Asphalt pavement distress assessment method and apparatus

Abstract

The present invention belongs to the technical field of road engineering, and relates to an asphalt pavement distress assessment method and apparatus. The method comprises: acquiring pavement service performance data and pavement structural performance data of an asphalt pavement; on the basis of the pavement service performance data, obtaining a pavement service performance index; then, on the basis of the pavement structural performance data, obtaining a pavement structural performance index; and further, on the basis of the pavement service performance index and the pavement structural performance index, determining a comprehensive performance assessment result for the asphalt pavement. Therefore, by means of a pavement service performance index and a pavement structural performance index, the inspection and assessment can be performed on an asphalt pavement, such that a comprehensive performance assessment result for the asphalt pavement is obtained, thereby improving the accuracy of pavement assessment.

Description

Asphalt pavement disease evaluation method and device TECHNICAL FIELD

[0001] The present application relates to the technical field of road engineering, and in particular to an asphalt pavement disease evaluation method and device. BACKGROUND

[0002] With the development of society, road infrastructure construction tends to be saturated, and early construction of expressways also faces the problem of gradual degradation of road performance. Therefore, the focus of the transportation industry will gradually shift to maintenance and repair work on existing roads. At present, the establishment of the road maintenance system mainly relies on the evaluation of road performance and road structure performance indicators, and then formulates targeted maintenance and repair schemes.

[0003] Because the road structure performance is hidden below the road surface, it is difficult to find and detect in place in time, so it is usually ignored in the road evaluation process. However, in fact, the road structure performance often has a greater impact on the degradation of the performance, so when evaluating the road, only evaluating the road performance will lead to inaccurate evaluation of the road.

[0004] Therefore, it is urgent to propose an asphalt pavement disease evaluation method and device to solve the technical problem of inaccurate road evaluation caused by the road evaluation method only evaluating the road performance in the prior art.

[0005] SUMMARY

[0006] Therefore, it is necessary to provide an asphalt pavement disease evaluation method and device to solve the technical problem of inaccurate road evaluation caused by the road evaluation method only evaluating the road performance in the prior art.

[0007] In order to solve the above problems, the present application provides an asphalt pavement disease evaluation method, comprising:

[0008] Obtaining road performance data and road structure performance data on the asphalt pavement;

[0009] According to the road performance data, a road performance index is obtained;

[0010] According to the road structure performance data, a road structure performance index is obtained;

[0011] According to the road performance index and the road structure performance index, a comprehensive performance evaluation result of the asphalt pavement is determined.

[0012] In a possible implementation, the road surface use performance data comprises a road surface damage rate, an international roughness index, a rut depth, a lateral force coefficient and a road surface bump height, and the road surface use performance index is obtained according to the road surface use performance data, comprising:

[0013] a road surface technical condition index is obtained according to the road surface damage rate;

[0014] a road surface driving quality index is obtained according to the international roughness index;

[0015] a road surface rut depth index is obtained according to the rut depth;

[0016] a road surface skid resistance performance index is obtained according to the lateral force coefficient;

[0017] a road surface bump index is obtained according to the road surface bump height;

[0018] a road surface use performance index is obtained according to the road surface technical condition index, the road surface driving quality index, the road surface rut depth index, the road surface skid resistance performance index and the road surface bump index.

[0019] In a possible implementation, the road surface structure performance data comprises crack disease data and road surface structure data, and the road surface structure performance index is obtained according to the road surface structure performance data, comprising:

[0020] an average crack depth is obtained according to the crack disease data;

[0021] deflection data is obtained according to the road surface structure data, and the road surface structure performance index comprises the average crack depth and the deflection data.

[0022] In a possible implementation, the comprehensive performance evaluation result of the asphalt road surface is determined according to the road surface use performance index and the road surface structure performance index, comprising:

[0023] factor rotation processing is performed on the road surface use performance index and the road surface structure performance index based on a maximum variance method, to obtain a cumulative variance explanation rate and a rotated factor loading coefficient;

[0024] at least one principal factor is determined according to the cumulative variance explanation rate;

[0025] a principal factor score of each principal factor corresponding to each index is obtained according to the rotated factor loading coefficient;

[0026] the comprehensive performance evaluation result of the asphalt road surface is obtained according to the road surface use performance index, all principal factor scores and the cumulative variance explanation rate.

[0027] In a possible implementation, the asphalt pavement comprehensive performance evaluation result is obtained according to the pavement performance index, the scores of all main factors and the cumulative variance explained rate.

[0028] The index value corresponding to each main factor is obtained according to the score of each main factor corresponding to all indexes;

[0029] The weight of each main factor is determined according to the cumulative variance explained rate.

[0030] The asphalt pavement comprehensive performance evaluation result is obtained according to the index value, the pavement performance index, all main factors and all weights.

[0031] In a possible implementation, the cumulative variance explained rate includes a post-rotation variance explained rate and a post-rotation cumulative variance explained rate, and the weight of each main factor is determined according to the cumulative variance explained rate, including:

[0032] The target variance explained rate is determined according to the post-rotation cumulative variance explained rate;

[0033] The weight of each main factor is obtained according to the target variance explained rate and the post-rotation variance explained rate corresponding to each main factor.

[0034] In a possible implementation, the asphalt pavement comprehensive performance evaluation result is obtained according to the index value, the pavement performance index, all main factors and all weights, including:

[0035] The pavement maintenance level index is obtained according to the index value, all main factors and all weights.

[0036] The road sections detected on the asphalt pavement are sorted according to the pavement performance index and the pavement maintenance level index respectively to obtain corresponding sorting results.

[0037] The asphalt pavement comprehensive performance evaluation result is obtained according to the sorting result of the pavement performance index and the sorting result of the pavement maintenance level index.

[0038] In a possible implementation, before the asphalt pavement comprehensive performance evaluation result is obtained according to the pavement performance index and the pavement structure performance index, the method further includes:

[0039] The pavement performance index and the pavement structure performance index are tested based on KMO test and Bartlett sphericity test to obtain corresponding test results.

[0040] According to the test result of the KMO test and the test result of the Bartlett sphericity test, the reliability of the comprehensive performance evaluation result of the asphalt pavement is determined.

[0041] In a possible implementation, the asphalt pavement usage performance data and the pavement structure performance data on the asphalt pavement are acquired by:

[0042] The asphalt pavement is detected based on an asphalt pavement usage performance detection vehicle to obtain the pavement usage performance data.

[0043] The asphalt pavement is detected based on a ground penetrating radar and a falling weight deflectometer to obtain the pavement structure performance data.

[0044] In another aspect, the present application further provides an asphalt pavement disease evaluation device, comprising:

[0045] A data acquisition module is configured to acquire the pavement usage performance data and the pavement structure performance data on the asphalt pavement.

[0046] A usage performance index determination module is configured to obtain a pavement usage performance index according to the pavement usage performance data.

[0047] A structure performance index determination module is configured to obtain a pavement structure performance index according to the pavement structure performance data.

[0048] A comprehensive performance determination module is configured to determine a comprehensive performance evaluation result of the asphalt pavement according to the pavement usage performance index and the pavement structure performance index.

[0049] The present application has the advantages that the pavement usage performance data and the pavement structure performance data on the asphalt pavement are acquired, so that the pavement usage performance index can be obtained according to the pavement usage performance data, the pavement structure performance index can be obtained according to the pavement structure performance data, and the comprehensive performance evaluation result of the asphalt pavement can be determined according to the pavement usage performance index and the pavement structure performance index, so that the asphalt pavement can be detected and evaluated through the pavement usage performance index and the pavement structure performance index to obtain the comprehensive performance evaluation result of the asphalt pavement, and the accuracy of the pavement evaluation is improved. BRIEF DESCRIPTION OF DRAWINGS

[0050] Fig. 1 is a flowchart of an embodiment of the asphalt pavement disease evaluation method provided by the present application;

[0051] Fig. 2 is a flowchart of an embodiment of step S102 in Fig. 1;

[0052] Fig. 3 is a flowchart of an embodiment of step S104 in Fig. 1;

[0053] Fig. 4 is a structural schematic diagram of an embodiment of the characteristic value stone map provided by the present application;

[0054] Fig. 5 is a flowchart of an embodiment of step S304 of Fig. 3 of the present application;

[0055] Fig. 6 is a flowchart of an embodiment of step S503 of Fig. 5 of the present application;

[0056] Fig. 7 is a structural schematic diagram of an embodiment of the asphalt pavement disease evaluation device provided by the present application;

[0057] Fig. 8 is a structural schematic diagram of an embodiment of the electronic device provided by the present application. DETAILED DESCRIPTION

[0058] The preferred embodiments of the present application will be described in detail below with reference to the drawings, which form a part of this application. The drawings show, by way of illustration, the principles of the application and are not intended to limit the scope of the application. The same reference numbers in different drawings represent the same or similar elements.

[0059] As shown in Fig. 1, one specific embodiment of the present application discloses an asphalt pavement disease evaluation method, comprising:

[0060] S101, obtaining pavement performance data and pavement structure performance data on the asphalt pavement;

[0061] S102, obtaining pavement performance index according to the pavement performance data;

[0062] S103, obtaining pavement structure performance index according to the pavement structure performance data;

[0063] S104, determining the comprehensive performance evaluation result of the asphalt pavement according to the pavement performance index and the pavement structure performance index.

[0064] It should be understood that: pavement performance refers to the service ability of the pavement under natural environmental conditions, mainly used to evaluate the pavement damage, pavement flatness, rutting, and anti-skid ability. The pavement performance is comprehensively evaluated by using the pavement maintenance quality index (PQI), and the sub-indexes include: pavement distress ratio (DR), international roughness index (IRI), pavement rutting depth (RD), pavement bumping (PB), and side-way force coefficient (SFC). The first four indexes can be collected by using a multifunctional road condition rapid detection vehicle, and the SFC can be collected by using a side-way force coefficient vehicle. The score range of each index is 0-100 points, the higher the score, the better the corresponding pavement performance, and then the PQI score can be obtained by adding the scores of each index.

[0065] The pavement structure performance refers to the ability of the pavement to maintain its structural integrity without damage, mainly including: pavement structural integrity and pavement structural bearing capacity. The ground penetrating radar (GPR) can obtain image information of hidden diseases of the pavement by emitting electromagnetic waves to the pavement, and is a relatively effective solution for non-destructive testing of pavement structural integrity; and the falling weight deflectometer (FWD) applies a load to the pavement in the form of a pulse load, and the pavement bearing capacity is characterized by the size of the displacement sensor value of the adjacent distance and the modulus back calculation method.

[0066] In specific embodiments of the present application, the pavement performance data and the pavement structure performance data on the asphalt pavement can be obtained by a performance detection vehicle or a radar, and the specific obtaining method can be set according to actual conditions, which is not limited in the embodiments of the present application. The obtaining method corresponding to each sub-indicator of the pavement technical condition index can be different, and the specific method can be set according to actual conditions. Then, the pavement performance data and the pavement structure performance data can be processed respectively, so that the pavement performance index of the asphalt pavement and the pavement structure performance index can be obtained, and then the asphalt pavement can be detected by the pavement performance index and the pavement structure performance index, so that the detection result of the asphalt pavement can be obtained, wherein the detection can be performed multiple times according to the starting stake number of the asphalt pavement, so that the detection result corresponding to each starting stake number can be obtained, and then the road section that needs to be repaired and processed can be determined according to all the detection results.

[0067] Compared with the prior art, the present embodiment provides the pavement performance data and the pavement structure performance data on the asphalt pavement, so that the pavement performance index can be obtained according to the pavement performance data, and then the pavement structure performance index can be obtained according to the pavement structure performance data, and then the comprehensive performance evaluation result of the asphalt pavement can be determined according to the pavement performance index and the pavement structure performance index, so that the asphalt pavement can be detected and evaluated by the pavement performance index and the pavement structure performance index, and the comprehensive performance evaluation result of the asphalt pavement can be obtained, thereby improving the accuracy of pavement evaluation.

[0068] In some embodiments of the present application, step S101 comprises:

[0069] The asphalt pavement is detected based on the asphalt pavement performance detection vehicle to obtain the pavement performance data;

[0070] The asphalt pavement is detected based on the ground penetrating radar and the falling weight deflectometer to obtain the pavement structure performance data.

[0071] In specific embodiments of the present application, the pavement performance data can include the pavement damage rate, the international roughness index, the rut depth, the lateral force coefficient and the road jump height, as shown in Table 1.

[0072] Table 1: meaning of pavement performance indicators

[0073] The road damage rate, the international roughness index, the rut depth, the lateral force coefficient and the road jump height can be detected by an asphalt pavement performance detection vehicle, a multifunctional road condition rapid detection system and a lateral force coefficient detection vehicle respectively, and corresponding detection data can be obtained. The signal transmitter of the ground penetrating radar transmits electromagnetic wave signals to penetrate the road surface to a response depth. The electromagnetic wave will penetrate and reflect after encountering different types of media in the road surface. The radar receiver will store the data in the form of reflected voltage after receiving the reflected signals. Then, the radar image is generated by the data processing software, and the type and position of the hidden road surface disease can be analyzed. The road surface can also be detected by the radar to obtain the road surface structure detection data. Further, the road surface can also be detected by the falling weight deflectometer (FWD) to obtain the detection structure data.

[0074] In some embodiments of the present application, as shown in FIG. 2, step S102 comprises:

[0075] S201, obtaining a pavement technical condition index according to the road damage rate;

[0076] S202, obtaining a road driving quality index according to the international roughness index;

[0077] S203, obtaining a road rut depth index according to the rut depth;

[0078] S204, obtaining a road anti-skid performance index according to the lateral force coefficient;

[0079] S205, obtaining a road jump index according to the road jump height;

[0080] S206, obtaining a road performance index according to the pavement technical condition index, the road driving quality index, the road rut depth index, the road anti-skid performance index and the road jump index.

[0081] In specific embodiments of the present application, after the road damage rate, the international roughness index, the rut depth, the lateral force coefficient and the road jump height are detected, the corresponding indexes can be calculated respectively, and specifically, a pavement maintenance quality index (PCI) is obtained. The PCI is an index for evaluating the road damage degree, and is evaluated by a deduction system. The calculation is shown in formulas (1) and (2):

[0082] In the formula, w i is the weight or conversion coefficient of the ith type of road damage; A iAi is the cumulative area of the ith type of pavement damage (m2); A is the pavement detection or investigation area (m2); a0and a1are empirical parameters, which are 15.00 and 0.412 for asphalt pavement, respectively.

[0083] Pavement Riding Quality Index (RQI). RQI is an important indicator for evaluating the flatness and comfort of highway pavement, which is mainly used to measure the degree of jolt felt by passengers when the vehicle is running on the pavement and the impact on the vehicle performance. The calculation is shown in equation (3):

[0084] In the formula: IRI is the international roughness index (m / km); a0and a1are model parameters, which are 0.026 and 0.65, respectively.

[0085] Rutting Depth Index (RDI). RDI is a quantitative indicator for evaluating the severity of permanent deformation of highway pavement under the action of vehicle load, especially the rutting disease. The calculation is shown in equation (4):

[0086] In the formula: RD is the rutting depth (mm); RD a and RD b are the rutting depth parameters, which are 10.0 and 40.0, respectively; a0and a1are model parameters, which are 1.0 and 3.0, respectively.

[0087] Pavement Skidding Resistance Index (SRI). SRI is an important indicator for measuring the skid resistance of pavement under wet or dry conditions based on the lateral force coefficient (SFC), which reflects the frictional resistance between the tire and the pavement when the vehicle is running on the pavement. The calculation is shown in equation (5):

[0088] In the formula: SRI min is the calibration coefficient, which is 35.0; a0and a1are model parameters, which are 28.6 and -0.105, respectively.

[0089] Pavement Bumping Index (PBI). PBI is an indicator for measuring the flatness of road surface, which mainly focuses on the degree of vehicle jolt caused by abnormal protrusions or subsidence of the pavement. PBI is usually used to quantify the vertical acceleration of the vehicle during the driving process due to the unevenness of the pavement, which directly affects the driving comfort and safety. The calculation is shown in equation (6):

[0090] PB = (PB1 + PB2 + PB3 + PB4 + PB5) / 5 (6) i is the number of road surface bumps of the ith degree. The road surface bump calculation method refers to the Highway Technical Condition Evaluation Standard (JTG H20-2018); a i is the unit deduction of the ith degree of road surface bump. Mild (2mm≤road longitudinal section height difference<5mm) takes 0, moderate (5mm≤road longitudinal section height difference<8mm) takes 25, and severe (road longitudinal section height difference≥8mm) takes 50.

[0091] Pavement Maintenance Quality Index (PQI). PQI is a comprehensive score obtained by evaluating a plurality of sub-technical indicators of the road surface. These sub-technical indicators usually include but are not limited to PCI, RQI, RDI, SRI, etc. The calculation is shown in formula (7): PQI = w PCI PCI + w RQI RQI + w RDI RDI + w SRI SRI + w PBI PBI (7)

[0092] In the formula, PQI is the pavement technical condition index; w PCI , w RQI , w RDI , w SRI respectively represent the weights of each part of the index; generally take 0.35, 0.3, 0.15, 0.1, 0.1.

[0093] In some embodiments of the present application, the pavement structure performance data includes crack disease data and pavement structure data, and step S103 includes:

[0094] According to the crack disease data, the average crack depth is obtained;

[0095] According to the pavement structure data, the deflection data is obtained, and the pavement structure performance index includes the average crack depth and the deflection data.

[0096] In specific embodiments of the present application, in view of the fact that the hidden disease of the road is mainly hidden cracks found by the early radar detection results, and the crack depth also has a great influence on the pavement structure, based on the above two reasons, the embodiment of the present application can take the average crack depth (Average Crack Depth, ACD) as the evaluation index of the hidden disease of the pavement, and the average crack depth is calculated as shown in formula (8):

[0097] In the formula, A is the length of the hidden crack disease (m); D is the depth of the hidden crack disease (m); and L is the evaluation length of the road section (m).

[0098] According to the falling weight deflectometer (FWD), deflection data D0, D1, D2, D3, D4, D5 and D6 can be obtained, which respectively represent the deflection values measured at distances of 0 mm, 300 mm, 600 mm, 900 mm, 1200 mm, 1500 mm and 2100 mm from the center of the load plate. The pavement structure can generally be simplified as a three-layer structure of surface layer + base layer + soil base. In order to evaluate the structural performance of the whole, the surface layer and the base layer, three deflection basin parameters are defined in this paper, as shown in Table 2. D0 reflects the mechanical response of the entire asphalt pavement; D 01 reflects the response of the asphalt surface layer; and D 12 reflects the mechanical response of the base layer.

[0099] Table 2, explanation of deflection basin parameters

[0100] In some embodiments of the present application, as shown in Figure 3, step S104 comprises:

[0101] S301, performing factor rotation processing on the pavement service performance index and the pavement structure performance index based on the maximum variance method to obtain an accumulated variance explanation rate and a rotated factor loading coefficient;

[0102] S302, determining at least one principal factor according to the accumulated variance explanation rate;

[0103] S303, obtaining a principal factor score of each index corresponding to each principal factor according to the rotated factor loading coefficient;

[0104] S304, obtaining a comprehensive performance evaluation result of the asphalt pavement according to the pavement service performance index, all principal factor scores and the accumulated variance explanation rate.

[0105] In specific embodiments of the present application, after detecting the pavement damage rate, the international roughness index, the rut depth, the lateral force coefficient, the road jump height, the average crack depth and the deflection data, all the above data can be processed by the factor analysis method, and all the data of the SPSS statistical calculation tool are shown in Table 3:

[0106] Table 3, road detection data of a certain section

[0107] The road detection data collected in Table 3 can then be input into the SPSS statistical calculation tool, the "factor analysis" tool of SPSS is used to complete the required calculation process, and the data in Table 3 is rotated according to the maximum variance method, so that the accumulated variance explanation rate and the eigenvalue scree plot of Table 4 can be output, and the eigenvalue scree plot is shown in Figure 4. The x-axis of Figure 4 is the factor, and the y-axis is the eigenvalue. As shown in Table 4, the accumulated variance explanation rate can include the rotated variance explanation rate and the rotated cumulative variance explanation rate:

[0108] Table 4, cumulative variance explanation rate

[0109] Wherein: (1) the size of the eigenvalue of the correlation coefficient matrix shown in Table 4 reflects the ability of the factor to explain the original information, when the eigenvalue is less than 1, it indicates that the explanatory power of the factor is not as good as the original variable, therefore, the components with eigenvalue greater than 1 are included in the evaluation system. (2) The broken stone chart is a chart drawn according to the explanation degree of each principal component to the data variation. Its function is to confirm the number of factors to be selected according to the slope of the eigenvalue, which can be used to confirm or adjust the number of factors in combination with the variance explanation table.

[0110] From the above analysis, it can be seen that the cumulative variance explanation rate of the first three principal factors reaches 84.645%, which indicates that the first three components can explain most of the information of the original variables, so the first three components are taken as the principal factors.

[0111] The factor loading matrix result after factor rotation is shown in Table 5. According to the size of the loading coefficient value, DR, PB, IRI and RD in factor 1 are named as road surface condition index (RSCI); D0, D 01 , D 12 in factor 2 are named as structure performance index (SPI); ACD, SFC and D01 in factor 3 are named as surface layer overall condition index (SOPI).

[0112] Table 5, factor loading matrix coefficient after rotation

[0113] Then, the factor component matrix table is established according to the factor loading matrix, as shown in Table 6, which aims to explain the factor score coefficient contained in each component, which is used to calculate the principal factor score.

[0114] Table 6, component score matrix table

[0115] In some embodiments of the present application, as shown in Figure 5, step S304 comprises:

[0116] S501, obtaining the index value corresponding to each principal factor according to the principal factor score of all indexes corresponding to each principal factor;

[0117] S502, determining the weight of each principal factor according to the cumulative variance explanation rate;

[0118] S503, obtaining the comprehensive performance evaluation result of the asphalt pavement according to the index value, the pavement use performance index, all principal factors and all weights.

[0119] In specific embodiments of the present application, after obtaining the main factor scores corresponding to each index of each main factor in Table 6, the index values corresponding to each main factor can be calculated according to the main factor formula, as shown in formulas (9)-(11): RSCI = -0.015D0-0.089D 01 -0.004D 12 -0.247DR-0.324PB- 0.326IRI-0.061ACD-0.071SFC+0.247RD (9) SPI=-0364D0-0304D 01 -0355D 12 -0.042DR-0.004PB- 0.029IRI-0.112ACD-0.081SFC+0.122RD (10) SOCI=-0.018D0-0.250D 01 -0.201D 12 -0.019DR-0.149PB- 0.101IRI-0.556ACD-0.476SFC+0.069RD (11)

[0120] In the formula, RSCI is the road surface condition index, SPI is the structural performance index, and SOCI is the surface comprehensive condition index.

[0121] In some embodiments of the present application, step S502 comprises:

[0122] According to the cumulative variance interpretation rate after rotation, determine the target variance interpretation rate;

[0123] According to the target variance interpretation rate and the variance interpretation rate corresponding to each main factor after rotation, obtain the weight corresponding to each main factor.

[0124] In specific embodiments of the present application, the three main factor weights shown in Table 7 are given according to the variance interpretation rate after rotation.

[0125] Table 7, factor weight calculation results

[0126] According to Table 7, it can be seen that when the cumulative variance contribution rate after rotation reaches 84.634%, the following contribution rate changes less, so the target variance explanation rate can be determined as 84.634%, and then 36.385 of RSCI in the variance contribution rate after rotation is divided by the target variance explanation rate 84.634, so that the weight of RSCI is 42.99% for normalization, and the weights of the target variance explanation rates RSCI, SPI and SOCI are 0.4399, 0.3530 and 0.2171 respectively. Finally, the comprehensive evaluation formula shown in formula (12) is derived to represent the comprehensive performance of the pavement, and is defined as the pavement maintenance ranking index (PMRI), and formula (12) is as follows: PMRI = 0.4299RSCI + 0.3530SPI + 0.2171SOCI (12)

[0127] In addition, since the embodiment of the present application adopts a negative index, the higher the value is, the worse the pavement performance is.

[0128] In some embodiments of the present application, as shown in Figure 6, step S503 comprises:

[0129] S601, obtaining the pavement maintenance ranking index according to the index value, all main factors and all weights;

[0130] S602, respectively sorting the detected road sections on the asphalt pavement according to the pavement performance index and the pavement maintenance ranking index to obtain corresponding sorting results;

[0131] S603, obtaining the comprehensive performance evaluation result of the asphalt pavement according to the sorting result of the pavement performance index and the sorting result of the pavement maintenance ranking index.

[0132] In specific embodiments of the present application, after establishing the comprehensive evaluation system of the pavement, the test road section is evaluated. The scores of each sub-item and the comprehensive score of PQI calculated according to formula (1) to formula (7) are shown in Table 8, and the maintenance planning is carried out in the order from small to large of the PQI score (the higher the PQI value is, the better the service performance of the road section is).

[0133] Table 8, PQI comprehensive score and maintenance order

[0134] The scores of each sub-item and the comprehensive score of PMRI calculated according to formula (9) to formula (12) are shown in Table 9, and the maintenance planning is carried out in the order from large to small of the PMRI score (for PMRI, the higher the value is, the deeper the damage degree of the road section is, and the worse the bearing capacity is).

[0135] Table 9, scores of each sub-item of PMRI and comprehensive score

[0136] It can be found that the overall trend of the PQI maintenance sequence and the PMRI maintenance sequence is slightly different. However, since the PMRI considers the hidden diseases and structural performance of the pavement, there is a certain difference between the maintenance sequences. Compared with the performance evaluation index of PQI which only considers the road surface disease, since the PMRI considers the hidden diseases and structural performance of the pavement, there is a certain difference between the maintenance sequences, and the evaluation index of the PMRI proposed in the embodiment of the present application is used as the criterion, so that the comprehensive performance evaluation result of the asphalt pavement is determined as the road pile number K1091+500 road needs to be maintained.

[0137] In some embodiments of the present application, before determining the comprehensive performance evaluation result of the asphalt pavement according to the pavement use performance index and the pavement structure performance index, the method further comprises:

[0138] Based on the KMO test and the Bartlett sphericity test, the pavement use performance index and the pavement structure performance index are tested to obtain corresponding test results;

[0139] According to the test results of the KMO test and the test results of the Bartlett sphericity test, the reliability of the comprehensive performance evaluation result of the asphalt pavement is determined.

[0140] In specific embodiments of the present application, before factor analysis is performed on each index of the pavement disease, KMO test and Bartlett sphericity test need to be performed on each index to evaluate the correlation of each index and whether the requirements of factor analysis are met. (1) Whether KMO is suitable for factor analysis: 0.9 < KMO < 1.0, very suitable; 0.8 < KMO < 0.9, suitable; 0.7 < KMO < 0.8, acceptable; 0.6 < KMO < 0.7, usable; KMO < 0.6, unacceptable. (2) By querying the chi-square distribution table based on the degrees of freedom and statistical observations, the corresponding accompanying probability value can be approximately obtained. According to the accompanying probability p and the significance level a, it is determined whether there is correlation between variables and suitable for factor analysis. Through KMO test and Bartlett test, the test results of the data in Table 3 are obtained as shown in Table 10.

[0141] Table 10, test results of KMO test and Bartlett test

[0142] The KMO value is greater than 0.7, indicating that there is strong partial correlation between the variables; the Bartlett sphericity test significance P is 0.01, indicating that the variables are not independent. That is, the variables shown in Table 3 are suitable for factor analysis, that is, the result of detection by the factor analysis method has high reliability.

[0143] Since the pavement structure performance often has a greater impact on the attenuation of the use performance, the structural condition and the pavement condition should be considered simultaneously in the asphalt pavement maintenance sequence in the embodiment of the application. Therefore, the embodiment of the application comprehensively evaluates the disease severity of the road from the internal and external two angles by combining the internal structure performance of the road tested by the ground penetrating radar (GPR) and the falling weight deflectometer (FWD), and the surface performance tested by the CiCS car and the lateral force coefficient car. That is, the original nine pavement performance evaluation indexes are converted into three by using the factor analysis method, data dimensionality reduction is realized, and the comprehensiveness and convenience of the factor analysis method for evaluating the pavement performance are embodied. Meanwhile, the factor analysis can also minimize the influence of subjective experience on the evaluation. In addition, in the comprehensive evaluation function, the weight of each evaluation index is the contribution rate, which reflects the proportion of the information amount expressed by the index in the total information amount. The weight determined in this way is objective and reasonable, and overcomes the defects of fixed weight in some evaluation methods.

[0144] In order to better implement the asphalt pavement disease evaluation method in the embodiment of the application, on the basis of the asphalt pavement disease evaluation method, correspondingly, the embodiment of the application also provides an asphalt pavement disease evaluation device, as shown in Figure 7, the asphalt pavement disease evaluation device 700 comprises:

[0145] A data acquisition module 701 is configured to acquire pavement use performance data and pavement structure performance data on the asphalt pavement.

[0146] A use performance index determination module 702 is configured to obtain a pavement use performance index according to the pavement use performance data.

[0147] A structure performance index determination module 703 is configured to obtain a pavement structure performance index according to the pavement structure performance data.

[0148] A comprehensive performance determination module 704 is configured to determine an asphalt pavement comprehensive performance evaluation result according to the pavement use performance index and the pavement structure performance index.

[0149] The asphalt pavement disease evaluation device 700 provided in the above embodiment can implement the technical solutions described in the asphalt pavement disease evaluation method embodiments described above, and the principles of the implementation of the above modules or units can be referred to the corresponding content in the asphalt pavement disease evaluation method embodiments described above, which will not be described here again.

[0150] As shown in FIG. 8, the present application also provides an electronic device 800. The electronic device 800 includes a processor 801, a memory 802, and a display 803. FIG. 8 only shows part of the components of the electronic device 800, but it should be understood that all the components shown are not required, and more or less components can be implemented instead.

[0151] The memory 802 can be an internal storage unit of the electronic device 800, such as a hard disk or a memory of the electronic device 800 in some embodiments. The memory 802 can also be an external storage device of the electronic device 800, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the electronic device 800 in other embodiments.

[0152] Further, the memory 802 can include both an internal storage unit and an external storage device of the electronic device 800. The memory 802 is used to store application software and various data installed on the electronic device 800.

[0153] The processor 801 can be a central processing unit (CPU), a microprocessor, or other data processing chip in some embodiments, used to run program codes or process data stored in the memory 802, such as the asphalt pavement disease evaluation method in the present application.

[0154] The display 803 can be an LED display, a liquid crystal display, a touch liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, etc. in some embodiments. The display 803 is used to display information of the electronic device 800 and to display a visualized user interface. The components 801-803 of the electronic device 800 communicate with each other through a system bus.

[0155] In some embodiments of the present application, when the processor 801 executes the asphalt pavement disease evaluation program in the memory 802, the following steps can be implemented:

[0156] Obtaining pavement use performance data and pavement structure performance data on the asphalt pavement;

[0157] Obtaining a pavement use performance index according to the pavement use performance data;

[0158] Obtaining a pavement structure performance index according to the pavement structure performance data;

[0159] Determining an asphalt pavement comprehensive performance evaluation result according to the pavement use performance index and the pavement structure performance index.

[0160] It should be understood that, in addition to the above functions, the processor 801 can also implement other functions when executing the asphalt pavement disease evaluation program in the memory 802. For details, refer to the description of the corresponding method embodiments.

[0161] Further, the type of the electronic device 800 is not specifically limited, and the electronic device 800 can be a mobile phone, a tablet computer, a personal digital assistant (PDA), a wearable device, a laptop, or the like. Exemplary embodiments of the portable electronic device include, but are not limited to, a portable electronic device running an IOS, an android, a microsoft, or other operating system. The portable electronic device can also be another portable electronic device, such as a laptop having a touch-sensitive surface (e.g., a touch panel). It should also be understood that, in some other embodiments of the present application, the electronic device 800 can also be a desktop computer having a touch-sensitive surface (e.g., a touch panel).

[0162] Correspondingly, the present application also provides a computer-readable storage medium for storing computer-readable programs or instructions, which, when executed by a processor, can implement the steps of the asphalt pavement disease evaluation method provided by the above method embodiments or the functions thereof.

[0163] Those skilled in the art can understand that all or part of the processes of the above-mentioned embodiments can be completed by a computer program instructing relevant hardware (such as a processor, a controller, etc.) to complete. The computer program can be stored in a computer-readable storage medium. The computer-readable storage medium includes a magnetic disk, an optical disk, a read-only memory, or a random access memory, etc.

[0164] The asphalt pavement disease evaluation method and device provided by the present application are described in detail above, and specific examples are applied to explain the principles and implementation modes of the present application. The above description of the embodiments is only used to help understand the method and its core idea; meanwhile, for those skilled in the art, according to the idea of the present application, the specific implementation mode and application range will be changed; in summary, the content of the specification should not be understood as a limitation of the present application.

Claims

1. A method for evaluating asphalt pavement distress, characterized by, The method comprises: obtaining pavement performance data and pavement structure performance data on the asphalt pavement; obtaining a pavement performance index according to the pavement performance data; obtaining a pavement structure performance index according to the pavement structure performance data; determining an asphalt pavement comprehensive performance evaluation result according to the pavement performance index and the pavement structure performance index.

2. The method for evaluating the asphalt pavement distress according to claim 1, wherein, The pavement performance data comprises pavement damage rate, international roughness index, rut depth, lateral force coefficient and road jump height, and the pavement performance index is obtained according to the pavement performance data, which comprises: obtaining a pavement technical condition index according to the pavement damage rate; obtaining a pavement driving quality index according to the international roughness index; obtaining a pavement rut depth index according to the rut depth; obtaining a pavement skid resistance index according to the lateral force coefficient; obtaining a pavement jump index according to the road jump height; obtaining the pavement performance index according to the pavement technical condition index, the pavement driving quality index, the pavement rut depth index, the pavement skid resistance index and the pavement jump index.

3. The method of claim 1, wherein, The pavement structure performance data comprises crack disease data and pavement structure data, and the pavement structure performance index is obtained according to the pavement structure performance data, which comprises: obtaining an average crack depth according to the crack disease data; obtaining deflection data according to the pavement structure data, and the pavement structure performance index comprises the average crack depth and the deflection data.

4. The method of claim 1, wherein, The asphalt pavement comprehensive performance evaluation result is determined according to the pavement performance index and the pavement structure performance index, which comprises: performing factor rotation processing on the pavement performance index and the pavement structure performance index based on the maximum variance method to obtain cumulative variance explanation rate and factor loading coefficient after rotation; determining at least one principal factor according to the cumulative variance explanation rate; obtaining principal factor scores of each principal factor corresponding to each index according to the factor loading coefficient after rotation; obtaining the asphalt pavement comprehensive performance evaluation result according to the pavement performance index, all principal factor scores and the cumulative variance explanation rate.

5. The asphalt pavement distress evaluation method of claim 4, wherein, The asphalt pavement comprehensive performance evaluation result is obtained according to the pavement performance index, all principal factor scores and the cumulative variance explanation rate, which comprises: obtaining index values corresponding to each principal factor according to principal factor scores of all indexes corresponding to each principal factor; determining weights of the each principal factor according to the cumulative variance explanation rate; obtaining the asphalt pavement comprehensive performance evaluation result according to the index values, the pavement performance index, all principal factors and all weights.

6. The asphalt pavement distress evaluation method of claim 5, wherein, The cumulative variance explanation rate comprises variance explanation rate after rotation and cumulative variance explanation rate after rotation, and the weights of the each principal factor are determined according to the cumulative variance explanation rate, which comprises: determining target variance explanation rate according to the cumulative variance explanation rate after rotation; obtaining weights corresponding to each principal factor according to the target variance explanation rate and the variance explanation rate after rotation corresponding to each principal factor.

7. The asphalt pavement distress evaluation method of claim 6, wherein, The asphalt pavement comprehensive performance evaluation result is obtained according to the index value, the pavement performance index, all the main factors and all the weights, and includes: A pavement maintenance grade index is obtained according to the index value, all the main factors and all the weights; The road sections on the asphalt pavement are sorted according to the pavement performance index and the pavement maintenance grade index respectively to obtain corresponding sorting results; The asphalt pavement comprehensive performance evaluation result is obtained according to the sorting result of the pavement performance index and the sorting result of the pavement maintenance grade index.

8. The method of claim 1, wherein, Before the asphalt pavement comprehensive performance evaluation result is determined according to the pavement performance index and the pavement structure performance index, the method further includes: The pavement performance index and the pavement structure performance index are tested based on KMO test and Bartlett sphericity test to obtain corresponding test results; The reliability of the asphalt pavement comprehensive performance evaluation result is determined according to the test result of the KMO test and the test result of the Bartlett sphericity test.

9. The method of claim 1, wherein, The pavement performance data and the pavement structure performance data on the asphalt pavement are obtained, including: The asphalt pavement is detected based on an asphalt pavement performance detection vehicle to obtain pavement performance data; The asphalt pavement is detected based on a ground penetrating radar and a falling weight deflectometer to obtain pavement structure performance data.

10. An asphalt pavement distress evaluation device, characterized by, The method includes: A data acquisition module is configured to acquire pavement performance data and pavement structure performance data on an asphalt pavement; A performance index determination module is configured to obtain a pavement performance index according to the pavement performance data; A structure performance index determination module is configured to obtain a pavement structure performance index according to the pavement structure performance data; A comprehensive performance determination module is configured to determine an asphalt pavement comprehensive performance evaluation result according to the pavement performance index and the pavement structure performance index. ​

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