The traditional evaluation method of construction quality for asphalt pavement has gradually lagged behind the pace of development of the road industry. Big data, Internet of Things (IoT), and intelligent sensing technology have been reflected in the field of road engineering, but these technologies also have technical shortcomings in terms of applicability, durability, real-time performance, and portability in practice. To provide a new method for construction quality evaluation of asphalt pavement, this study developed an intelligent sensing aggregate (ISA) with low cost and high precision based on the 3D printing and Internet of Things (IoT) technology. Based on the laboratory test and field test, the sensing characteristics, high-temperature resistance, and mechanical properties of ISA are analyzed to verify the reliability of ISA. Through the quantitative analysis of ISA perception data, the Driving Perception Index (DPI) is proposed. By analyzing the quantitative correlation between the spatial angle of ISA and the compaction degree, the quantitative correlation between the DPI, International Roughness Index (IRI), and the deflection value, the evaluation standard of construction quality for asphalt pavement is established. The result shows that the best baud rate for ISA is 9600 bps, and the corresponding data transmission distance is 350 m. In the range of 6 m, the cars, trucks, trailers, and buses can be perceived by ISA. The maximum operating temperature of ISA is up to 200°C. Embedding ISA into asphalt mixture has no significant effect on original gradation of asphalt mixture. The established evaluation standard of construction quality for asphalt pavement takes into account the compaction quality, the requirements of bearing capacity, and the driving comfort of asphalt pavement, which is suitable for expressway and first-class highway.
Pavement construction is the key part of the whole asphalt pavement engineering. The construction quality of asphalt pavement is closely related to its road performance [
Modulus is also one of the important indexes of construction quality evaluation for asphalt pavement. Modulus can directly reflect the bearing capacity of pavement structure and judge the quality of pavement [
Intelligent sensing technology is the advanced technology of intelligent manufacturing and the Internet of Things (IoT), which is of great significance. In recent years, intelligent sensor technology has developed rapidly in road engineering. Hasni et al. present a surface sensing approach for the detection of bottom-up cracking in asphalt concrete (AC) pavements. The proposed method was based on the interpretation of compressed data stored in memory cells of a self-powered wireless sensor (SWS) with nonconstant injection rates [
In summary, the traditional evaluation method of construction quality for asphalt pavement has gradually lagged behind the pace of development of the road industry. At present, the big data, Internet of Things (IoT), and intelligent sensing technology have been reflected in the field of road engineering, but these technologies also have technical shortcomings in terms of applicability, durability, real-time performance, and portability in practice, which to some extent restricts the promotion of the new technologies and new materials in the road industry. In this context, this study developed an intelligent sensing aggregate (ISA) with a small volume, low cost, and high precision based on the Internet of Things technology. Firstly, the reliability of ISA is evaluated from the aspects of data transmission sensitivity, vehicle perception, high-temperature resistance, and mechanical properties. Then, the evaluation standard of construction quality for asphalt pavement considering the compaction quality, the bearing capacity, and the driving comfort is established based on ISA perception data, which provides a new method for construction quality evaluation of asphalt pavement.
The angle sensor module is selected as the main chip of ISA, and its technical parameters are shown in Table
Technical parameters of angular transducer module.
Parameters | Index value |
---|---|
Size | Length: 15 mm; width: 15 mm; thickness: 2 mm |
Supply voltage | 3.3–5 V |
Working current | <10 mA |
Communication mode | Serial communication |
Output data | Triaxial angle |
The wireless transmission module is used for full-duplex wireless transparent transmission of the collected data of the angle sensor, and the technical parameters are shown in Table
Technical parameters of wireless transmission module.
Parameters | Index value |
---|---|
Size | Length: 15 mm; width: 15 mm; thickness: 2 mm |
Transmission distance under open field | 600 m without package |
Input voltage | 3.7 V |
Working current | 60 mA (emission) and 40 mA (receive) |
The maximum transmit power | 22 dBm |
Control mode | Serial command |
The wireless transmission modules are usually used in pairs, one as a transmitter and the other as a receiver.
The external packaging layer of ISA was prepared by nylon 6/66 copolymer based on 3D printing technology. The material has excellent heat resistance and mechanical properties [
Technical indicators of the nylon 6/66 copolymer.
Parameters | Units | Index value |
---|---|---|
Density | g/cm3 (21.5°C) | 1.53 |
Vicat softening temperature | °C | 180 |
Melting temperature | °C | 190 |
Young's modulus | MPa | 2350 |
Tensile strength | MPa | 67.2 |
Elongation at break | % | 11.8 |
Flexural modulus | MPa | 1700 |
Bending strength | MPa | 97.4 |
The plastic steel soil and high-temperature adhesive tape with a temperature resistance of 350°C were used as the internal insulation layer of ISA, as shown in Figure
Internal insulation layer materials.
Battery module system.
Based on the 3D printing and Internet of Things (IoT) Technology, an intelligent sensing aggregate (ISA) with low cost and high precision is developed. Based on the laboratory test and field test, the sensing characteristics, high-temperature resistance, and mechanical properties of ISA are analyzed to verify the reliability of ISA. By establishing the quantitative correlation between the ISA sensing data, the compaction degree, the IRI, and the deflection values, the evaluation standard of construction quality for asphalt pavement which can comprehensively consider the compaction quality, the requirements of bearing capacity, and the driving comfort of asphalt pavement are proposed.
An intelligent sensing aggregate (ISA) with a particle size of 20 mm was prepared by using the wireless transmission module, the angle sensor, and the rechargeable lithium battery module. The ISA was packaged with 3D printing technology and high-strength and high-temperature-resistant materials to controlling the shape, ensuring mechanical strength and signal stability. The preparation process is shown in Figure
The preparation process of ISA.
The compressive strength of the finished ISA can reach 80 MPa. The ISA can obtain the angle data in the three directions of XYZ. The spatial angle was taken as indicators for analysis in this study. The calculation method is as shown in the following formula:
This study used Python programming language to develop data acquisition and analysis software of ISA, as shown in Figure
The data acquisition and analysis software of ISA.
The ISA data acquisition system (IDAS) is developed based on the technology of the Internet of Things (IoT). The size of IDAS is the length of 24 cm, the width of 17 cm, and the height of 10 cm, as shown in Figure
The ISA data acquisition system (IDAS).
The ISA was buried in asphalt pavement before pavement compaction to test the signal transmission performance under different baud rates (9600 bps, 19200 bps, 38400 bps, 51200 bps, and 115200 bps). The buried depth is 10 cm, as shown in Figure
Signal transmission performance test of ISA.
The signal strength of ISA can be obtained through the serial port command of the wireless transmission module during the test. The test site is in an open area, and the test results are shown in Table
Test result of wireless transmission performance test.
Baud rates (bps) | Wireless transmission distance(m) | Signal strength (dBm) |
---|---|---|
9600 | 350 | −53.7 |
19200 | 320 | −57.8 |
38400 | 290 | −69.2 |
57600 | 270 | −73.4 |
115200 | 240 | −78.6 |
As shown in Table
When the asphalt pavement is finished, the internal aggregate is in close contact or embedded state, and there is an interaction force between aggregate particles [
Disturbance characteristics of aggregates.
In Figure
Test Scheme for disturbance characteristics of ISA.
In Figure
Test results of driving perception performance of ISA.
Vehicle type | Calculating parameter | Pavement parameters | |
---|---|---|---|
Car | Top layer: 6 cm AC-16 | ||
Truck | Middle layer: 7 cm AC-20 | ||
Trailer | Bottom layer: 8 cm AC-25 | ||
Bus | Embedded position: middle layer |
From Table
The mixing and molding temperature for asphalt mixtures is generally not more than 200°C [
High-temperature resistance test of ISA.
Test results of high-temperature resistance of ISA.
From Figures
Based on the laboratory tests, the mechanical properties of the ISA and its mechanical properties in AC-25 gradation asphalt mixtures were studied. The technical performance comparison between the ISA and traditional limestone aggregates is shown in Table
Comparison of physical properties between ISA and traditional limestone aggregate.
Index | Units | Limestone aggregates | ISA | Technical standard | Test methods |
---|---|---|---|---|---|
Crush value | % | 24.6 | 23.5 | ≤28 | T0316 |
Abrasion value | % | 22.4 | 19.6 | ≤30 | T0317 |
Compressive strength | MPa | 62.9 | 65.8 | ≥50 | T0616 |
From Table
Comparison of dynamic modulus test results. (a) Test specimens. (b) Test result of dynamic modulus. (c) The state of the ISA after test
From Figure
Difference analysis of test results.
Source of variance | |||
---|---|---|---|
Dynamic modulus of the ordinary asphalt mixtures and the asphalt mixtures embedded with ISA | 7.85 | 0.092 | 10.6 |
Crush value of ISA and limestone aggregates | 13.2 | 0.083 | 19.7 |
Abrasion value of ISA and limestone aggregates | 22.5 | 0.076 | 28.3 |
Compressive strength of ISA and limestone aggregates | 17.4 | 0.105 | 22.6 |
According to the hypothesis of SPSS two-factor variance analysis, if the
To propose a construction quality evaluation standard of asphalt pavement based on the ISA perception data, the compaction degree, International Roughness Index (IRI), and the deflection value are selected as reference indexes. The compaction degree can reflect the compaction quality of new asphalt pavement, the IRI can reflect the driving comfort of asphalt pavement, and the deflection value can reflect the bearing capacity of asphalt pavement [
According to the layout schemes in Section
The road compaction scheme.
Compaction phase | Compact machinery | Compaction temperature (°C) | Compaction (times) |
---|---|---|---|
Initial pressure | Static roller | 150 | 2 |
Repressing | Vibratory roller | 135 | 6 |
Final pressure | Heavy tire roller | 90 | 2 |
Testing pressure | Static roller | 30 | 3 |
From Table
The relationship between the ISA spatial angle and the compaction degree. (a) Initial pressure. (b) Repressing. (c) Final pressure. (d) Testing stage.
From Figure
The Driving Perception Index (DPI) proposed in this study refers to the driving comfort of drivers based on the ISA perception data, which is used to evaluate the construction quality of asphalt pavement in this study. The better the driver’s comfort, the better the construction quality of the pavement. The DPI criteria are determined by analyzing the relationship between DPI, IRI, and deflection value. The IDAS is fixed on the roof of the vehicle for data collected, as shown in Figure
The test scenario of the Driving Perception Index (DPI).
According to the following steps, we collect the data and calculate the DPI value: Drive 5 km in a straight line at a speed of 80 km/h, collect a group of spatial angle data every 0.45 s, and make two trips in the same lane. A total of four groups of data were obtained, with 500 samples in each group Calculate the absolute value of the difference between two adjacent samples in each group data, and remove the maximum and minimum values Calculate the mean value of the difference between each group of samples, denoted as DPI1, DPI2, DPI3, and DPI4 Take the average value of DPI
The smaller the DPI value is, the higher the driving comfort is, and the better the pavement construction quality is.
The International Roughness Index (IRI) is the most widely used roughness index in the world, and most European countries use IRI as pavement roughness acceptance index. The calculation method of IRI is shown as follows:
The classification standard of IRI.
Pavement condition | Excellent | Good | Medium | Inferior | Bad |
---|---|---|---|---|---|
Value ranges of IRI (m/km) | ≤2.3 | >2.3, ≤3.5 | >3.5, ≤4.3 | >4.3, ≤5.0 | >5.0 |
The 20 different newly built road sections are selected for field tests, and the test section information is shown in Table
The test section information.
Sections | Length (km) | Pavement structure | Service time |
---|---|---|---|
1 | 6 | Top layer: 6 cm SBS-16 | 1 month |
2 | 6 | Middle layer: 7 cm AC-20 | 2 months |
3 | 6 | Bottom layer: 8 cm AC-25 | 2 months |
4 | 6 | Base: 36 cm cement stabilized macadam | 2 months |
5 | 6 | Subbase: 20 cm graded crushed stone | 2 months |
6 | 6 | 1 month | |
7 | 6 | 1 month | |
8 | 8 | Top layer: 4 cm AC-13C | 3 months |
9 | 8 | Middle layer: 6 cm AC-20 | 3 months |
10 | 8 | Bottom layer: 7 cm AC-25 | 1 month |
11 | 8 | Base: 30 cm cement stabilized macadam | 3 months |
12 | 8 | Subbase: 15 cm cement stabilized macadam | 3 months |
13 | 8 | 1 month | |
14 | 8 | 2 months | |
15 | 10 | Top layer: 5 cm SMA-13C | 2 months |
16 | 10 | Middle layer: 6 cm AC-20 | 2 months |
17 | 10 | Bottom layer: 7 cm AC-25 | 2 months |
18 | 10 | Base: 36 cm cement stabilized macadam | 3 months |
19 | 10 | Subbase: 20 cm graded crushed stone | 1 month |
20 | 10 | 1 month |
According to the test results, the test values of 12 typical sections are selected for analysis of the correlation between the IRI and DPI, as shown in Figure
The relationship between IRI and DPI.
From Figure
Evaluation standard of construction quality for asphalt pavement based on DPI.
Construction quality | Excellent | Good | Medium | Inferior | Bad |
---|---|---|---|---|---|
Value ranges of DPI (°) | ≤5.2 | >5.2, ≤6.8 | >6.8, ≤7.9 | >7.9, ≤9.6 | >9.6 |
The deflection value is the deformation of the pavement before and after the load acting on the pavement. The deflection index can reflect the bearing capacity of asphalt pavement. The Falling Weight Deflectometer (FWD) is generally used to detect the deflection value of asphalt pavement [
According to the “
The relationship between deflection value and DPI.
From Figure
In order to make the evaluation standard simultaneously consider the requirements of bearing capacity and driving comfort, the DPI value corresponding to the “excellent” level is corrected in this study, and the final evaluation standard is shown in Table
Evaluation standard of construction quality for asphalt pavement based on DPI.
Construction quality | Excellent | Good | Medium | Inferior | Bad |
---|---|---|---|---|---|
Value ranges of DPI (°) | ≤4.7 | >4.7, ≤6.8 | >6.8, ≤7.9 | >7.9, ≤9.6 | >9.6 |
Matters needing attention | (1) When the construction quality is “excellent” level, it must also meet the condition of | ||||
(2) The test mileage of DPI should not be less than 5 km and increased the testing times in the same lane when the test mileage is less than 5 km |
The evaluation standard of construction quality proposed in this study is applicable to the expressway and first-class highway.
Based on the Internet of Things technology, a low-cost and high-precision intelligent sensing aggregate (ISA) was developed by using high-strength and high-temperature-resistant materials, wireless transmission module, angular sensor, and rechargeable lithium battery module. Based on the laboratory test and field test, the sensing characteristics, high-temperature resistance, and mechanical properties of ISA were analyzed to verify the reliability of ISA and determine the working conditions of ISA.
The 9600 bps is recommended as the best transmission baud rate of ISA, and the corresponding data transmission distance is 350 m. In the range of 6 m, the cars, trucks, trailers, and buses can be perceived by ISA. The maximum operating temperature of ISA is up to 200°C. Embedding ISA into asphalt mixture has no significant effect on the original gradation of asphalt mixture.
The spatial angle of ISA
Through the quantitative analysis of ISA perceived data, the evaluation standard of construction quality for asphalt pavement based on the spatial angle of ISA and the DPI value is established. The standard takes into account the compaction quality, the bearing capacity, and the driving comfort requirements of asphalt pavement and is applicable to expressways and first-class highways.
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.
The authors declare no conflicts of interest.
Y. Z. investigated the study and validated the data; C. Z. was responsible for methodology and software. All authors have read and agreed to the published version of the manuscript.
This research was funded by the China Postdoctoral Science Foundation (2020M683402), Open Fund of Key Laboratory for Special Area Highway Engineering of Ministry of Education (Chang’an University) (300102210504), the Science and Technology Planning Project of Xi’an (2020KJRC0046), and the Natural Science Basic Research Program of Shaanxi (2021JQ-856).