CN110738636A - Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology - Google Patents
Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology Download PDFInfo
- Publication number
- CN110738636A CN110738636A CN201910863261.9A CN201910863261A CN110738636A CN 110738636 A CN110738636 A CN 110738636A CN 201910863261 A CN201910863261 A CN 201910863261A CN 110738636 A CN110738636 A CN 110738636A
- Authority
- CN
- China
- Prior art keywords
- asphalt mixture
- test piece
- testing
- digital image
- scanning
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30132—Masonry; Concrete
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Quality & Reliability (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Computer Graphics (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- Investigating Strength Of Materials By Application Of Mechanical Stress (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention provides methods and systems for testing the skid resistance of an asphalt mixture based on a digital image technology, wherein the method comprises the steps of preparing an asphalt mixture test piece, scanning the test piece by laser to obtain scanning data, obtaining a test piece structure evaluation index, and evaluating the skid resistance according to the structure evaluation index.
Description
Technical Field
The invention relates to the technical field of buildings, in particular to a method and a system for testing the anti-sliding performance of an asphalt mixture based on a digital image technology.
Background
The anti-skid performance of the pavement paved by the asphalt mixture is an important factor influencing the driving safety of the road, and serious traffic accidents can be caused by insufficient anti-skid performance of the pavement, so that the testing of the anti-skid performance of the surface of the asphalt mixture is very important for ensuring that the anti-skid performance of the pavement meets the requirements.
At present, the method for testing the surface skid resistance of the asphalt mixture mainly comprises a macrostructure depth method, a pendulum type friction meter method, a braking distance method, a wheel-locking trailer method, a slip rate method, a transverse force coefficient tester method and the like.
Macrostructure depth method: sanding and laser structuring depth gauges are currently common. The sand paving method is that sand with known volume is paved on a measuring point of a road surface to be tested, the covered area is measured and flattened, and the road surface structure depth is determined according to the ratio of the volume of the sand to the covered average area. The laser depth-of-construction instrument method combines a computer analysis technology and a laser measurement technology, utilizes a laser emitter to emit laser to a road surface and receives reflected laser from other angles, and further determines the depth of the detected road surface structure. However, the macrostructure depth method is sensitive to environmental factors, and accumulated water, accumulated snow, mud and the like all affect the detection result.
Pendulum tribometer method: according to the method, the anti-skid performance of the road surface is tested according to the energy loss of the rubber block on the road surface by utilizing the principle that the gravitational potential energy of the pendulum bob falling from a high position is equal to the sum of the friction work of the rubber block on the road surface and the residual gravitational potential energy according to the energy conservation rule. However, the method can only detect a single point, and is difficult to reflect the anti-skid performance of the whole road surface and low in working efficiency.
A braking distance method: since the road surface anti-skid performance is in inverse proportion to the braking distance of the vehicle during emergency braking, the braking distance can be used for reflecting the road surface anti-skid performance. The method determines the skid resistance of the road surface according to the road surface evaluation requirement through the braking distance of the automobile when the automobile is braked on the road surface, has higher requirement on the test road surface environment, and needs the vehicle during the test, so the use value is lower.
The method of locking wheels and towing the vehicle is that the towing vehicle is used to tow a single wheel test vehicle with standard tires to run on wet road surface at a constant speed of 60km/h, the test wheel is used to tow the towing vehicle in a locked state (the slip rate is 100% or the fixed slip rate is 86%), the test method is the anti-slip index SN. by dividing the friction force formula by the load P, and the test method is not suitable for a large range because the test equipment has large volume and definite limitation, and only can evaluate the instantaneous anti-slip performance in the locked state.
The method can measure variable slip rate and fixed slip rate, when measuring the fixed slip rate, the test equipment is similar to the locking wheel trailer method, only can measure the frictional resistance of the road surface under the state of certain specific slip rate, and is suitable for the state of low-speed driving of the automobile, and the variable slip rate can test the friction coefficient under different slip rates (0-100 percent).
Transverse force coefficient tester method: the method comprises a road surface friction coefficient tester method and a SCRIM transverse force coefficient tester method. The road surface friction coefficient tester method basically realizes the automation of the detection of the road surface skid resistance, but needs to be improved in the aspects of temperature, speed, the use state of tires and the like; the SCRIM transverse force coefficient tester method is suitable for large-area daily detection, but has large limitation on small-range detection and high equipment price.
At present, various methods and various testing devices are adopted for testing the skid resistance of the pavement formed by the asphalt mixture, different testing methods are suitable for different testing scenes, the evaluation standard of the testing result is not uniform , and even serious divergence exists in principle.
Disclosure of Invention
In light of the above-mentioned shortcomings and drawbacks of the prior art, an object of the present invention is to solve at least the above-mentioned problems in the prior art by providing or more and novel methods and systems for testing the skid resistance of asphalt mixture.
The aspect of the invention provides methods for testing the skid resistance of an asphalt mixture based on a digital image technology, which comprise the following steps:
preparing an asphalt mixture test piece;
laser scanning the test piece to obtain scanning data;
calculating a test piece structure evaluation index;
optimizing and determining a structural evaluation index to evaluate the anti-skid performance.
Preferably, the aggregate of the asphalt mixture test piece is basalt, and the asphalt is SBS modified asphalt with the type of AC, and has 3 groups of gradation.
Preferably, in any above, the laser scanning the test piece to obtain the scan data includes:
setting scanning parameters;
and carrying out laser scanning to obtain scanning point cloud data.
Preferably, the is characterized in that the scan parameters include at least of scan frequency, scan pattern, scan dot spacing and scan line width.
In any of the above, preferably, the step of obtaining the specimen structure evaluation index includes:
establishing a three-dimensional digital model of the test piece;
acquiring three-dimensional coordinate information;
and acquiring a test piece structure evaluation index according to the three-dimensional coordinate information.
Preferably, in any above, the creating a three-dimensional digital model of the test piece includes at least of the processes of packaging, exporting, and filling holes for the point cloud data.
Preferably, in any above, the obtaining three-dimensional coordinate information includes intercepting a cross-sectional curve and breaking the cross-sectional curve into points for processing the three-dimensional digital model.
In any of the aspects described above, the specimen structure evaluation index preferably includes at least of skewness Rsk and humpness Rku.
In any of the above, the specimen configuration evaluation index preferably further includes at least of an arithmetic mean Ra, a standard deviation of section Rq, a range Rz, an average wavelength La, an average slope Da, a root mean square Lq of wavelength, a root mean square Dq of slope, and a slope S1.
In any , it is preferable that at least structural evaluation indexes with high correlation with the surface swing value and/or the structural depth of the asphalt mixture are selected to evaluate the skid resistance of the asphalt mixture.
Another aspect of the present invention provides a system for testing anti-skid performance of asphalt mixture based on digital image technology, comprising a processor and a storage medium, wherein the storage medium stores a program designed according to the method for testing anti-skid performance of asphalt mixture based on digital image technology, and the program is executed by the processor to perform the following steps:
acquiring a test piece structure evaluation index according to the laser scanning point cloud data;
and selecting a structural evaluation index to evaluate the anti-skid performance.
Preferably, the system further comprises a laser scanning device, and the laser scanning device performs laser scanning on the asphalt mixture to obtain scanning point cloud data.
Any above scheme is preferable, the laser scanning device can set scanning parameters, and the scanning parameters include at least of scanning frequency, scanning mode, scanning point spacing and scanning line width.
Any of the above aspects may be preferably configured such that the laser scanning point cloud data is transferable to the storage medium.
Preferably, in any , the system further includes an asphalt mixture test piece manufacturing device.
The invention provides novel methods and systems for testing the anti-skid performance of an asphalt mixture based on a digital image technology, which are used for obtaining three-dimensional coordinates of the asphalt mixture by scanning the asphalt mixture with laser, further determining the structure evaluation index of the asphalt mixture and selecting a proper structure evaluation index to evaluate the anti-skid performance of the asphalt mixture.
Drawings
FIG. 1 is a schematic flow chart diagram of a preferred embodiment of a method for testing asphalt skid resistance based on digital image technology in accordance with the present invention.
FIG. 2 is a schematic surface diagram of the asphalt mixture test piece according to the embodiment shown in FIG. 1 of the method for testing the anti-slip performance of the asphalt mixture based on the digital image technology.
FIG. 3 is a schematic diagram of point cloud data obtained in the embodiment shown in FIG. 1 according to the method for testing the skid resistance of asphalt mixture based on digital image technology.
FIG. 4 is a schematic diagram of a three-dimensional digital model of a test piece according to the embodiment shown in FIG. 1 of the method for testing the skid resistance of the asphalt mixture based on the digital image technology.
FIG. 5 is a cross-sectional curve diagram of a test piece of the embodiment shown in FIG. 1 according to the method for testing the anti-slip performance of the asphalt mixture based on the digital image technology.
Detailed Description
For a better understanding of the present invention, reference will now be made in detail to the following examples. The embodiments are given by way of illustration only and not by way of limitation, and any insubstantial modifications, based on the present disclosure, may be made by those skilled in the art without departing from the scope of the present disclosure.
Example 1
As shown in FIG. 1, methods for testing the skid resistance of asphalt mixture based on digital image technology comprise the following steps:
s1, preparing an asphalt mixture test piece;
s2, laser scanning the test piece to obtain scanning data;
s3, obtaining a test piece structure evaluation index;
s4, evaluating the anti-skid performance according to the structure evaluation index.
In the step S1, the aggregate of the asphalt mixture test piece is basalt, and the asphalt is SBS modified asphalt with the type of AC and the total 3 groups of gradation.
In step S2, firstly, scanning parameters of the laser scanning device are set, where the scanning parameters include at least of scanning frequency, scanning mode, scanning point distance, and scanning line width, and then the test piece is subjected to laser scanning to obtain laser scanning point cloud data.
In step S3, the method includes the steps of:
s31, establishing a three-dimensional digital model of the test piece;
s32, acquiring three-dimensional coordinate information;
and S33, acquiring the test piece structure evaluation index according to the three-dimensional coordinate information.
The method comprises the steps of establishing a three-dimensional digital model of the test piece, packaging the point cloud data, exporting the point cloud data, and performing at least kinds of processing in hole filling processing, acquiring three-dimensional coordinate information, intercepting a section curve and breaking the section curve into points, wherein the test piece structure evaluation indexes comprise skewness Rsk and humpness Rku, and further comprise at least kinds of arithmetic mean value Ra, section standard deviation Rq, pole difference Rz, skewness Rsk, humpness Rku, mean wavelength La, mean slope Da, root mean square Lq of wavelength, root mean square Dq of slope, and slope S1.
In step S4, at least construction evaluation indexes with high correlation with the surface swing value and/or the construction depth of the asphalt mixture in step S3 are selected to evaluate the anti-skid performance of the asphalt mixture.
Example 2
When the asphalt mixture test piece is manufactured, basalt is selected as the aggregate of the test piece, SBS modified asphalt is selected as the asphalt, the type of the manufactured test piece is AC type, 3 groups of gradation are totally adopted, the test piece is manufactured under the optimal oilstone ratio according to the standard requirement, the size of the test piece is 300mm multiplied by 50mm, and the surface of the test piece is shown in figure 2.
The laser scanning device employs a Haekang-metered laser scanning system HP-L-20.8, the operating parameters of which are shown in Table 1:
TABLE 1 HP-L-20.8 MODEL THREE-DIMENSIONAL LASER SCANNING SYSTEM OPERATING PARAMETERS
When the test piece in this embodiment is scanned, the scanning frequency is set to 150000 dots/sec, the scanning mode is set to the sequential scanning, the dot pitch of the sequential scanning is 0.5mm, and the scanning line width is 50 mm. Fig. 3 shows point cloud data obtained by scanning the medium-value graded mixture test piece by the laser scanning device according to the set parameters.
And packaging, deriving and hole filling the point cloud data obtained by scanning of the laser scanning equipment to obtain a high-precision three-dimensional character model of the asphalt mixture test piece, wherein the high-precision three-dimensional character model is reconstructed according to the point cloud data shown in the figure 4 as shown in figure 3. And when the point cloud data is subjected to hole filling processing, a method of filling holes according to curvature is adopted.
For the obtained three-dimensional digital model, firstly, cutting a section curve at intervals of , and as shown in fig. 5, obtaining a schematic diagram of the section curve of the test piece when the intervals are set to be 2cm, then, cutting each section curve into 50000 points, thereby obtaining a three-dimensional coordinate of the surface elevation of the asphalt mixture test piece, and finally, calculating according to the three-dimensional coordinate of the time surface elevation to obtain a test piece structure evaluation index.
And selecting a structure evaluation index with high correlation between the structure evaluation index of the test piece and the surface swing value and structure depth of the asphalt mixture to evaluate the anti-sliding performance of the asphalt mixture, and selecting skewness Rsk and humpness Rku to evaluate the anti-sliding performance of the asphalt mixture in the embodiment.
The skewness Rsk and the humpness Rku are selected to evaluate the anti-skid performance of the asphalt mixture because the skewness Rsk and the humpness Rku have high correlation with the surface swing value (BPN) and the structure depth (MPD) of the asphalt mixture through verification.
As shown in table 2, the correlations between the 10 test piece structure evaluation indexes and the surface swing value and the structure depth of the asphalt mixture were calculated by using SPSS software, and it can be seen from table 2 that:
among 10 indexes represented by the three-dimensional space coordinate, which are 10 types of indexes represented by statistical indexes, 5 indexes with high correlation (greater than 0.7) with the asphalt mixture surface swing value (BPN) and the structure depth (MPD) are respectively an arithmetic mean value Ra, a section standard deviation Rq, a pole error Rz, a skewness Rsk and a hump degree Rku, wherein the skewness Rsk and the hump degree Rku have correlation with the asphalt mixture surface swing value (BPN) and the structure depth (MPD) of greater than 0.9, the skewness Rsk has highest correlation with the asphalt mixture surface swing value (BPN) and the structure depth (MPD) of greater than 0.96, the asphalt mixture surface swing value (BPN) and the structure depth (MPD) are two general indexes for representing the anti-skid performance, and the skewness Rsk, the asphalt mixture surface swing value (BPN) and the structure depth (MPD) have high correlation so far, the three-dimensional space coordinate system can represent the anti-skid performance of a road surface by adopting a laser scanning technology, and the asphalt mixture can be used for evaluating the anti-skid performance of a road surface.
Meanwhile, the anti-slip performance analysis of the asphalt mixtures with different grades in 3 shows that under the condition of the same asphalt mixture, the influence of the anti-slip performance with different grades is as follows: when the coarse material accounts for a relatively large amount and the fine material accounts for a relatively small amount, the optimal oilstone of the asphalt mixture is relatively low, and the anti-skid performance is best.
TABLE 2 correlation of the structural evaluation index with the surface swing value and the structural depth of the asphalt mixture
Example 3
When the anti-skid performance of the asphalt mixture is evaluated according to the asphalt mixture structure evaluation index, a plurality of indexes can be comprehensively evaluated, and a single index can be selected for evaluation. When a plurality of indexes are evaluated, corresponding weights may be set for the selected plurality of indexes.
Example 4
A system for testing the skid resistance of asphalt mixture based on digital image technique, comprising a processor and a storage medium, wherein the storage medium stores a program, the program is designed according to the method for testing the skid resistance of asphalt mixture based on digital image technique, the program is executed by the processor to execute the following steps:
acquiring a test piece structure evaluation index according to the laser scanning point cloud data;
and selecting a structural evaluation index to evaluate the anti-skid performance.
The system further comprises a laser scanning device, wherein the laser scanning device performs laser scanning on the asphalt mixture to obtain scanning point cloud data, scanning parameters of the laser scanning device can be set, the scanning parameters comprise at least of scanning frequency, scanning mode, scanning point distance and scanning line width, the laser scanning point cloud data can be transmitted to the storage medium, and the system further comprises an asphalt mixture test piece manufacturing device.
It should be noted that the components with the types indicated in the embodiments of the present application are only used for describing the technical solutions of the present application in detail, it should be understood that the technical solutions to be protected by the present invention are not limited by the types, and there are many alternatives that can replace the components in the prior art.
The above examples are only for illustrating the technical solutions of the present invention, and not for limiting the same; although the foregoing embodiments illustrate the invention in detail, those skilled in the art will appreciate that: it is possible to modify the technical solutions described in the foregoing embodiments or to substitute some or all of the technical features thereof, without departing from the scope of the technical solutions of the present invention.
Claims (10)
1, method for testing the skid resistance of asphalt mixture based on digital image technology, which is characterized by comprising the following steps:
preparing an asphalt mixture test piece;
laser scanning the test piece to obtain scanning data;
calculating a test piece structure evaluation index;
the anti-skid property was evaluated according to the structural evaluation index.
2. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 1, wherein: the aggregate of the asphalt mixture test piece is basalt, and the asphalt is SBS modified asphalt with the type of AC, and has 3 groups of gradation.
3. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 1, wherein: the laser scanning the test piece to obtain scanning data comprises the following steps:
setting scanning parameters;
and carrying out laser scanning to obtain scanning point cloud data.
4. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 3, wherein the scanning parameters comprise at least of scanning frequency, scanning mode, scanning point distance and scanning line width.
5. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 3, wherein: the method for acquiring the test piece structure evaluation index comprises the following steps:
establishing a three-dimensional digital model of the test piece;
acquiring three-dimensional coordinate information;
and calculating the structure evaluation index of the test piece according to the three-dimensional coordinate information.
6. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 5, wherein the establishing of the three-dimensional digital model of the test piece comprises at least processes of packaging, exporting and hole filling of the point cloud data.
7. The method for testing the skid resistance of the asphalt mixture based on the digital image technology as claimed in claim 5, wherein: acquiring the three-dimensional coordinate information comprises intercepting a section curve of the three-dimensional digital model and breaking the section curve into points.
8. The method for testing the anti-slip performance of the asphalt mixture based on the digital image technology as claimed in claim 5, wherein the test piece structure evaluation index comprises at least of skewness Rsk and humpness Rku.
9. The method for testing the anti-slip performance of the asphalt mixture based on the digital image technology as claimed in claim 8, wherein the test piece structure evaluation index further comprises at least of an arithmetic mean value Ra, a section standard deviation Rq, a pole difference Rz, an average wavelength La, an average slope Da, a root mean square Lq of a wavelength, a root mean square Dq of a slope and a slope S1.
10, System for testing the skid resistance of asphalt mixture based on digital image technique, comprising a processor and a storage medium, wherein the storage medium stores a program, the program is designed according to the method for testing the skid resistance of asphalt mixture based on digital image technique as claimed in any of claims 1-9- , the program when executed by the processor performs the steps of:
calculating a test piece structure evaluation index according to the laser scanning point cloud data;
optimizing and determining a structural evaluation index to evaluate the anti-skid performance.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910863261.9A CN110738636A (en) | 2019-09-12 | 2019-09-12 | Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910863261.9A CN110738636A (en) | 2019-09-12 | 2019-09-12 | Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110738636A true CN110738636A (en) | 2020-01-31 |
Family
ID=69267908
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910863261.9A Pending CN110738636A (en) | 2019-09-12 | 2019-09-12 | Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110738636A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112927204A (en) * | 2021-02-25 | 2021-06-08 | 同济大学 | Pavement water seepage performance evaluation method based on key water seepage point identification |
| CN113567603A (en) * | 2021-07-22 | 2021-10-29 | 华谱科仪(大连)科技有限公司 | Detection and analysis method of chromatographic spectrogram and electronic equipment |
| CN113686858A (en) * | 2021-08-31 | 2021-11-23 | 山东省交通科学研究院 | Pavement skid resistance evaluation method based on surface texture structure |
| CN114441436A (en) * | 2021-12-20 | 2022-05-06 | 中国公路工程咨询集团有限公司 | Analysis method for evaluating anti-skid performance based on pavement texture |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106442231A (en) * | 2016-08-31 | 2017-02-22 | 北京建筑大学 | Coarse aggregate angularity evaluation method based on digital image analysis technology |
| CN107807082A (en) * | 2017-10-19 | 2018-03-16 | 武汉科技大学 | The assay method in the asphalt section space based on laser scanning |
| CN107883891A (en) * | 2017-12-27 | 2018-04-06 | 长安大学 | A kind of bituminous paving gathers around bag various dimensions characteristic index recognition methods |
-
2019
- 2019-09-12 CN CN201910863261.9A patent/CN110738636A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106442231A (en) * | 2016-08-31 | 2017-02-22 | 北京建筑大学 | Coarse aggregate angularity evaluation method based on digital image analysis technology |
| CN107807082A (en) * | 2017-10-19 | 2018-03-16 | 武汉科技大学 | The assay method in the asphalt section space based on laser scanning |
| CN107883891A (en) * | 2017-12-27 | 2018-04-06 | 长安大学 | A kind of bituminous paving gathers around bag various dimensions characteristic index recognition methods |
Non-Patent Citations (1)
| Title |
|---|
| 陈广辉: "矿料组成对沥青路面宏观纹理及抗滑性能的影响研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112927204A (en) * | 2021-02-25 | 2021-06-08 | 同济大学 | Pavement water seepage performance evaluation method based on key water seepage point identification |
| CN112927204B (en) * | 2021-02-25 | 2022-09-20 | 同济大学 | Pavement water seepage performance evaluation method based on key water seepage point identification |
| CN113567603A (en) * | 2021-07-22 | 2021-10-29 | 华谱科仪(大连)科技有限公司 | Detection and analysis method of chromatographic spectrogram and electronic equipment |
| CN113567603B (en) * | 2021-07-22 | 2022-09-30 | 华谱科仪(大连)科技有限公司 | Detection and analysis method of chromatographic spectrogram and electronic equipment |
| CN113686858A (en) * | 2021-08-31 | 2021-11-23 | 山东省交通科学研究院 | Pavement skid resistance evaluation method based on surface texture structure |
| CN113686858B (en) * | 2021-08-31 | 2023-11-17 | 山东省交通科学研究院 | Pavement anti-skid performance evaluation method based on surface texture structure |
| CN114441436A (en) * | 2021-12-20 | 2022-05-06 | 中国公路工程咨询集团有限公司 | Analysis method for evaluating anti-skid performance based on pavement texture |
| CN114441436B (en) * | 2021-12-20 | 2024-04-16 | 中国公路工程咨询集团有限公司 | Analysis method for evaluating anti-skid performance based on pavement texture |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110738636A (en) | Method and system for testing anti-sliding performance of asphalt mixture based on digital image technology | |
| Mataei et al. | Pavement friction and skid resistance measurement methods: A literature review | |
| Islam et al. | Measurement of pavement roughness using android-based smartphone application | |
| Wang et al. | Design and verification of a laser based device for pavement macrotexture measurement | |
| Serigos et al. | Incorporating surface microtexture in the prediction of skid resistance of flexible pavements | |
| CN108760740B (en) | Quick detection method for road surface skid resistance based on machine vision | |
| Abbondati et al. | Surface monitoring of road pavements using mobile crowdsensing technology | |
| EP3384265B1 (en) | A method and system for measuring deformation of a surface | |
| Čelko et al. | Analysis of the pavement surface texture by 3D scanner | |
| Chou et al. | Using a constructive pavement texture index for skid resistance screening | |
| CN104749095B (en) | Pavement skid resistance condition evaluation method based on tire Yu road surface contact characteristic | |
| KR101206064B1 (en) | Surface roughness measurement system and method that filtering of the vehicle is driving situations | |
| Kargah-Ostadi et al. | Monitoring pavement surface macrotexture and friction: Case study | |
| Huang et al. | Effects of pavement texture on pavement friction: a review | |
| Cebon et al. | A study of road damage due to dynamic wheel loads using a load measuring mat | |
| Aktaş et al. | Comparative analysis of macrotexture measurement tests for pavement preservation treatments | |
| Lukman et al. | The flatness levels of flexible road based on roadroid software in Perintis Kemerdekaan Street Makassar | |
| CN116824546A (en) | Method, device, equipment and medium for determining rugged road surface type | |
| Zhang et al. | Development and verification of integrated photoelectric system for noncontact detection of pavement ponding and freezing | |
| CN109615258A (en) | The evaluation method of automobile brake pedal sense | |
| Sun | On human perception and evaluation to road surfaces | |
| Britton et al. | Estimation of skid numbers from surface texture parameters in the rational design of standard reference pavements for test equipment calibration | |
| Chu et al. | Incorporating braking distance evaluation into pavement management system for safe road operation | |
| Raslavičius et al. | Investigation of asphalt texture roughness on friction evolution for wheeled vehicles | |
| Vallejo* | Fractal assessment of the surface texture of pavements |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200131 |
|
| RJ01 | Rejection of invention patent application after publication |