CN111523825A - Multi-dimensional-based method for evaluating long-term performance of asphalt pavement of highway - Google Patents

Multi-dimensional-based method for evaluating long-term performance of asphalt pavement of highway Download PDF

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CN111523825A
CN111523825A CN202010392375.2A CN202010392375A CN111523825A CN 111523825 A CN111523825 A CN 111523825A CN 202010392375 A CN202010392375 A CN 202010392375A CN 111523825 A CN111523825 A CN 111523825A
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卢勇
曹荣吉
刘林林
刘爱华
李亚丽
吴昊
温肖博
吴宝鑫
杨惠宇
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Abstract

The invention discloses a multi-dimensional highway asphalt pavement long-term performance evaluation method, which is used for evaluating the long-term performance of a highway asphalt pavement which has been on traffic for more than 8 years. And secondly, detecting and analyzing the performance of the pavement material to obtain a second-dimension comprehensive evaluation value RMC. And finally, judging the long-term performance of the expressway asphalt pavement based on the second-dimension comprehensive evaluation value RMC. From a macroscopic perspective to a microscopic perspective, on one hand, the long-term performance of the highway asphalt pavement can be accurately evaluated, and on the other hand, the method can be used as an important basis for maintenance decision, and has a good application prospect.

Description

Multi-dimensional-based method for evaluating long-term performance of asphalt pavement of highway
Technical Field
The invention relates to the technical field of highway detection, in particular to a multidimensional evaluation method for long-term performance of a highway asphalt pavement.
Background
With the rapid development of scientific technology, the demand for the construction and maintenance of highways between cities is increasing. In order to ensure the safety and reliability of vehicle driving, it is critical to ensure good road conditions on the highway. Currently, the evaluation of the long-term performance of the asphalt pavement of the expressway is to perform multi-index detection on the pavement of the expressway which has been in traffic for 8 years, so as to obtain indexes of each pavement 8 years after the traffic is in traffic, and on one hand, the evaluation of the long-term performance of the expressway network can be performed based on the detected index data of each pavement, and on the other hand, the evaluation can be used as an important means for maintenance decision.
The existing method for evaluating the long-term performance of the asphalt pavement of the expressway evaluates the long-term performance of the asphalt pavement from three aspects of road surface performance, material performance and structural performance indexes, and belongs to the same latitude. And moreover, the single index is adopted to judge the quality of the long-term performance of the asphalt pavement and the basis of maintenance decision. Therefore, there are disadvantages:
(1) the existing method for evaluating the long-term performance of the asphalt pavement of the expressway does not evaluate according to levels and latitudes, only evaluates according to the PQI (pavement service performance index) of the pavement, and has the disadvantages of time and labor consumption and poor economy in PQI detection;
(2) the decision index is single or not representative, and the long-term performance condition of the on-site asphalt pavement cannot be comprehensively represented or is difficult to represent.
Therefore, how to overcome the above problems is a problem to be solved currently.
Disclosure of Invention
The invention aims to solve the problems that the existing method for evaluating the long-term performance of the asphalt pavement of the expressway has ambiguous observation indexes, does not carry out classification and latitudinal observation, cannot accurately evaluate the long-term performance of the pavement and the like. The invention discloses a long-term performance evaluation method of an expressway bituminous pavement based on multiple dimensions, which is based on the macro-observation angle, namely, the long-term performance of the pavement is detected and analyzed from the aspects of road surface performance and structural performance from the first dimension to obtain a comprehensive evaluation value PPC of the first dimension, and whether the long-term performance of the expressway bituminous pavement is good or bad is judged and whether the long-term performance evaluation of the second dimension is carried out is determined based on the comprehensive evaluation value PPC of the first dimension. And secondly, based on the first dimension evaluation result, from a microscopic view angle, performing second dimension evaluation, and performing pavement material performance detection analysis to obtain a second dimension comprehensive evaluation value RMC. And finally, judging the long-term performance of the expressway asphalt pavement based on the second-dimension comprehensive evaluation value RMC. From a macroscopic perspective to a microscopic perspective, a multi-dimensional decision index system of the highway asphalt pavement is established, evaluation is carried out by adopting multi-dimensional indexes, on one hand, the long-term performance of the highway asphalt pavement can be accurately evaluated, on the other hand, the multi-dimensional decision index system can be used as an important basis for maintenance decision, and the method has a good application prospect.
In order to achieve the purpose, the invention adopts the technical scheme that:
a long-term performance evaluation method for an expressway bituminous pavement based on multiple dimensions can evaluate the long-term performance of the expressway bituminous pavement which has been on traffic for more than 8 years, and comprises the following steps,
step (A), constructing a first dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the first dimension evaluation model is obtained by detecting a sub-index driving quality index RQI, an anti-skid performance index SRI, a pavement damage index PCI, a rut depth index RDI and a pavement structural strength index PSSI, and calculating the sub-indexes by weight to obtain a first dimension evaluation index pavement performance state PPC;
step (B), constructing a second dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the second dimension evaluation model is obtained by detecting a surface layer high-temperature performance index HTPM, a lower layer high-temperature performance index HTPL, an upper layer crack resistance index CRI and a base layer mechanical performance index MPI in sub-indexes and calculating the sub-indexes by weight to obtain a second dimension evaluation index pavement material condition RMC;
and (C) evaluating the long-term performance of the expressway asphalt pavement sequentially through the combination of the first dimension evaluation model and the second dimension evaluation model to obtain the evaluation grade of the long-term performance of the expressway asphalt pavement.
The long-term performance evaluation method of the multi-dimensional highway asphalt pavement comprises the step (A) of calculating the running quality index RQI according to the formula (1),
Figure BDA0002486279740000031
wherein IRI is international flatness index and the unit is m/km; a is0For the first driving quality coefficient, 0.026 is adopted for the expressway and the first-level highway; a is1For the second running quality coefficient, the expressway and the first-level expressway adopt 0.65;
the anti-skid performance index SRI is obtained by calculating the formula (2),
Figure BDA0002486279740000032
wherein SFC is a transverse force coefficient, SRImin is a calibration parameter, and 35 is adopted; a is228.6 is adopted as the first anti-slip performance parameter; a is3For the second anti-skid performance parameter, -0.015;
the pavement damage index PCI is calculated by a formula (3),
PCI＝100-a4DRa5(3)
wherein DR is the pavement damage rate, and the unit is%; a is415 is adopted as the damage coefficient of the first asphalt pavement; a is5The pavement damage coefficient of the second asphalt pavement is 0.412;
the rut depth index RDI is obtained by calculation according to a formula (4),
Figure RE-GDA0002522906190000041
wherein RD is the rutting depth; RDa is a rut depth parameter, using 10; RDb is the rut depth parameter, 40; a is6Adopting 1 as a first rut depth model parameter; a is7For the second rut depth model parameter, adopt 3;
the road surface structural strength index PSSI is obtained by calculation according to a formula (5),
Figure BDA0002486279740000042
wherein, SSR is road surface structure coefficient and is road surface deflection standard value lRDeflection representative deflection l measured with road surface0The ratio of (A) to (B); a is915.71 is adopted as a first road surface structure strength model parameter; a is10For the second road surface structure strength model parameter, -5.19 was used.
In the multi-dimensional-based highway asphalt pavement long-term performance evaluation method, in the step (a), the first dimension evaluation model is obtained by detecting a sub-index driving quality index RQI, an anti-skid performance index SRI, a pavement damage index PCI, a rut depth index RDI and a pavement structural strength index PSSI, calculating the sub-indexes by weight to obtain a first dimension evaluation index pavement performance condition PPC, and calculating by using a formula (6).
PPC＝wPCIPCI+wRQIRQI+wRDIRDI+wSRISRI+wPSSIPSSI (6)
Wherein, WPCIFor the road surface damage index weight, the expressway and the first-level highway adopt 0.35; wRQIIs the running quality index weightThe highway and the first-level highway adopt 0.3; wRDIFor track depth index weight, 0.15 is adopted for a highway and a first-level highway; wSRIThe weight of the anti-skid performance index is 0.1 for the expressway and the first-level highway; wPSSIFor the structural strength weight of the pavement, the highway and the first-level highway adopt 0.1.
In the multidimensional-based method for evaluating the long-term performance of the highway asphalt, the pavement damage index weight W isPCIRunning quality index weight WRQIRut depth index weight WRDIAnti-skid performance index weight WSRIRoad surface structural strength weight WPSSIThe determination process of (2) is as follows:
(A1) constructing a first dimension evaluation index judgment matrix P by using original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix P is a result of pairwise comparison of indexes, and for an index system with the 5 indexes, the matrix form is as follows:
Figure RE-GDA0002522906190000051
(A2) calculating the first dimension evaluation index judgment matrix P, and calculating the weight value of each index by using a sum method;
(A3) adding each row of the first dimension evaluation index judgment matrix P, and then carrying out normalization processing on each element to obtain Pij'，
Figure BDA0002486279740000052
(A4) For p of each rowij' summing to get p1ij'，
Figure BDA0002486279740000053
(A5) P1ij' adding the columns forming the new matrix, and then normalizing the elements to obtain the weight of each indexThe weight value of the weight is set to be,
Figure BDA0002486279740000054
said w1Is road surface damage index weight WPCI、w2As a running quality index weight WRQI、w3For rut depth index weight WRDI、w4Is the anti-skid performance index weight WSRI、w5For road surface structural strength weight WPSSI。
The long-term performance evaluation method of the multi-dimensional highway asphalt pavement comprises the following steps that (B), the middle-surface layer high-temperature performance index HTPM is judged through a middle-surface layer hamburger rut test, and the grade is 90 minutes when the value of the middle-surface layer hamburger rut is smaller than 1.4 mm; between 1.4 and 2.4mm is 80 points in the grade; the grade difference is 60 minutes when the diameter is larger than 2.4 mm;
the lower layer high-temperature performance index HTPL is judged according to a lower layer hamburger rutting test, and the grade is superior to 90 minutes when the numerical value of the lower layer hamburger rutting is less than 4.1 mm; 80 points in the grade between 4.1mm and 7.3 mm; the grade difference is 60 minutes when the diameter is more than 7.3 mm;
the CRI is judged by the upper layer fracture energy test, and the grade is 90 minutes when the numerical value of the upper layer fracture energy is more than or equal to 700J/m 2; 80 points in the grade between 300 and 700J/m 2; the grade difference is less than or equal to 300J/m2 and is 60 points;
the base layer mechanical property index MPI is judged according to an unconfined compressive strength test, and the grade is superior to 90 minutes when the unconfined compressive strength is greater than 7.3 Mpa; 80 minutes in the grade between 4.6 and 7.3 Mpa; the grade difference is 60 minutes when the pressure is less than 4.6 MPa.
The multidimensional-based highway asphalt pavement long-term performance evaluation method comprises the step (B) of detecting a surface layer high-temperature performance index HTPM, a lower layer high-temperature performance index HTPL, an upper layer crack resistance index CRI and a base layer mechanical performance index MPI in sub-indexes by the second dimension evaluation model, obtaining a second dimension evaluation index pavement material condition RMC by weight calculation of the sub-indexes, and obtaining the second dimension evaluation index pavement material condition RMC by the calculation of a formula (7),
RMC＝wHTPMHTPM+wHTPLHTPL+wCRICRI+wMPIMPI (7)
wherein, WHTPMThe weight of the high-temperature performance index of the middle surface layer is 0.3 for the expressway and the first-level expressway; wHTPLThe weight of the high-temperature performance index of the lower layer is 0.25 for the expressway and the first-level highway; wCRIThe weight of the crack resistance index of the upper layer is 0.15 for the expressway and the first-level highway; wMPIThe weight of the mechanical property index of the basic level is 0.3 for the expressway and the first-level highway.
The multidimensional-based highway asphalt long-term performance evaluation method comprises the step (B) of weighing the middle-surface-layer high-temperature performance index WHTPMLower layer high temperature performance index weight WHTPLUpper layer crack resistance index weight WCRIBasic mechanical property index weight WMPIThe determination process of (2) is as follows:
(B1) and constructing a second dimension evaluation index judgment matrix Q by using original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix Q is a result of pairwise comparison of indexes, and for an index system with the 4 indexes, the matrix form is as follows:
Figure RE-GDA0002522906190000071
(B2) calculating the obtained second dimension evaluation index judgment matrix Q, and calculating the weight value of each index by using a sum method;
(B3) adding each row of the second dimension evaluation index judgment matrix Q, and then carrying out normalization processing on each element to obtain Qij'，
Figure BDA0002486279740000072
(B4) For each row qij' summing to get q1ij'，
Figure BDA0002486279740000073
(B5) Q1ij' adding the columns forming the new matrix, then normalizing each element to obtain the weight value of each index,
Figure BDA0002486279740000081
the w11Is the high-temperature performance index weight W of the middle layerHTPM，w12Is the weight W of the high temperature performance index of the lower layerHTPL、w13Is the upper layer crack resistance index weight WCRI、w14Is the basic mechanical property index weight WMPI。
The method for evaluating the long-term performance of the multi-dimensional highway asphalt pavement comprises the following steps of (C) sequentially evaluating the long-term performance of the highway asphalt pavement through the combination of a first dimension evaluation model and a second dimension evaluation model,
(C1) performing primary evaluation on the expressway through a first dimension evaluation model, and if the PPC (pavement performance condition) is greater than or equal to 90 minutes, determining that the expressway is excellent; if the road surface performance condition PPC is less than 90 minutes and is greater than or equal to 80 minutes, executing (C2) and carrying out secondary evaluation according to the road surface performance condition PPC; if the PPC of the road surface performance condition is less than 80 minutes and more than or equal to 70 minutes, the expressway is divided into two times; if the PPC of the pavement performance is less than 70 minutes, the expressway is poor;
(C2) performing secondary evaluation through the pavement performance condition PPC, and if the pavement material condition RMC is more than or equal to 90 minutes, judging that the expressway is good; if the PPC of the pavement performance is less than 90 minutes and more than or equal to 80 minutes, the expressway is medium; if the PPC of the pavement performance condition is less than 80 minutes and more than or equal to 70 minutes, the expressway is divided into two times; if the road surface performance condition PPC is less than 70 minutes, the highway is poor.
The invention has the beneficial effects that: the method for evaluating the long-term performance of the expressway bituminous pavement based on the multiple dimensions performs long-term performance evaluation on the expressway bituminous pavement which has been on traffic for more than 8 years. Firstly, from a macroscopic perspective, namely, the long-term performance of the pavement is detected and analyzed from the two aspects of the road surface performance and the structural performance from the first dimension, so as to obtain a comprehensive evaluation value PPC of the first dimension, and based on the comprehensive evaluation value PPC of the first dimension, the quality of the long-term performance of the asphalt pavement of the expressway is judged and whether the long-term performance evaluation of the second dimension is carried out or not is determined. And secondly, based on the first dimension evaluation result, from a microscopic view angle, performing second dimension evaluation, and performing pavement material performance detection analysis to obtain a second dimension comprehensive evaluation value RMC. And finally, judging the long-term performance of the expressway asphalt pavement based on the second-dimension comprehensive evaluation value RMC. From a macroscopic view to a microscopic view, a multi-dimensional decision index system of the highway asphalt pavement is established, and the evaluation is carried out by adopting the multi-dimensional index, so that on one hand, the long-term performance of the highway asphalt pavement can be accurately evaluated, on the other hand, the multi-dimensional decision index can be used as an important basis for maintenance decision, and the method has a good application prospect.
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FIG. 1 is a flow chart of the method for evaluating the long-term performance of the multi-dimensional highway asphalt pavement.
Detailed Description
The invention will be further described with reference to the accompanying drawings.
As shown in figure 1, the invention discloses a multidimensional method for evaluating the long-term performance of an asphalt pavement of a highway, which is used for evaluating the long-term performance of the asphalt pavement of the highway which has been on for more than 8 years. Firstly, from a macroscopic perspective, namely, the long-term performance of the pavement is detected and analyzed from the two aspects of the road surface performance and the structural performance from the first dimension, so as to obtain a comprehensive evaluation value PPC of the first dimension, and based on the comprehensive evaluation value PPC of the first dimension, the quality of the long-term performance of the asphalt pavement of the expressway is judged and whether the long-term performance evaluation of the second dimension is carried out or not is determined. And secondly, based on the first dimension evaluation result, from a microscopic view angle, performing second dimension evaluation, and performing pavement material performance detection analysis to obtain a second dimension comprehensive evaluation value RMC. And finally, judging the long-term performance of the expressway asphalt pavement based on the second-dimension comprehensive evaluation value RMC. From macroscopic view to microscopic view, a multi-dimensional decision index system of the highway asphalt pavement is established, and evaluation is carried out by adopting multi-dimensional indexes, so that on one hand, the long-term performance of the highway asphalt pavement can be accurately evaluated, and on the other hand, the multi-dimensional decision index system can be used as an important basis for maintenance decision, and the method comprises the following steps,
step (A), constructing a first dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the first dimension evaluation model is obtained by detecting sub-index running quality index RQI, anti-skid performance index SRI, pavement damage index PCI, rut depth index RDI and pavement structural strength index PSSI, and calculating the sub-indexes by weight to obtain a first dimension evaluation index pavement performance condition PPC, and the running quality index RQI is obtained by calculating according to a formula (1),
Figure BDA0002486279740000101
wherein IRI is international flatness index and the unit is m/km; a is0For the first driving quality coefficient, 0.026 is adopted for the expressway and the first-level highway; a is1For the second running quality coefficient, the expressway and the first-level expressway adopt 0.65;
the anti-skid performance index SRI is obtained by calculating the formula (2),
Figure BDA0002486279740000102
wherein SFC is a transverse force coefficient, SRImin is a calibration parameter, and 35 is adopted; a is228.6 is adopted as the first anti-slip performance parameter; a is3For the second anti-skid performance parameter, -0.015;
the pavement damage index PCI is calculated by a formula (3),
PCI＝100-a4DRa5(3)
wherein DR is the pavement damage rate, and the unit is%; a is415 is adopted as the damage coefficient of the first asphalt pavement; a is5The pavement damage coefficient of the second asphalt pavement is 0.412;
the rut depth index RDI is obtained by calculation according to a formula (4),
Figure RE-GDA0002522906190000103
wherein RD is the rutting depth; RDa is a rut depth parameter, using 10; RDb is the rut depth parameter, 40; a is6Adopting 1 as a first rut depth model parameter; a is7For the second rut depth model parameter, adopt 3;
the road surface structural strength index PSSI is obtained by calculation according to a formula (5),
Figure BDA0002486279740000111
wherein, SSR is road surface structure coefficient and is road surface deflection standard value lRDeflection representative deflection l measured with road surface0The ratio of (A) to (B); a is915.71 is adopted as a first road surface structure strength model parameter; a is10For the second road surface structure strength model parameter, -5.19 was used.
The first dimension evaluation model is obtained by detecting sub-index driving quality index RQI, anti-skid performance index SRI, road surface damage index PCI, rut depth index RDI and road surface structural strength index PSSI, obtaining a first dimension evaluation index road surface performance condition PPC through weight calculation of the sub-indexes, and calculating through formula (6),
PPC＝wPCIPCI+wRQIRQI+wRDIRDI+wSRISRI+wPSSIPSSI (6)
the road surface damage index weight WPCIRunning quality index weight WRQIRut depth index weight WRDIAnti-skid performance index weight WSRIRoad surface structural strength weight WPSSIThe determination process of (2) is as follows:
(A1) constructing a first dimension evaluation index judgment matrix P by using original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix P is a result of pairwise comparison of indexes, and for an index system with the 5 indexes, the matrix form is as follows:
Figure RE-GDA0002522906190000112
(A2) calculating the first dimension evaluation index judgment matrix P, and calculating the weight value of each index by using a sum method;
(A3) adding each row of the first dimension evaluation index judgment matrix P, and then carrying out normalization processing on each element to obtain Pij'，
Figure BDA0002486279740000121
(A4) For p of each rowij' summing to get p1ij'，
Figure BDA0002486279740000122
(A5) P1ij' adding the columns forming the new matrix, then normalizing each element to obtain the weight value of each index,
Figure BDA0002486279740000123
said w1Is road surface damage index weight WPCI、w2As a running quality index weight WRQI、w3For rut depth index weight WRDI、w4Is the anti-skid performance index weight WSRI、w5For road surface structural strength weight WPSSI，
The optimal value obtained by the calculation of the first dimension evaluation index weight is as follows, WPCIFor the road surface damage index weight, the expressway and the first-level highway adopt 0.35; wRQIAs a running quality index weight, highThe speed road and the first-level road adopt 0.3; wRDIFor track depth index weight, 0.15 is adopted for a highway and a first-level highway; wSRIFor the anti-skid performance index weight, the highway and the first-level highway adopt 0.1; wPSSIFor the structural strength weight of the road surface, the expressway and the first-level highway adopt 0.1, the scoring accuracy of the PPC of the road surface performance condition can be improved through the calculation of the first-dimension evaluation index weight, as shown in the table 1,
TABLE 1 first dimension evaluation model PPC each subentry index weight
Figure BDA0002486279740000124
Figure BDA0002486279740000131
Step (B), constructing a second dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the second dimension evaluation model is obtained by detecting a surface layer high-temperature performance index HTPM, a lower layer high-temperature performance index HTPL, an upper layer crack resistance index CRI and a base layer mechanical performance index MPI in sub-indexes and calculating the sub-indexes by weight to obtain a second dimension evaluation index pavement material condition RMC;
the middle-surface-layer high-temperature performance index HTPM is judged according to a middle-surface-layer hamburger rutting test, and the grade is superior to 90 minutes when the numerical value of the middle-surface-layer hamburger rutting is less than 1.4 mm; between 1.4 and 2.4mm is 80 points in the grade; the grade difference is 60 minutes when the diameter is larger than 2.4 mm;
the lower layer high-temperature performance index HTPL is judged according to a lower layer hamburger rutting test, and the grade is superior to 90 minutes when the numerical value of the lower layer hamburger rutting is less than 4.1 mm; 80 points in the grade between 4.1mm and 7.3 mm; the grade difference is 60 minutes when the diameter is more than 7.3 mm;
the CRI is determined by the fracture energy test of the upper layer, and when the fracture energy value of the upper layer is more than or equal to 700J/m2The grade is superior to 90 points; at 300-700J/m 280 points in the grade are between; less than or equal to 300J/m2Is a gradeThe difference is 60 minutes;
the base layer mechanical property index MPI is judged according to an unconfined compressive strength test, and the grade is superior to 90 minutes when the unconfined compressive strength is greater than 7.3 Mpa; 80 minutes in the grade between 4.6 and 7.3 Mpa; the grade difference is 60 minutes when the pressure is less than 4.6 MPa.
The index grade division and the index value are shown in tables 2 and 3.
TABLE 2 second dimension evaluation model index rating
Figure BDA0002486279740000132
Figure BDA0002486279740000141
TABLE 3 evaluation of the second dimension model
Evaluation index Grade 1 (excellent) Grade 2 (middle) Grade 3 (poor)
HTPM 90 80 60
HTPL 90 80 60
CRI 90 80 60
MPI 90 80 60
And the second dimension evaluation index is calculated by weight to obtain the road surface material condition RMC, and is calculated by a formula (7),
RMC＝wHTPMHTPM+wHTPLHTPL+wCRICRI+wMPIMPI (7)
the middle-layer high-temperature performance index weight WHTPMLower layer high temperature performance index weight WHTPLUpper layer crack resistance index weight WCRIBasic mechanical property index weight WMPIThe determination process of (2) is as follows:
(B1) and constructing a second dimension evaluation index judgment matrix Q by using original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix Q is a result of pairwise comparison of indexes, and for an index system with the 4 indexes, the matrix form is as follows:
Figure RE-GDA0002522906190000142
(B2) calculating the obtained second dimension evaluation index judgment matrix Q, and calculating the weight value of each index by using a sum method;
(B3) adding each row of the second dimension evaluation index judgment matrix Q, and then carrying out normalization processing on each element to obtain Qij'，
Figure BDA0002486279740000151
(B4) For each row qij' summing to get q1ij'，
Figure BDA0002486279740000152
(B5) Q1ij' adding the columns forming the new matrix, then normalizing each element to obtain the weight value of each index,
Figure BDA0002486279740000153
the w11Is the high-temperature performance index weight W of the middle layerHTPM，w12Is the weight W of the high temperature performance index of the lower layerHTPL、w13Is the upper layer crack resistance index weight WCRI、w14Is the basic mechanical property index weight WMPI，
According to the calculation of the second dimension evaluation index weight, the optimal value is as follows: wHTPMThe weight of the high-temperature performance index of the middle surface layer is 0.3 for the expressway and the first-level expressway; wHTPLThe weight of the high-temperature performance index of the lower layer is 0.25 for the expressway and the first-level highway; wCRIThe anti-crack index weight of the upper layer is 0.15 for the expressway and the first-level highway; wMPIFor the base mechanical property index weight, 0.3 is adopted for the expressway and the first-level highway, and the accuracy of the score of the pavement material condition RMC can be improved through the calculation of the second-dimension evaluation index weight, as shown in Table 4,
TABLE 4 second-dimension evaluation model RMC each subentry index weight
Figure BDA0002486279740000154
Step (C), evaluating the long-term performance of the expressway bituminous pavement sequentially through the combination of the first dimension evaluation model and the second dimension evaluation model to obtain the long-term performance evaluation grade of the expressway bituminous pavement, comprising the following steps,
(C1) the long-term performance of the highway asphalt pavement is evaluated for the first time through a first dimension evaluation model, and if the PPC (point to point) of the pavement performance is greater than or equal to 90 minutes, the long-term performance of the highway asphalt pavement is excellent; if the road surface performance condition PPC is less than 90 minutes and more than or equal to 80 minutes, executing (C2), and carrying out secondary evaluation according to the road surface performance condition PPC; if the PPC of the pavement performance condition is less than 80 minutes and more than or equal to 70 minutes, the long-term performance of the expressway asphalt pavement is inferior; if the PPC of the pavement performance condition is less than 70 minutes, the long-term performance of the asphalt pavement of the high-speed highway is poor, as shown in Table 5; if the long-term performance of the expressway asphalt pavement is excellent, the expressway asphalt pavement does not need to be treated; if the expressway is inferior or poor, comprehensive treatment needs to be carried out according to the subentry indexes, for example, according to the PCI indexes, which measures are adopted for treatment is determined.
TABLE 5 road surface Long-term Performance grading of first dimension evaluation model
Evaluation index ≥90 Less than 90 and more than or equal to 80 Less than 80 and more than or equal to 70 ＜70
PPC Superior food Performing second dimension evaluation Next time Difference (D)
(C2) Performing secondary evaluation through the pavement performance condition PPC, and if the pavement material condition RMC is more than or equal to 90 minutes, the long-term performance of the expressway asphalt pavement is good; if the PPC of the pavement performance condition is less than 90 minutes and more than or equal to 80 minutes, the long-term performance of the asphalt pavement of the expressway is medium; if the PPC of the pavement performance condition is less than 80 minutes and more than or equal to 70 minutes, the long-term performance of the expressway asphalt pavement is inferior; if the road surface performance condition PPC is less than 70 minutes, the long-term performance of the highway asphalt road surface is poor, if the highway road surface material condition index (RMC) is evaluated to be good and medium, the treatment is not needed, if the highway is evaluated to be poor, the treatment is needed according to the subentry indexes, and if the highway is evaluated to be poor, the treatment is determined to be carried out according to the upper layer crack resistance index CRI index, and the treatment is carried out according to the measures, wherein the measures are shown in the table 6.
TABLE 6 Long-term performance grading of a road for a second-dimension evaluation model
Evaluation index ≥90 Less than 90 and more than or equal to 80 Less than 80 and more than or equal to 70 ＜70
RMC Good wine In Next time Difference (D)
The following description describes a specific implementation case according to the multidimensional expressway asphalt pavement long-term performance evaluation method.
The town highway starts from a Dane junction, is crossed with the Nanjing to Taicang highway in the gold Tan city to the south, is connected with the NingHang highway through Liyang south and is planned to be constructed into Liyang to Guangde highway, so that the important component of the 'vertical five' line is planned for the highway in Jiangsu province, the full length of the highway is 65.66 kilometers, and the project is built into a pass vehicle in 2007 and is up to now for 12 years. The long-term performance detection and evaluation are carried out on the highway pavement at the 10 th year of traffic,
TABLE 7 ZHENLi expressway structure type
Figure BDA0002486279740000171
(1) A first dimension evaluation model evaluation is performed,
according to the detection result of each index of the first dimension, the score of each index of the first dimension is obtained, as shown in table 8,
TABLE 8 first dimension test results
Index (I) RQI SRI PCI RDI PSSI
Results 91 74 95 90 76
PPC＝91*0.3+74*0.1+95*0.35+90*0.15+76*0.1＝89.1
The PPC result was 89.1, and according to table 2, the second dimension detection evaluation was performed;
(2) second dimension evaluation model evaluation is performed, and scores of each index of the second dimension are obtained according to the detection result of each index of the second dimension, as shown in table 9,
TABLE 9 second dimension test results
Index (I) HTPM HTPL CRI MPI
Results
80 80 80 80
RMC＝80*0.3+80*0.25+80*0.15+80*0.3＝80
The RMC result was 80, and the evaluation rating of the long-term performance of the asphalt pavement for the Zhe Li expressway was middle according to Table 6.
Note: the index weight of each sub-item of the pavement performance condition index (PPC) is selected by referring to JTG-5210 and 2018 'assessment standard of road technical condition'.
In conclusion, the method for evaluating the long-term performance of the multi-dimensional highway asphalt pavement disclosed by the invention is used for evaluating the long-term performance of the highway asphalt pavement which is already on traffic for more than 8 years. The method comprises the steps of firstly, detecting and analyzing the long-term performance of a road surface from a macroscopic angle, namely, from the two aspects of road surface performance and structural performance from a first dimension to obtain a comprehensive evaluation value PPC of the first dimension, judging the long-term performance of the expressway based on the comprehensive evaluation value PPC of the first dimension, and determining whether to evaluate the long-term performance of a second dimension. And secondly, performing second-dimension evaluation from a viewpoint of mesopic based on the first-dimension evaluation result, and performing pavement material performance detection analysis to obtain a second-dimension comprehensive evaluation value RMC. And finally, judging the long-term performance of the expressway based on the second-dimension comprehensive evaluation value RMC. From a macroscopic view to a microscopic view, a multi-dimensional decision index system of the expressway bituminous pavement is established, and the multi-dimensional indexes are adopted for evaluation, so that on one hand, the long-term performance of the expressway bituminous pavement can be accurately evaluated, on the other hand, the multi-dimensional decision index system can be used as an important basis for maintenance decision, and the expressway bituminous pavement maintenance decision method has a good application prospect.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are given by way of illustration of the principles of the present invention, and that various changes and modifications may be made without departing from the spirit and scope of the invention as defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (8)

1. The method for evaluating the long-term performance of the expressway bituminous pavement based on multiple dimensions is characterized by comprising the following steps of: can evaluate the long-term performance of the asphalt pavement of the expressway which has been on traffic for more than 8 years, comprises the following steps,
step (A), constructing a first dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the first dimension evaluation model is obtained by detecting sub-index running quality index RQI, anti-skid performance index SRI, pavement damage index PCI, rut depth index RDI and pavement structural strength index PSSI, and calculating the sub-indexes by weight to obtain a first dimension evaluation index pavement performance condition PPC;
step (B), constructing a second dimension evaluation model for evaluating the long-term performance of the asphalt pavement of the expressway, wherein the second dimension evaluation model is used for obtaining a second dimension evaluation index pavement material condition RMC by detecting a surface layer high-temperature performance index HTPM, a lower layer high-temperature performance index HTPL, an upper layer crack resistance index CRI and a base layer mechanical performance index MPI in sub-indexes and calculating the sub-indexes through weights;
and (C) evaluating the long-term performance of the expressway asphalt pavement sequentially through the combination of the first dimension evaluation model and the second dimension evaluation model to obtain the evaluation grade of the long-term performance of the expressway asphalt pavement.
2. The multidimensional-based highway asphalt pavement long-term performance evaluation method according to claim 1, characterized in that: step (A), the running quality index RQI is obtained by calculation through a formula (1),
Figure RE-FDA0002522906180000011
wherein IRI is international flatness index and the unit is m/km; a is0For the first driving quality coefficient, 0.026 is adopted for the expressway and the first-level highway; a is1For the second running quality coefficient, the expressway and the first-level expressway adopt 0.65;
the anti-skid performance index SRI is obtained by calculating the formula (2),
Figure RE-FDA0002522906180000021
wherein SFC is a transverse force coefficient, SRImin is a calibration parameter, and 35 is adopted; a is228.6 is adopted as the first anti-skid performance parameter; a is3For the second anti-skid performance parameter, -0.015;
the pavement damage index PCI is calculated by a formula (3),
PCI＝100-a4DRa5(3)
wherein DR is the pavement damage rate, and the unit is%; a is415 is adopted as the damage coefficient of the first asphalt pavement; a is5The pavement damage coefficient of the second asphalt pavement is 0.412;
the rut depth index RDI is obtained by calculation according to a formula (4),
Figure RE-FDA0002522906180000022
wherein RD is the rutting depth; RDa is a rut depth parameter, using 10; RDb is the rut depth parameter, 40; a is6Adopting 1 as a first rut depth model parameter; a is7For the second rut depth model parameter, adopt 3;
the road surface structural strength index PSSI is obtained by calculation according to a formula (5),
Figure RE-FDA0002522906180000023
wherein, SSR is road surface structure coefficient and is road surface deflection standard value lRDeflection representative deflection l measured with road surface0The ratio of (A) to (B); a is915.71 is adopted as a first road surface structure strength model parameter; a is10For the second road surface structure strength model parameter, -5.19 was used.
3. The method for evaluating the long-term performance of the multi-dimensional highway asphalt pavement according to claim 2, characterized in that: and (A) detecting a sub-index driving quality index RQI, an anti-skid performance index SRI, a road surface damage index PCI, a rut depth index RDI and a road surface structural strength index PSSI, calculating the sub-indexes by weight to obtain a first dimension evaluation index road surface performance condition PPC, and calculating by a formula (6).
PPC＝wPCIPCI+wRQIRQI+wRDIRDI+wSRISRI+wPSSIPSSI (6)
Wherein, WPCIFor the road surface damage index weight, the expressway and the first-level highway adopt 0.35; wRQIFor the weight of the running quality index, the highway and the first-level highway adopt 0.3; wRDIFor track depth index weight, 0.15 is adopted for a highway and a first-level highway; wSRIFor the anti-skid performance index weight, the highway and the first-level highway adopt 0.1; wPSSIFor the structural strength weight of the pavement, the highway and the first-level highway adopt 0.1.
4. The multidimensional-based highway asphalt long-term performance evaluation method according to claim 3, wherein: the road surface damage index weight WPCIRunning quality index weight WRQIRut depth index weight WRDIAnti-skid performance index weight WSRIRoad surface structural strength weight WPSSIThe determination process of (2) is as follows:
(A1) constructing a first dimension evaluation index judgment matrix P by using original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix P is a result of pairwise comparison of indexes, and for an index system with the 5 indexes, the matrix form is as follows:
Figure RE-FDA0002522906180000031
(A2) calculating the first dimension evaluation index judgment matrix P, and calculating the weight value of each index by using a sum method;
(A3) adding each column of the first dimension evaluation index judgment matrix P, and normalizing each elementGet pij'，
Figure RE-FDA0002522906180000041
(A4) For p of each rowij' summing to get p1ij'，
Figure RE-FDA0002522906180000042
(A5) P1ij' adding the columns forming the new matrix, then normalizing each element to obtain the weight value of each index,
Figure RE-FDA0002522906180000043
said w1Is road surface damage index weight WPCI、w2As a running quality index weight WRQI、w3For rut depth index weight WRDI、w4Is the anti-skid performance index weight WSRI、w5For road surface structural strength weight WPSSI。
5. The multidimensional-based highway asphalt pavement long-term performance evaluation method according to claim 1, characterized in that: step (B), the middle-surface layer high-temperature performance index HTPM is judged through a middle-surface layer hamburger rutting test, and the grade is superior to 90 minutes when the value of the middle-surface layer hamburger rutting is less than 1.4 mm; between 1.4 and 2.4mm is 80 points in the grade; the grade difference is 60 minutes when the diameter is larger than 2.4 mm;
the lower layer high-temperature performance index HTPL is judged according to a lower layer hamburger rutting test, and the grade is superior to 90 minutes when the numerical value of the lower layer hamburger rutting is less than 4.1 mm; 80 points in the grade between 4.1mm and 7.3 mm; the grade difference is 60 minutes when the diameter is more than 7.3 mm;
the CRI is judged by the upper layer fracture energy test, and the grade is 90 minutes when the numerical value of the upper layer fracture energy is more than or equal to 700J/m 2; 80 points in the grade between 300 and 700J/m 2; the grade difference is less than or equal to 300J/m2 and is 60 points;
the base layer mechanical property index MPI is judged according to an unconfined compressive strength test, and the grade is superior to 90 minutes when the unconfined compressive strength is greater than 7.3 Mpa; 80 minutes in the grade between 4.6 and 7.3 Mpa; the grade difference is 60 minutes when the pressure is less than 4.6 MPa.
6. The method for evaluating the long-term performance of the multi-dimensional highway asphalt pavement according to claim 5, wherein the method comprises the following steps: step (B), the second dimension evaluation model is obtained by detecting the high-temperature performance index HTPM of the upper layer, the high-temperature performance index HTPL of the lower layer, the crack resistance index CRI of the upper layer and the mechanical performance index MPI of the base layer in the sub-indexes, calculating the sub-indexes by weight to obtain the second dimension evaluation index pavement material condition RMC, and calculating by a formula (7),
RMC＝wHTPMHTPM+wHTPLHTPL+wCRICRI+wMPIMPI (7)
wherein, WHTPMThe weight of the high-temperature performance index of the middle surface layer is 0.3 for the expressway and the first-level expressway; wHTPLThe weight of the high-temperature performance index of the lower layer is 0.25 for the expressway and the first-level highway; wCRIThe weight of the crack resistance index of the upper layer is 0.15 for the expressway and the first-level highway; wMPIThe weight of the mechanical property index of the basic level is 0.3 for the expressway and the first-level highway.
7. The multidimensional-based highway asphalt long-term performance evaluation method according to claim 6, wherein: a step (B) of weighting the intermediate layer high temperature performance index WHTPMLower layer high temperature performance index weight WHTPLUpper layer crack resistance index weight WCRIBasic mechanical property index weight WMPIThe determination process of (2) is as follows:
(B1) and constructing a second dimension evaluation index judgment matrix Q by utilizing original data obtained by questionnaire survey of experts, wherein the first dimension evaluation index judgment matrix Q is a result of pairwise comparison of indexes, and for an index system with the 4 indexes, the matrix form is as follows:
Figure RE-FDA0002522906180000061
(B2) calculating the obtained second dimension evaluation index judgment matrix Q, and calculating the weight value of each index by using a sum method;
(B3) adding each row of the second dimension evaluation index judgment matrix Q, and then carrying out normalization processing on each element to obtain Qij'，
Figure RE-FDA0002522906180000062
(B4) For each row qij' summing to get q1ij'，
Figure RE-FDA0002522906180000063
(B5) Q1ij' adding the columns forming the new matrix, then normalizing each element to obtain the weight value of each index,
Figure RE-FDA0002522906180000064
the w11Is the high-temperature performance index weight W of the middle layerHTPM，w12Is the weight W of the high temperature performance index of the lower layerHTPL、w13Is the upper layer crack resistance index weight WCRI、w14Is the basic mechanical property index weight WMPI。
8. The multidimensional-based highway asphalt pavement long-term performance evaluation method according to claim 1, characterized in that: step (C), the long-term performance of the asphalt pavement of the expressway is evaluated sequentially through the combination of the first dimension evaluation model and the second dimension evaluation model, the method comprises the following steps,
(C1) performing primary evaluation on the expressway through a first dimension evaluation model, and if the PPC (pavement performance condition) is greater than or equal to 90 minutes, determining that the expressway is excellent; if the road surface performance condition PPC is less than 90 minutes and more than or equal to 80 minutes, executing (C2), and carrying out secondary evaluation according to the road surface performance condition PPC; if the PPC of the pavement performance condition is less than 80 minutes and more than or equal to 70 minutes, the expressway is divided into two times; if the PPC of the pavement performance is less than 70 minutes, the expressway is poor;
(C2) performing secondary evaluation through the pavement performance condition PPC, and if the pavement material condition RMC is more than or equal to 90 minutes, judging that the expressway is good; if the PPC of the pavement performance is less than 90 minutes and more than or equal to 80 minutes, the expressway is medium; if the PPC of the pavement performance condition is less than 80 minutes and more than or equal to 70 minutes, the expressway is divided into two times; if the road surface performance condition PPC is less than 70 minutes, the highway is poor.
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Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112132431A (en) * 2020-09-15 2020-12-25 交通运输部公路科学研究所 Method for detecting gap connectivity of multi-layer porous pavement structure
CN112950020A (en) * 2021-03-01 2021-06-11 上海应用技术大学 Asphalt pavement comprehensive performance weight determination method based on modified analytic hierarchy process
CN114003310A (en) * 2021-10-29 2022-02-01 深信服科技股份有限公司 Parameter selection method, device, equipment and medium based on service scene
CN114486571A (en) * 2022-01-07 2022-05-13 武汉理工大学 Pavement comprehensive performance evaluation method based on pavement service performance and structural performance
CN114970102A (en) * 2022-04-25 2022-08-30 北京工业大学 Evaluation method for full-chain ecological design, construction and operation and maintenance of asphalt pavement

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101818476A (en) * 2010-01-28 2010-09-01 湖北省高速公路实业开发有限公司 Bituminous pavement intelligent maintaining system based on Internet B/S network architecture
US20120123969A1 (en) * 2010-11-15 2012-05-17 Messmer Peter F Methods and Processes of Road Use Evaluation and Regulation
CN103091480A (en) * 2013-01-07 2013-05-08 河北工业大学 Entropy weight-based underground road bituminous pavement service performance evaluation method
CN110501221A (en) * 2019-08-12 2019-11-26 武汉理工大学 A kind of pavement performance evaluation method based on Pavement Condition and material property

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101818476A (en) * 2010-01-28 2010-09-01 湖北省高速公路实业开发有限公司 Bituminous pavement intelligent maintaining system based on Internet B/S network architecture
US20120123969A1 (en) * 2010-11-15 2012-05-17 Messmer Peter F Methods and Processes of Road Use Evaluation and Regulation
CN103091480A (en) * 2013-01-07 2013-05-08 河北工业大学 Entropy weight-based underground road bituminous pavement service performance evaluation method
CN110501221A (en) * 2019-08-12 2019-11-26 武汉理工大学 A kind of pavement performance evaluation method based on Pavement Condition and material property

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
巩建 等: "基于弯沉的沥青路面使用性能评价模型" *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112132431A (en) * 2020-09-15 2020-12-25 交通运输部公路科学研究所 Method for detecting gap connectivity of multi-layer porous pavement structure
CN112950020A (en) * 2021-03-01 2021-06-11 上海应用技术大学 Asphalt pavement comprehensive performance weight determination method based on modified analytic hierarchy process
CN114003310A (en) * 2021-10-29 2022-02-01 深信服科技股份有限公司 Parameter selection method, device, equipment and medium based on service scene
CN114486571A (en) * 2022-01-07 2022-05-13 武汉理工大学 Pavement comprehensive performance evaluation method based on pavement service performance and structural performance
CN114486571B (en) * 2022-01-07 2023-11-07 武汉理工大学 Pavement comprehensive performance evaluation method based on pavement service performance and structural performance
CN114970102A (en) * 2022-04-25 2022-08-30 北京工业大学 Evaluation method for full-chain ecological design, construction and operation and maintenance of asphalt pavement
CN114970102B (en) * 2022-04-25 2023-02-17 北京工业大学 Evaluation method for full-chain ecological design, construction and operation and maintenance of asphalt pavement

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