crack is a slight bulk crack; the main crack block degree is 0.5-1.0 m, and the severe block cracks are formed when the average crack width is more than 2 mm;

converting the disease unit into a rectangle, generating a blue polygon edge boundary by adopting an MATLAB program, configuring the Length and the Width according to the recorded data, wherein the Length is Length, and the Width is Width; selecting a green dotted line to bias inwards to generate a block crack diagram, wherein the bias distances are 0.5m and 1m respectively, and the block crack diagram represents slight block crack and severe block crack;

(1-3) cracking: the longitudinal cracks are parallel to the driving direction, the transverse cracks are vertical to the driving direction, the severity degree takes the crack width of 3mm as a boundary, the cracks with the width more than 3mm are severe cracks, and the cracks with the width less than 3mm are mild cracks;

compiling a random crack generation function by using a UNIFIND function, and performing unit configuration by using a Length to generate a longitudinal/transverse crack diagram; selecting green lines to generate longitudinal cracks, and selecting sky blue ([0,0.74902,1]) lines to generate transverse cracks; the line width of the slight crack is configured as a default pixel, and the line width of the severe crack is configured as 2 pixels;

(1-4) pit: the depth of the light pit is less than 25mm, or the area is less than 0.1m²(ii) a The depth of the heavy pit is more than 25mm, or the area is more than 0.1m²；

The diffusion form of the pit groove is circular or elliptical, and the area is less than 0.1m²Approximately less than 0.178m in diameter; the spindle Length is set according to the Length and Width of the pit slot to generate orange color ([1,0.54902, 0)]) The edge of the oval is limited, the light pit is filled by adopting a red main shaft, and the heavy pit is filled by adopting a blue main shaft;

(1-5) repairing: the method comprises the steps of generating rectangular units according to size information Length and Width by adopting a rectangular conversion area mode for repairing, and filling the repairing units by adopting gray ([0.7451,0.7451,0.7451]) surfaces;

(1-6) uniformly generating other surface defect diseases by adopting rectangle conversion area and position information, generating blue rectangles according to the sizes of Length and Width, filling the inside of the oil-flooding disease unit in a random circle mode, and filling the inside of the oil-flooding disease unit in a loose mode in a random rhombus mode;

and (1-7) uniformly performing surface deformation damage by adopting a rectangular conversion mode, performing unit configuration according to the size information Length and Width to generate a black rectangular boundary, and performing internal filling on the surface deformation damage unit by adopting a red curve.

3. The visual recording method for the artificial detection of the asphalt pavement damage condition as claimed in claim 1, characterized in that in step (2), an original recording mode is provided in the form of Excel table, and an "original recording table of asphalt pavement damage condition" is created, wherein the length and width information of the damage unit is manually entered, the type, degree and center point position information of the damage unit are used to establish a pull-down menu through Excel data verification mode, set the limited option, select the corresponding option to enter;

when creating the "original record table of the damaged condition of the asphalt pavement", the options for defining the types of the damaged units are set as follows: cracking diseases, block cracks, longitudinal cracks, transverse cracks, sinking diseases, track diseases, wave congestion, pit slot diseases, loosening diseases, oil bleeding diseases and repairing diseases;

the disease location restriction options are set as follows: a left driving belt, a right driving belt, a driving lane central line, a left edge line and a right edge line (Y direction); upper, middle, lower (X direction).

4. The visual recording method for detecting the disease state of asphalt pavement according to claim 1, wherein in the step (3), the X-coordinate range of the hectometer pavement unit is X e-50, the hectometer pavement unit is divided into an upper part, a middle part and a lower part along the X direction, the upper coordinate range is X e-50, -20, the middle coordinate range is X e-20, and the lower coordinate range is X e [20, 50 ].

5. The visual recording method for detecting the disease condition of the asphalt pavement as claimed in claim 1, wherein in the step (4), the hundred meter damage graphic representation of the asphalt pavement is determined by the following steps:

(4-1) reading survey data in an original record table of the asphalt pavement damage condition by using MATLAB, reading size and shape data raw (i,5) of a damaged unit, judging a measuring unit of the damaged unit, and extracting length information 'length _ i', width information 'width _ i' and degree information 'degree';

(4-2) generating a damaged cell center point X coordinate: judging the longitudinal positioning data of the central point position information recorded by raw (i,8), determining the X coordinate range of the damaged unit, the drawing positions (upper/middle/lower part) of the damaged unit on the hectometer pavement unit, and adopting 2 (X-X) as the specific X coordinate matrix of the damaged unit central point X-ZB_i)>(length+length_i) "spacing constraint mode generation;

(4-3) generating a damaged cell center point Y coordinate: judging the cross section positioning data (left/right side wheel track, center line of traffic lane, left/right side edge) of the central point position information recorded by raw (i,9) to generate a central point y coordinate value matrix 'y _ ZB' of the damaged unit;

(4-4) reading the type data of the damaged unit, verifying the damaged type data recorded in raw (i,2) and generating a damaged unit type judgment result matrix 'void';

and (4-5) calling the MATLAB damage type basic unit generation file corresponding to the parameter [ X _ ZB _ i, Y _ ZB _ i, Length _ i, Width _ i and depth _ i ] read in the steps (4-4) to generate a hectometre damage diagram of the asphalt pavement.

Images