WO2022156256A1 - 一种沥青材料表面能测试中化学试剂的选取方法及系统 - Google Patents

一种沥青材料表面能测试中化学试剂的选取方法及系统 Download PDF

Info

Publication number
WO2022156256A1
WO2022156256A1 PCT/CN2021/120076 CN2021120076W WO2022156256A1 WO 2022156256 A1 WO2022156256 A1 WO 2022156256A1 CN 2021120076 W CN2021120076 W CN 2021120076W WO 2022156256 A1 WO2022156256 A1 WO 2022156256A1
Authority
WO
WIPO (PCT)
Prior art keywords
asphalt
surface energy
chemical reagent
chemical
reagent combination
Prior art date
Application number
PCT/CN2021/120076
Other languages
English (en)
French (fr)
Inventor
罗蓉
牛茏昌
涂崇志
罗晶
汪翔
苗强
Original Assignee
武汉理工大学
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 武汉理工大学 filed Critical 武汉理工大学
Priority to US17/863,390 priority Critical patent/US20220357308A1/en
Publication of WO2022156256A1 publication Critical patent/WO2022156256A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N13/00—Investigating surface or boundary effects, e.g. wetting power; Investigating diffusion effects; Analysing materials by determining surface, boundary, or diffusion effects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/42—Road-making materials
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N13/00—Investigating surface or boundary effects, e.g. wetting power; Investigating diffusion effects; Analysing materials by determining surface, boundary, or diffusion effects
    • G01N13/02—Investigating surface tension of liquids
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N19/00—Investigating materials by mechanical methods
    • G01N19/04—Measuring adhesive force between materials, e.g. of sealing tape, of coating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/11—Complex mathematical operations for solving equations, e.g. nonlinear equations, general mathematical optimization problems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N13/00—Investigating surface or boundary effects, e.g. wetting power; Investigating diffusion effects; Analysing materials by determining surface, boundary, or diffusion effects
    • G01N13/02—Investigating surface tension of liquids
    • G01N2013/0208—Investigating surface tension of liquids by measuring contact angle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis

Definitions

  • the invention relates to the technical field of asphalt material surface energy testing, in particular to a method and system for selecting chemical reagents in asphalt material surface energy testing.
  • asphalt pavement As one of the main structural forms of highways and urban roads in my country, asphalt pavement is more and more widely used. In the design and construction of asphalt pavement surface layer, an important factor that directly affects the water stability, self-healing ability and fatigue cracking life of asphalt mixture is the adhesion between asphalt and aggregate.
  • the surface free energy method is used to determine its size internationally, and this is used as a quantitative index.
  • the primary task of determining this index is to accurately measure asphalt and aggregate.
  • the surface energy parameters of the aggregates are then solved with the help of the equations provided by the surface energy theory system.
  • the GvOC (Good–van Oss–Chaudhury) surface energy theory system is widely used in the road industry at home and abroad. The system stipulates that asphalt and aggregates each have three basic surface energy parameters, including non-polar components, polar acid weight, polar base weight.
  • the most common test methods for determining the three surface energy parameters are the plug-in method and the static drop method. The same test method is used for the test. Since simultaneous equations are required in the process of solving the asphalt surface energy parameters, at least three different chemical reagents with known surface energy parameters are selected for random combination. There are obvious differences in the surface energy parameters of the same asphalt, and the solution results of some chemical reagent combinations may even have negative values, making it impossible to solve. Therefore, in the face of multiple sets of test data with obvious differences, how to choose the type of chemical reagent combination with high test data stability and how to formulate a reasonable and effective data stability evaluation plan in the surface energy test of asphalt materials is undoubtedly become an important problem that needs to be solved urgently.
  • the invention provides a method for selecting chemical reagents in the surface energy test of asphalt materials, comprising the following steps:
  • the obtaining of the contact angle value formed by the chemical reagent and the asphalt glass slide specifically includes:
  • the asphalt surface energy parameter corresponding to the chemical reagent combination which specifically includes:
  • the asphalt surface energy parameters corresponding to the chemical reagent combination specifically including:
  • the asphalt surface energy parameter corresponding to the chemical reagent combination is determined, and the minimum value of the fitting error is determined.
  • two chemical reagent combinations whose surface energy parameters of asphalt are not zero at the same time are selected, and the coefficient of variation of the surface energy parameters of different kinds of asphalt for each chemical reagent combination is calculated separately.
  • the coefficient of variation of the energy parameters is selected, and the range of chemical reagent combinations is selected.
  • obtaining the number of abnormal values of the asphalt surface energy component in the range of the chemical reagent combination specifically includes:
  • determining the final chemical reagent combination according to the number of the abnormal values specifically including: taking the chemical reagent combination with the smallest number of abnormal values of the asphalt surface energy component in the chemical reagent combination range as the final chemical reagent combination.
  • the chemical reagent combination includes 3 kinds of chemical reagents or 4 kinds of chemical reagents.
  • the invention also provides a system for selecting chemical reagents in the surface energy test of asphalt materials, including a contact angle acquisition module, an asphalt surface energy parameter acquisition module, a chemical reagent combination range acquisition module, and a chemical reagent combination determination module;
  • the contact angle obtaining module is used to select several different chemical reagents to obtain the contact angle value formed by the chemical reagent and the asphalt glass slide;
  • the asphalt surface energy parameter acquisition module is used for acquiring the asphalt surface energy parameter corresponding to the combination of chemical reagents according to the contact angle value formed by the chemical reagent and the asphalt glass slide;
  • the chemical reagent combination range obtaining module is used to obtain the variation coefficient of the asphalt surface energy parameter corresponding to the chemical reagent combination, and select the chemical reagent combination range according to the variation coefficient;
  • the chemical reagent combination determination module is configured to acquire the number of abnormal values of the asphalt surface energy component in the chemical reagent combination range, and determine the final chemical reagent combination according to the number of abnormal values.
  • the beneficial effects of the present invention include: obtaining the contact angle value formed by the chemical reagent and the asphalt glass slide by selecting several different chemical reagents; obtaining the contact angle value formed by the chemical reagent and the asphalt glass slide
  • the asphalt surface energy parameter corresponding to the chemical reagent combination; the variation coefficient of the asphalt surface energy parameter corresponding to the chemical reagent combination is obtained, and the range of the chemical reagent combination is selected according to the variation coefficient; the abnormal value of the asphalt surface energy component in the chemical reagent combination range is obtained
  • the number of outliers is determined, and the final chemical reagent combination is determined according to the number of abnormal values; the type of chemical reagent combination with higher test data stability can be selected.
  • Fig. 1 is the schematic flow sheet of the selection method of chemical reagent in the asphalt material surface energy test provided by the present invention
  • Fig. 2 is the optical contact angle meter provided by the present invention
  • FIG. 3 is a schematic diagram of the static drop method for measuring the contact angle provided by the present invention.
  • Fig. 4 is the automatic surface tensiometer provided by the present invention.
  • Fig. 5 is the Excel calculation table schematic diagram provided by the present invention.
  • Fig. 6 is the Excel programming solver operation interface provided by the present invention.
  • FIG. 7 is a structural block diagram of a system for selecting chemical reagents in the asphalt material surface energy test provided by the present invention.
  • the embodiment of the present invention provides a method for selecting chemical reagents in the surface energy test of asphalt materials, and a schematic flowchart of the method, as shown in FIG. 1 , includes the following steps:
  • the asphalt surface energy parameters include the non-polar component of the surface energy of the asphalt, the polar alkali component of the surface energy of the asphalt, the polar acid component of the surface energy of the asphalt, the polar component of the surface energy of the asphalt, and the surface energy of the asphalt. total energy.
  • the asphalt surface energy parameter corresponding to the chemical reagent combination which specifically includes:
  • Excel software is used to make an asphalt surface energy parameter calculation table, and the contact angle data obtained from the test and the respective surface energy parameter values of the chemical reagents that meet the conditions are substituted into the asphalt surface energy parameter calculation formula and the parallel equations are solved; Obtain the non-polar component of the surface energy of the asphalt Polar base content and polar acid content After that, by formula Calculate the surface energy polar component of asphalt and the total surface energy ⁇ S .
  • the non-polar component, polar alkali component and polar acid component of the surface energy of the chemical reagent are known, and the contact angle can be obtained by the static drop method and the plug-in method. According to the contact angle calculation formula, at least 3 A set of equations can be used to obtain the asphalt surface energy parameters. At the same time, due to the existence of the radical sign, one asphalt surface energy parameter has multiple values.
  • the asphalt surface energy parameters corresponding to the chemical reagent combination specifically including:
  • the asphalt surface energy parameter corresponding to the chemical reagent combination is determined, and the minimum value of the fitting error is determined.
  • the overall least squares method is used to control the fitting error to the minimum, so as to determine the optimal asphalt surface energy parameter, and the fitting error of each equation in the set of equations for the calculation formula of the asphalt surface energy parameter and the parallel equation is set as the target.
  • the overall least squares method can make the fitting error reach the minimum value Min, that is, the shortest straight-line distance from the fitting point to any plane in the space rectangular coordinate system .
  • the three asphalt surface energy parameters to be solved are set as variable cells, and the average value of the sum of the three Min values is set as the target value, which can be calculated by using the Solver function in the Excel table. result.
  • the obtaining of the contact angle value formed by the chemical reagent and the asphalt glass slide specifically includes:
  • the coefficient of variation of the contact angle value formed by each chemical reagent and the asphalt glass slide is calculated respectively, and the test method with the smallest degree of data dispersion is selected.
  • Asphalt is not a unipolar substance, that is, all three asphalt surface energy parameters should be greater than zero, and the total surface energy of asphalt calculated under each combination of reagents should not be greater than the total surface energy of any chemical reagent in the combination. Types of chemical reagent combinations for which there is clearly unreasonable data.
  • variation coefficient of the asphalt surface energy parameter corresponding to the chemical reagent combination and select the chemical reagent combination range according to the variation coefficient, which specifically includes:
  • the coefficient of variation of the data obtained by the programming solution for each chemical reagent combination is calculated separately.
  • the coefficient of variation value is the average value of the coefficient of variation calculated by a variety of asphalt materials;
  • the calculation formula for evaluating the data stability with the coefficient of variation CV is: Among them, CV is the coefficient of variation, ⁇ is the standard deviation of the original data, ⁇ is the average value of the original data, xi is any observation value in the original data, and n is the number of data.
  • the coefficient of variation of the data obtained by each chemical reagent combination planning solution is compared, and five kinds of surface energy parameters are selected.
  • the first three types of chemical reagent combinations with smaller coefficients of variation correspond to each other.
  • outliers that is, abnormal data
  • outliers are also called outliers, that is, part of the data that is obviously inconsistent with the rest of the data in a set of statistical data, and can be identified by the test method of jump degree;
  • X (1) , X (2) , ⁇ , X (n-1) , X (n) be the order statistics of sample size n from the population distribution F(x;
  • the point estimate of the expected ⁇ of X (1) , ⁇ ,X (k) is called is the jump degree of ⁇ at point k (referred to as the jump degree at point k), then the calculation formula of the jump degree is:
  • ⁇ k and ⁇ k+1 are expected point estimates
  • k is the sequence of any order statistics
  • k 1, 2, 3,...,n
  • D k is the jump degree at point k .
  • Determine the final chemical reagent combination according to the number of the abnormal values which specifically includes: taking the chemical reagent combination with the smallest number of abnormal values of the asphalt surface energy component in the chemical reagent combination range as the final chemical reagent combination.
  • the chemical reagent combination includes 3 chemical reagents or 4 chemical reagents.
  • outliers there are three types of outliers in a set of data: only abnormally large values, only abnormally small values, or both abnormally small values and abnormally large values. For each case, the following steps can be used to test outliers: (1) Arrange all the data in ascending order, and calculate the size of the jump at each point; (2) Find the jump from both ends of the data (3) If there is a significant difference between the maximum jump degree and the adjacent jump degrees, the statistical data corresponding to the left is the largest abnormally small value, and the statistical data corresponding to the right is the smallest abnormally large value. value.
  • the number of outliers in the asphalt surface energy parameters obtained through the range of chemical reagent combinations can be used to screen out the combination types with relatively good data stability and relatively few outliers.
  • the reagent type is the final chemical reagent combination
  • the asphalt surface energy parameter calculated under this combination type is the final obtained asphalt surface energy parameter.
  • the embodiment of the present invention provides a method for selecting chemical reagents in the surface energy test of asphalt materials, which includes: selecting two methods for testing the surface energy of asphalt materials, the static drop method and the plug-in method, and selecting at least three known surface energy parameters.
  • Chemical reagents are used as test reagents to measure the contact angles formed by asphalt slide samples and different reagents respectively, so as to obtain the original test data; after substituting the contact angle data and the surface energy parameters of different kinds of chemical reagents into the well-made Excel table, the simultaneous equation
  • the overall least squares method is used to solve the contact angle calculation formula; when selecting the chemical reagent combination, the coefficient of variation is used to evaluate the stability of the test data, and the outliers in the data are excluded by means of the jump degree test method. Analysis interference; after multiple comparisons and screening, the chemical reagent combination type with relatively good data stability and relatively few outliers was finally selected.
  • a total of 8 chemical reagents including distilled water, formamide, ethylene glycol, glycerol, dimethyl sulfoxide, diiodomethane, benzyl alcohol and n-octanol are selected as test reagents, and the basic selection principles are as follows. 3 points: 1.
  • the chemical reagent is a single homogeneous pure liquid reagent, and does not dissolve or chemically react with the asphalt material; 2.
  • the surface energy parameter of the chemical reagent is a known quantity, in order to substitute it into the contact angle calculation formula.
  • the unknown quantities in the equation system are only three surface energy components of asphalt; 3.
  • the chemical reagent can form a stable contact angle with the asphalt glass slide, that is, the total surface energy of the chemical reagent is greater than that of the asphalt material.
  • Total energy the English letter abbreviations of 8 chemical reagents and their respective surface energy parameters are listed in Table 1; the surface energy parameters of different chemical reagents are shown in Table 1;
  • the asphalt-coated glass slides were prepared, and the asphalt glass slides with smooth, smooth surface and no impurities were selected for curing for 24 hours, and then the static drip method and the plug-in method were used for several times respectively.
  • the contact angle was measured by the parallel test; the static drop test was performed using an optical contact angle meter (DSA100); the optical contact angle meter was shown in Figure 2; the basic steps of the static drop test were as follows:
  • the baseline position is determined by a dynamic method, that is, the moment the platform rises to the moment when the surface of the asphalt glass slide contacts the reagent droplet, the droplet will A complete projection mirror image is formed on the surface of the glass slide, and the contact line of the two droplet images is the exact position of the baseline;
  • the plug-in method test is tested with an automatic surface tensiometer (K100); the automatic surface tensiometer is shown in Figure 4; the basic steps of the plug-in method test are as follows:
  • the controllable human error and system error are summarized as follows:
  • the droplet titration system is set to a fixed value for each drop of liquid volume. Then, perform the droplet contour fitting as quickly as possible and record the contact angle values before the contour is deformed by gravity, and record the left and right contact angles and their average values respectively;
  • the insert plate method set the test temperature of the constant temperature water bath system. The temperature is 20°C. In each test, only the part between 2mm and 10mm of the pitch glass slide is measured from the time it is immersed in the reagent liquid level.
  • the asphalt is prepared from the same batch and origin, and has the same curing time in the drying oven.
  • the schematic diagram of the Excel calculation table is shown in Figure 5.
  • the table is divided into upper and lower parts.
  • a column that can be marked with Probe Liquid is the English abbreviation of the chemical reagent; a i1 , a i2 , a i3 are sequentially and b i is Min is the fitting error, Target is the average of the sum of the three fitting errors, and x1, x2, and x3 are in turn and SFE is the calculated value of each surface energy parameter of asphalt. Enter the surface energy parameters of different chemical reagents and the corresponding contact angle values in the contact angle calculation formula, and solve the equations simultaneously to obtain the asphalt surface energy parameters.
  • WFE means the reagent combination of "distilled water + formamide + ethylene glycol”
  • WFEG means "distilled water + formamide + ethylene glycol”
  • alcohol + glycerol means "distilled water + formamide + ethylene glycol”
  • the coefficient of variation is used to first evaluate the data stability between the test methods, complete the first screening of chemical reagent combinations, and then evaluate the data stability between chemical reagent combinations, and complete the second screening.
  • the coefficient of variation of the contact angle values formed by each chemical reagent and the asphalt glass slide was calculated respectively, and the test method with the smallest degree of data dispersion was selected.
  • the coefficient of variation values of each group of data are listed in Table 8 and Table 9.
  • Table 8 and Table 9 correspond to the coefficient of variation of the contact angle values obtained by the intravenous drip method and the insert plate method, respectively.
  • the coefficient of variation of the contact angle data measured by the static drop method is greater than that of the plug-in method, that is, the degree of dispersion of the contact angle data measured by the static-drop method is greater than that of the plug-in method.
  • the three cases include 70# base asphalt+W, SBS modified asphalt+F, SBS modified asphalt+B.
  • WFSD ⁇ WGDB ⁇ WFBN WFDN ⁇ WGSD ⁇ WFDB ⁇ WFGD ⁇ WFGB ⁇ WSD ⁇ GSD.
  • the test method of jumping degree is used to analyze the twelve reagent combinations selected by the coefficient of variation, and judge the number of abnormal values in the data obtained by each reagent combination, as shown in Table 11.
  • An embodiment of the present invention provides a system for selecting chemical reagents in the surface energy test of asphalt materials. Its structural block diagram is shown in FIG. 7 .
  • the system includes a contact angle acquisition module 1 , an asphalt surface energy parameter acquisition module 2 , and chemical reagents. Combination range acquisition module 3 and chemical reagent combination determination module 4;
  • the contact angle obtaining module 1 is used for selecting several different chemical reagents to obtain the contact angle value formed by the chemical reagent and the asphalt glass slide;
  • the asphalt surface energy parameter acquisition module 2 is configured to acquire the asphalt surface energy parameter corresponding to the combination of chemical reagents according to the contact angle value formed by the chemical reagent and the asphalt glass slide;
  • the chemical reagent combination range obtaining module 3 is used to obtain the variation coefficient of the asphalt surface energy parameter corresponding to the chemical reagent combination, and select the chemical reagent combination range according to the variation coefficient;
  • the chemical reagent combination determination module 4 is configured to acquire the number of abnormal values of the asphalt surface energy component in the chemical reagent combination range, and determine the final chemical reagent combination according to the number of abnormal values.
  • the invention discloses a method and system for selecting chemical reagents in the surface energy test of asphalt materials.
  • the contact angle values formed by the chemical reagents and the asphalt glass sheets are obtained;
  • the number of abnormal values of the asphalt surface energy component, and according to the number of the abnormal values, the final chemical reagent combination is determined; the type of chemical reagent combination with higher test data stability can be selected.
  • the technical solution of the present invention uses the overall least squares method to solve the equation system, which can reduce the error between the calculated value and the actual value of each surface energy parameter of asphalt, and is more consistent with the equation system composed of three basic unknown equations in three-dimensional space. Therefore, the three asphalt surface energy parameters obtained by solving the equation system are more reasonable and closer to the actual value, thus providing a more accurate data basis for data stability evaluation.
  • a new analysis method is introduced to evaluate the data stability in the surface energy test of asphalt materials, that is, the coefficient of variation, a numerical feature commonly used in statistics, is used to analyze each set of data.
  • the magnitude of the glass movement is determined, and the interference of the abnormal values in each group of data on the stability analysis is eliminated by the test method of the jump degree.
  • the purpose is to screen the data with large differences, so as to provide the basis for the experimental design of accurate calculation of surface energy parameters.
  • the technical solution of the present invention selects a chemical reagent combination with relatively high test data stability, provides a reasonable and effective method basis for selecting chemical reagents for testers engaged in testing asphalt surface energy parameters, and can be better applied to the direction of pavement asphalt performance test.

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Mathematical Physics (AREA)
  • Pure & Applied Mathematics (AREA)
  • Data Mining & Analysis (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Theoretical Computer Science (AREA)
  • Computational Mathematics (AREA)
  • Medicinal Chemistry (AREA)
  • Food Science & Technology (AREA)
  • Algebra (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Operations Research (AREA)
  • Investigating Or Analyzing Non-Biological Materials By The Use Of Chemical Means (AREA)
  • Testing Resistance To Weather, Investigating Materials By Mechanical Methods (AREA)

Abstract

一种沥青材料表面能测试中化学试剂的选取方法及系统，所述方法包括以下步骤：选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值（S1）；根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数（S2）；获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围（S3）；获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合（S4）。该沥青材料表面能测试中化学试剂的选取方法，可以选择出试验数据稳定性较高的化学试剂组合类型。

Description

一种沥青材料表面能测试中化学试剂的选取方法及系统 技术领域
本发明涉及沥青材料表面能测试技术领域，尤其涉及一种沥青材料表面能测试中化学试剂的选取方法及系统。
背景技术
作为我国公路与城市道路的主要结构形式之一，沥青路面的应用越来越广泛。在沥青路面面层的设计和施工过程当中，直接影响到沥青混合料的水稳定性、自愈合能力以及疲劳开裂寿命等路用性能的一个重要因素是沥青与集料之间的黏附性能。
为了借助详细准确的试验数值评价沥青与集料之间的黏附性能，国际上采用表面自由能方法来确定其大小，并以此作为量化指标，而确定该指标的首要任务是准确地测定沥青和集料的表面能参数，进而借助表面能理论体系提供的方程求解。现今国内外道路行业普遍采用的是GvOC(Good–van Oss–Chaudhury)表面能理论体系，该体系规定，沥青和集料各自有三个基本的表面能参数，分别包括非极性分量、极性酸分量、极性碱分量。
针对沥青材料而言，测定其三个表面能参数的试验方法最常见的有插板法和静滴法两种，在既有的表面自由能理论体系以及试验条件下，选取不同的化学试剂并使用同一试验方法进行试验，由于在求解沥青表面能参数的过程中需要联立方程组，所以至少选取三种不同的已知表面能参数的化学试剂进行随机组合，然而不同化学试剂组合测得的同种沥青表面能参数存在明显差异，某些化学试剂组合的求解结果甚至会出现负值，导致无法求解。因此，面对求解得出的多组差异性明显的试验数 据，如何选择试验数据稳定性较高的化学试剂组合类型以及如何在沥青材料表面能测试中制定合理有效的数据稳定性评价方案，无疑成为目前亟待解决的重要问题。
发明内容
有鉴于此，有必要提供一种沥青材料表面能测试中化学试剂的选取方法及系统，用以解决现有技术中无法选择出试验数据稳定性较高的化学试剂组合的问题。
本发明提供了一种沥青材料表面能测试中化学试剂的选取方法，包括以下步骤：
选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；
根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合。
进一步地，所述获取化学试剂与沥青玻片形成的接触角数值，具体包括：
计算化学试剂在不同试验方法条件下，与沥青玻片形成的接触角数值的变异系数大小，获取数据离散程度最小的试验方法，并以该实验方法获取不同化学试剂与沥青玻片形成的接触角数值；
进一步地，根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数，具体包括：
根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数的多个值，根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数。
进一步地，根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数的多个值，具体包括：
根据所述化学试剂与沥青玻片形成的接触角数值及沥青表面能参数计算公式，获取化学试剂组合对应的沥青表面能参数的多个值；所述沥青表面能参数计算公式为
Figure PCTCN2021120076-appb-000001
其中，
Figure PCTCN2021120076-appb-000002
为沥青的表面能非极性分量，
Figure PCTCN2021120076-appb-000003
为化学试剂的表面能非极性分量，
Figure PCTCN2021120076-appb-000004
为沥青的表面能极性碱分量，
Figure PCTCN2021120076-appb-000005
为沥青的表面能极性酸分量，
Figure PCTCN2021120076-appb-000006
为化学试剂的表面能极性碱分量，
Figure PCTCN2021120076-appb-000007
为化学试剂的表面能极性酸分量，γ L为化学试剂的表面能总量，θ为接触角。
进一步地，根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，具体包括：
根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，所述拟合误差最小值
Figure PCTCN2021120076-appb-000008
进一步地，获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围，具体包括：
在所述若干不同化学试剂中，选取两种沥青的表面能参数同时不为 零的化学试剂组合，分别计算每一种化学试剂组合的不同种类沥青表面能参数的变异系数，根据不同种类沥青表面能参数的变异系数，选取化学试剂组合范围。
进一步地，获取所述化学试剂组合范围中沥青表面能分量异常值的个数，具体包括：
根据两种沥青的表面能参数同时不为零的化学试剂组合的沥青表面能分量跳跃度，确定所述化学试剂组合范围中各个化学试剂组合沥青表面能分量的异常值个数。
进一步地，根据所述异常值的个数，确定最终的化学试剂组合，具体包括：以化学试剂组合范围中沥青表面能分量的异常值个数最少的化学试剂组合，作为最终的化学试剂组合。
进一步地，所述化学试剂组合包括3种化学试剂或者4种化学试剂。
本发明还提供了一种沥青材料表面能测试中化学试剂的选取系统，包括接触角获取模块、沥青表面能参数获取模块、化学试剂组合范围获取模块及化学试剂组合确定模块；
所述接触角获取模块，用于选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；
所述沥青表面能参数获取模块，用于根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
所述化学试剂组合范围获取模块，用于获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
所述化学试剂组合确定模块，用于获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合。
与现有技术相比，本发明的有益效果包括：通过选取若干不同化学 试剂，获取化学试剂与沥青玻片形成的接触角数值；根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合；可以选择出试验数据稳定性较高的化学试剂组合类型。
附图说明
图1为本发明提供的沥青材料表面能测试中化学试剂的选取方法的流程示意图；
图2为本发明提供的光学接触角仪；
图3为本发明提供的静滴法测定接触角的示意图；
图4为本发明提供的全自动表面张力仪；
图5为本发明提供的Excel计算表格示意图；
图6为本发明提供的Excel规划求解操作界面；
图7为本发明提供的沥青材料表面能测试中化学试剂的选取系统的结构框图。
具体实施方式
下面结合附图来具体描述本发明的优选实施例，其中，附图构成本申请一部分，并与本发明的实施例一起用于阐释本发明的原理，并非用于限定本发明的范围。
实施例1
本发明实施例提供了一种沥青材料表面能测试中化学试剂的选取方法，其流程示意图，如图1所示，所述方法包括以下步骤：
S1、选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触 角数值；
S2、根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
S3、获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
S4、获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合。
一个具体实施例中，所述沥青表面能参数包括沥青的表面能非极性分量、沥青的表面能极性碱分量、沥青的表面能极性酸分量、沥青的表面能极性分量及沥青表面能总量。
根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数，具体包括：
根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数的多个值，根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数。
根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数的多个值，具体包括：
根据所述化学试剂与沥青玻片形成的接触角数值及沥青表面能参数计算公式，获取化学试剂组合对应的沥青表面能参数的多个值；所述沥青表面能参数计算公式为
Figure PCTCN2021120076-appb-000009
其中，
Figure PCTCN2021120076-appb-000010
为沥青的表面能非极性分量，
Figure PCTCN2021120076-appb-000011
为化学试剂的表面能非极性分量，
Figure PCTCN2021120076-appb-000012
为沥青的表面能极性碱分量，
Figure PCTCN2021120076-appb-000013
为沥青的表面能极性酸分 量，
Figure PCTCN2021120076-appb-000014
为化学试剂的表面能极性碱分量，
Figure PCTCN2021120076-appb-000015
为化学试剂的表面能极性酸分量，γ L为化学试剂的表面能总量，θ为接触角。
一个具体实施例中，利用Excel软件制作沥青表面能参数计算表格，将试验所得接触角数据以及满足条件的化学试剂的各个表面能参数数值代入所述沥青表面能参数计算公式并联立方程组求解；得到沥青的表面能非极性分量
Figure PCTCN2021120076-appb-000016
极性碱分量
Figure PCTCN2021120076-appb-000017
和极性酸分量
Figure PCTCN2021120076-appb-000018
后，通过公式
Figure PCTCN2021120076-appb-000019
计算沥青的表面能极性分量
Figure PCTCN2021120076-appb-000020
和表面能总量γ S。
需要说明的是，化学试剂的表面能非极性分量、极性碱分量以及极性酸分量为已知，接触角可以通过静滴法与插板法获取，根据接触角计算公式至少联立3个方程组，即可获取沥青表面能参数，同时，由于根号的存在，使得一个沥青表面能参数具有多个值。
根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，具体包括：
根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，所述拟合误差最小值
Figure PCTCN2021120076-appb-000021
一个具体实施中，通过运用总体最小二乘法控制拟合误差达到最小，以确定最佳的沥青表面能参数，将沥青表面能参数计算公式并联立的方程组中各个方程的拟合误差设为目标值，根据沥青表面能参数计算公式和总体最小二乘法的几何含义，运用总体最小二乘法能够使拟合误差达到最小值Min，即空间直角坐标系中拟合点到任一平面的最短直线距离。
具体实施时，将需要求解的三个沥青表面能参数设定为可变单元格，将三个Min值之和的平均值设定为目标值，使用Excel表格中规划求解功能即可计算得出结果。
所述获取化学试剂与沥青玻片形成的接触角数值，具体包括：
计算化学试剂在不同试验方法条件下，与沥青玻片形成的接触角数值的变异系数大小，获取数据离散程度最小的试验方法，并以该实验方法获取不同化学试剂与沥青玻片形成的接触角数值。
一个具体实施例中，需要在满足条件的化学试剂中随机选取3种或4种进行试验并将其表面能参数代入沥青表面能参数计算公式规划求解，在评价不同试验方法之间接触角数据的稳定性时，每3种或4种化学试剂构成一种试剂组合类型，不同试剂组合计算得出的沥青表面能参数数据之间需要进一步评价其稳定性。
另一个具体实施例中，按照试验方法的不同，分别计算每种化学试剂与沥青玻片形成的接触角数值的变异系数大小，选出数据离散程度最小的试验方法，在不同试验方法下，根据沥青并非单极性物质即三个沥青表面能参数均应大于零，并且每种试剂组合下计算得出的沥青表面能总量不得大于该组合中任何一种化学试剂的表面能总量，排除存在明显不合理数据的化学试剂组合类型。
获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围，具体包括：
在所述若干不同化学试剂中，选取两种化学试剂的沥青表面能参数同时不为零的化学试剂组合，分别计算每一种化学试剂组合的不同种类沥青表面能参数的变异系数，根据不同种类沥青表面能参数的变异系数，选取化学试剂组合范围。
一个具体实施例中，按照不同种类的沥青表面能参数，分别计算每 一化学试剂组合规划求解所得数据的变异系数大小。其中，为控制试验变量，对于某一特定的沥青表面能参数，变异系数值取多种沥青材料计算所得变异系数的平均值；借助变异系数C.V.评价数据稳定性的计算公式为
Figure PCTCN2021120076-appb-000022
其中，C.V.为变异系数，σ为原始数据的标准差，μ为原始数据的平均值，x i为原始数据中任一观测值，n为数据个数。
另一个具体实施例中，对于不同种类的沥青表面能参数，比较每种化学试剂组合规划求解所得数据的变异系数大小，并选取出五种表面能参数
Figure PCTCN2021120076-appb-000023
分别对应的变异系数较小的前三种化学试剂组合类型。
获取所述化学试剂组合范围中沥青表面能分量异常值的个数，具体包括：
根据两种沥青(70#基质沥青和SBS改性)的表面能参数同时不为零的化学试剂组合的沥青表面能分量跳跃度，确定所述化学试剂组合范围中各个化学试剂组合沥青表面能分量的异常值个数。
一个具体实施例中，异常值即异常数据也称之为离群值，即在一组统计数据当中与其余数据相比明显不一致的部分数据，可以通过跳跃度这一检验方法将其判别；
设X (1),X (2),Λ,X (n-1),X (n)为来自总体分布F(x；θ)的样本容量为n的次序统计量，μ k为仅依赖于X (1),Λ,X (k)的期望μ的点估计值，则称
Figure PCTCN2021120076-appb-000024
为μ在点k的跳跃度(简称k点处的跳跃度)，则跳跃度的计算公式为
Figure PCTCN2021120076-appb-000025
Figure PCTCN2021120076-appb-000026
Figure PCTCN2021120076-appb-000027
其中，μ k和μ k+1均为期望的点估计值，k为任一次序统计量的序列，k＝1,2,3,...,n，D k为k点处的跳跃度。
根据所述异常值的个数，确定最终的化学试剂组合，具体包括：以化学试剂组合范围中沥青表面能分量的异常值个数最少的化学试剂组合，作为最终的化学试剂组合。
所述化学试剂组合包括3种化学试剂或者4种化学试剂。
需要说明的是，任何一组由n个数据组成的样本，将所有数据由小到大排序之后，如有异常值，则其必居于该组数据所组成的数列两端，并且异常值的存在必定会使得期望的点估计产生间断性的跳跃，因此如果异常值不止一个时，期望点估计的最大跳跃点即跳跃度最大的点最有可能是异常数据的起始点。
一组数据存在异常值的情况可以分为以下三种：仅存在异常大值、仅存在异常小值或者既存在异常小值又存在异常大值。对于每种情况均可以用以下步骤进行异常值检验：(1)将全部数据按照由小到大的顺序排列，并计算各点处的跳跃度大小；(2)从数据两端开始找出跳跃度的最大值点；(3)若跳跃度的最大值与相邻跳跃度存在明显差异，则以左侧对应的统计数据为最大的异常小值，右侧对应的统计数据为最小的异常大值。
借助跳跃度分析通过化学试剂组合范围所得沥青表面能参数中异常值的个数，从而筛选出数据稳定性相对较优且异常值相对最少的组合类型，经过三次筛选后的化学试剂组合所包含的试剂种类即为最终的化学 试剂组合，该组合类型下计算得出的沥青表面能参数即为最终获取的沥青表面能参数。
实施例2
本发明实施例提供了一种沥青材料表面能测试中化学试剂的选取方法，其包括：选用静滴法和插板法两种沥青材料表面能测试方法，选取至少三种已知表面能参数的化学试剂作为测试试剂，分别测定沥青玻片样本与不同试剂形成的接触角，从而得到原始试验数据；将接触角数据以及不同种类化学试剂的表面能参数代入制作完善的Excel表格之后，联立方程组计算沥青表面能参数时，运用总体最小二乘法规划求解接触角计算公式；选取化学试剂组合时，运用变异系数评估试验数据的稳定性，并借助跳跃度检验方法排除数据中异常值对稳定性分析的干扰；经过多次对比筛选，最终选取出数据稳定性相对较优且异常值相对最少的化学试剂组合类型。
一个具体实施例中，选取蒸馏水、甲酰胺、乙二醇、丙三醇、二甲基亚砜、二碘甲烷、苯甲醇和正辛醇共8种化学试剂作为测试试剂，其基本的选取原则有3点：一、化学试剂为单一均质的纯液体试剂，且不与沥青材料相溶或发生化学反应；二、化学试剂的表面能参数为已知量，为了代入接触角计算公式中联立方程组并求解，而方程组中的未知量仅为沥青的三个表面能分量；三、化学试剂能够与沥青玻片形成稳定的接触角，即化学试剂的表面能总量大于沥青材料的表面能总量，将8种化学试剂的英文字母简称及其各个表面能参数分别列于表1中；化学试剂不同化学试剂的表面能参数，如表1所示；
表1
Figure PCTCN2021120076-appb-000028
以70#基质沥青与SBS改性沥青为例，制备沥青涂膜玻片并选取表面光滑平整无杂质的沥青玻片养生达到二十四小时后，分别借助静滴法和插板法进行多次平行试验测定接触角；采用光学接触角仪(DSA100)进行静滴法试验；光学接触角仪，如图2所示；静滴法试验基本步骤如下：
S11、注入测试试剂，按顺序打开各仪器待正常运转之后，打开静滴法系统软件，分别将不同测试试剂注满滴定系统；
S12、水平放置沥青玻片，将制备好的沥青玻片水平放置于试验腔体中，在腔体一侧有可视玻璃窗，光学接触角仪自带的高清摄像头可以通过可视窗随时观测试剂液滴形状以获取其外轮廓；
S13、释放液滴至沥青玻片表面，选择所需化学试剂种类，将液滴滴定系统的针头旋转调下对准腔体内的沥青玻片，然后操作软件上下移动针头使距离适中，释放速率一般设定为V＝1μL/min，液体滴落的体积设定为v＝0.5μL；
S14、确定基线位置，试剂液滴与沥青玻片接触瞬间形成的分界线称 为基线，一般使用动态方式确定基线位置，即上升平台至沥青玻片表面与试剂液滴接触的瞬间，液滴会在玻片表面上形成一个完整的投影镜像，这两个液滴影像的接触线就是基线的准确位置；
S15、测定接触角，使用软件的自动轮廓捕捉功能，勾勒出液滴的外形轮廓，同时及时在短时间内采用椭圆拟合法测定形成的稳定接触角，静滴法测定接触角的示意图，如图3所示。
插板法试验则采用全自动表面张力仪(K100)进行测试；全自动表面张力仪，如图4所示；插板法试验基本步骤如下：
S21、测试前的准备工作，试验前两小时左右打开JULABO恒温浴系统并设定试验温度，将仪器腔体内的温度探头插入化学试剂液面以下；
S22、测量沥青玻片尺寸，从干燥箱中取出养生好的沥青玻片，使用游标卡尺测量其宽度及厚度，对于每片沥青玻片，平行测试3次并取结果的平均值；
S23、水平固定沥青玻片，将沥青玻片固定在仪器腔体内的样品夹具上，不断校核调整令玻片下端呈水平状态，且化学试剂液面与沥青玻片底端较为接近，但避免使玻片直接浸入化学试剂中；
S24、测定接触角，运行K100软件，选择化学试剂种类，测试深度设定为2mm到10mm，测试速率默认为3mm/min，点击开始测试后，软件将自动记录并拟合得到接触角数值。
同时，为了控制试验变量，对可控的人为误差和系统误差统一归纳如下：对于静滴法，液滴滴定系统每次滴落液体体积设定为固定值，在液滴滴落到沥青玻片上之后尽可能迅速地进行液滴轮廓拟合并记录轮廓尚未受重力影响变形的接触角数值，分别记录左右两个接触角及其平均值；对于插板法，将恒温水浴系统的试验温度设定为20℃，每次试验仅测量沥青玻片从浸入试剂液面开始算起的2mm到10mm之间的部分，沥 青玻片底端尽可能与试剂液面保持平行；每种沥青玻片均采用同一批次以及产地的沥青制备的，而且在干燥箱中养生的时间相同，对于同一种试验方法、同一种沥青玻片和同一种化学试剂，均进行三次平行试验测量，而且最终的接触角数值取三次测量结果的平均值；由此测得的接触角数值记载于表2和表3中，静滴法及插板法测试得到的接触角数值，分别如表2、3所示；
表2
Figure PCTCN2021120076-appb-000029
表3
Figure PCTCN2021120076-appb-000030
对于插板法试验测定接触角，由于沥青玻片在退出测试试剂的过程中，沥青涂膜表面已经附着上一层试剂液体薄膜而受到液体自重和表面 张力的影响，导致后退角与前进角之间的差值明显，因此在表中只记录了前进角的数值大小。
Excel计算表格示意图，如图5所示，根据随机选取的化学试剂种类的不同，表格分为上下两部分，上部分为从八种化学试剂中随机选取三种分别代入方程联立求解，共有
Figure PCTCN2021120076-appb-000031
种试剂组合类型；而下部分则选取四种，共有
Figure PCTCN2021120076-appb-000032
种试剂组合类型；两部分均以能够形成稳定接触角计算公式情况下的作为计算公式；
一个具体实施例中，可标明Probe Liquid的一列为化学试剂的英文简称；a i1、a i2、a i3依次为
Figure PCTCN2021120076-appb-000033
和
Figure PCTCN2021120076-appb-000034
b i为
Figure PCTCN2021120076-appb-000035
Min为拟合误差，Target为三个拟合误差之和的平均值，x1、x2、x3依次为
Figure PCTCN2021120076-appb-000036
和
Figure PCTCN2021120076-appb-000037
SFE为沥青各个表面能参数的计算值。在接触角计算公式中分别输入不同化学试剂的表面能参数以及对应的接触角数值，联立方程组并线性规划求解，可获取沥青表面能参数。
另一个具体实施例中，使用Excel软件中的规划求解功能计算沥青表面能参数并进行数据的整理与记录，其基本步骤如下：将需要求解的三个沥青表面能参数x1、x2、x3设定为可变单元格，将三个Min值之和的平均值设定为目标值；每次规划求解之前只需更改测试试剂种类、测试试剂的三个表面能参数和接触角数值即可。
点击Excel表格中工具栏右上角的“文件”菜单，继续点击“选项”-“加载项”-“转到”，弹出“可用加载宏”窗口之后，勾选“规划求解加载项”，此时工具栏的“数据”页面下便会出现“规划求解”选项；打开规划求解参数页面填写“设置目标”和“通过更改可变单元格”，勾选“使无约束变量为非负数”，求解方法为“非线性GRG”，然后即可进行求解；Excel规划求解操作界面，如图6所示。
重复规划求解的基本步骤，按照试验方法和沥青种类的不同，将计算得出的沥青表面能参数分别记录于表4至表7中；不同试验方法、沥青种类对应计算得到沥青表面能参数，如表4-7所示；
表4
Figure PCTCN2021120076-appb-000038
表5
Figure PCTCN2021120076-appb-000039
Figure PCTCN2021120076-appb-000040
表6
Figure PCTCN2021120076-appb-000041
Figure PCTCN2021120076-appb-000042
表7
Figure PCTCN2021120076-appb-000043
Figure PCTCN2021120076-appb-000044
为了便于对化学试剂组合进行第一次筛选，考虑以下条件后对数据进行记录与整理：WFE表示“蒸馏水+甲酰胺+乙二醇”的试剂组合，WFEG则表示“蒸馏水+甲酰胺+乙二醇+丙三醇”的试剂组合，以此类推； 由于实际中沥青并非单极性物质，三个表面能参数均应大于零，而部分表面能参数计算值为零值，因此，为了便于下一章分析数据的稳定性和异常值，排除明显不合理数据的干扰，以下将仅考虑表面能参数计算值不为零的化学试剂组合；每种试剂组合下计算得出的沥青表面能总量不得大于该组合中任何一种化学试剂的表面能总量，否则排除。
一个具体实施例中，利用变异系数先评价试验方法之间的数据稳定性，完成对化学试剂组合的第一次筛选，后评价化学试剂组合之间的数据稳定性，并完成第二次筛选。
按照试验方法的不同，分别计算每种化学试剂与沥青玻片形成的接触角数值的变异系数大小，选出数据离散程度最小的试验方法。各组数据的变异系数值列于表8和表9中，表8、表9分别对应静滴法及插板法获取的接触角数值的变异系数大小。
表8
Figure PCTCN2021120076-appb-000045
表9
Figure PCTCN2021120076-appb-000046
Figure PCTCN2021120076-appb-000047
以静滴法试验中蒸馏水与70#基质沥青所测接触角数据为例，其变异系数计算为
Figure PCTCN2021120076-appb-000048
通过比较两种方法的C.V.值可得，除三种情况外，静滴法测得接触角数据的变异系数均大于插板法，即静滴法测得接触角数据的离散程度大于插板法，该三种情况包括70#基质沥青+W，SBS改性沥青+F，SBS改性沥青+B。
具体实施时，静滴法试验的人为干扰因素较多，导致数据频繁产生较大误差。由表4至表7可知，由于静滴法测得的接触角数据不甚理想，致使规划求解的沥青表面能参数经常为零值，不得不排除过多化学试剂组合类型；相对于静滴法，插板法测得的接触角数据稳定性较好，多次平行试验所得数据的变异系数均小于4％，而且试验操作过程中人为干扰因素较少，对数据精确度和制作沥青玻片的水平要求较高。因此，为了使结论更具普适性和有效性，仅评价分析插板法试验条件下筛选得到的化学试剂组合的数据稳定性。
由表5和7可得，两种沥青的表面能参数计算值同时不为零的试剂组合类型共有24种，按照不同种类的沥青表面能参数，分别计算每一化学试剂组合规划求解所得数据(接触角)的变异系数大小，并记录于表10中，其中，对于某一特定的沥青表面能参数，变异系数值取两种沥青计算所得变异系数的平均值。需要说明的是，由于重复进行三次测试，每一化学试剂组合规划求解所得数据为三个值，所述计算变异系数大小 即计算该三个值的变异系数大小。每一化学试剂组合对应接触角的变异系数大小，如表10所示。
表10
Figure PCTCN2021120076-appb-000049
由表10可知，对于不同种类的沥青表面能参数，每种化学试剂组合 规划求解所得数据的变异系数大小比较如下(仅取数值较小的前十种)，
Figure PCTCN2021120076-appb-000050
WFDB<WFDN<WGDB<WGSD<WFGD<WFSD<WFBN<WFE＝FEG<WSD＝WFS＝FGS＝GSD；
Figure PCTCN2021120076-appb-000051
GSD<WFD<WFS<WGS<WSD<WGDN<WFG<WFGB<WFSD<WGD；
Figure PCTCN2021120076-appb-000052
WFES<WSD<WFGD<WGDB<WFEG<GSD<WFGS<WFGB<WGD<WEGS；
Figure PCTCN2021120076-appb-000053
WFDB<WFD<WGS<GSD<WSD<WFDN<WFGB<WGDB<WGD<WFSD；
γ S：WFSD<WGDB<WFBN＝WFDN<WGSD<WFDB<WFGD<WFGB<WSD<GSD。
通过比较可知，在5种沥青表面能分量中没有唯一变异系数最小的化学试剂组合，因此选取出每种表面能分量对应的变异系数较小的前三种化学试剂组合，分别为：WFD、WFS、WSD、GSD、WGS、WFES、WFGD、WFSD、WFDB、WFDN、WFBN、WGDB。
由于数据中或多或少存在异常值，故需要对上述十二种试剂组合进行异常值的检验，从而排除异常值对数据稳定性分析的干扰，保证变异系数在衡量各组数据离散程度方面的准确性与可靠度，最终选取出数据稳定性较好且异常值较少的试剂组合。最后以基质沥青的非极性分量
Figure PCTCN2021120076-appb-000054
为例，借助跳跃度来分析上述十二种试剂组合中数据是否存在异常值。
按照跳跃度的检验步骤，将表10中所有试剂组合对基质沥青的非极性分量
Figure PCTCN2021120076-appb-000055
规划求解得出的计算值按照由小到大的顺序排列如下：7.98，16.81，18.27，18.27，18.27，18.28，18.28，18.28，18.33，18.86，19.22，20.11，21.53，21.53，21.53，21.53，22.2，22.2，22.2，22.2，24.91，24.91， 24.91，25.06，其次，由跳跃度的计算公式可得：
μ 1＝191.52,μ 2＝197.31,μ 3＝142.24,...,μ 23＝21.11,μ 24＝20.24
Figure PCTCN2021120076-appb-000056
由以上计算可知，除了
Figure PCTCN2021120076-appb-000057
其他各跳跃度均小于1，因此第一个数据7.98为异常小值，即试剂组合WFGB对基质沥青的非极性分量
Figure PCTCN2021120076-appb-000058
的计算值中存在异常值。同样地，运用跳跃度这一检验方法分析通过变异系数选取出的十二种试剂组合，分别判断每种试剂组合所得数据中存在异常值的个数，如表11所示。
表11
Figure PCTCN2021120076-appb-000059
由表11可知，化学试剂组合GSD通过计算所得数据中异常值的个数最少为零，即不存在异常值的出现，并且结合对每种试剂组合计算所得数据的变异系数分析，化学试剂组合GSD的数据稳定性相对较优且异常值相对最少。
最终选择丙三醇、二甲基亚砜和二碘甲烷三种化学试剂，并将沥青表面能参数计算值记录于表12中，沥青表面能参数计算值，如表12所示。
表12
Figure PCTCN2021120076-appb-000060
实施例3
本发明实施例提供了一种沥青材料表面能测试中化学试剂的选取系统，其结构框图，如图7所示，所述系统包括接触角获取模块1、沥青表面能参数获取模块2、化学试剂组合范围获取模块3及化学试剂组合确定模块4；
所述接触角获取模块1，用于选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；
所述沥青表面能参数获取模块2，用于根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
所述化学试剂组合范围获取模块3，用于获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
所述化学试剂组合确定模块4，用于获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合。
本发明公开了一种沥青材料表面能测试中化学试剂的选取方法及系统，通过选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合；可以选择出试验数据稳定性较高的化学试剂组合类型。
本发明技术方案运用总体最小二乘法求解方程组可以使得沥青各表面能参数计算值与实际值之间的误差减小，且更为符合由三个基本未知 方程构成的该方程组在三维空间中代表的几何意义；由此，使求解方程组得出的三个沥青表面能参数更加合理，同时更加趋近于实际值的大小，从而为数据稳定性评价提供了更为准确的数据基础。
在分析数据稳定性进而评判数据是否合理有效方面，引入一种新的分析方法评估沥青材料表面能测试中数据的稳定性，即运用变异系数这一统计学中常用到的数字特征分析每组数据的玻动大小，并借助跳跃度这一检验方法排除每组数据中的异常值对稳定性分析的干扰；其意义在于，将变异系数和跳跃度首次应用于路面沥青表面能参数试验数据分析当中，目的是对存在较大差异性的各组数据进行筛选，从而为精确计算表面能参数试验设计提供依据。
通过本发明技术方案选取出试验数据稳定较高的化学试剂组合，为从事测试沥青表面能参数的试验人员提供一种合理有效的选取化学试剂的方法依据，并能够较好地应用于路面沥青方向的性能试验。
以上所述，仅为本发明较佳的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。

Claims (10)

  1. 一种沥青材料表面能测试中化学试剂的选取方法，其特征在于，包括以下步骤：
    选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；
    根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
    获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
    获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化学试剂组合。
  2. 根据权利要求1所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，所述获取化学试剂与沥青玻片形成的接触角数值，具体包括：
    计算化学试剂在不同试验方法条件下，与沥青玻片形成的接触角数值的变异系数大小，获取数据离散程度最小的试验方法，并以该试验方法获取不同化学试剂与沥青玻片形成的接触角数值。
  3. 根据权利要求1所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数，具体包括：
    根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数的多个值，根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数。
  4. 根据权利要求3所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，根据所述化学试剂与沥青玻片形成的接触角数值，获 取化学试剂组合对应的沥青表面能参数的多个值，具体包括：
    根据所述化学试剂与沥青玻片形成的接触角数值及沥青表面能参数计算公式，获取化学试剂组合对应的沥青表面能参数的多个值；所述沥青表面能参数计算公式为
    Figure PCTCN2021120076-appb-100001
    其中，
    Figure PCTCN2021120076-appb-100002
    为沥青的表面能非极性分量，
    Figure PCTCN2021120076-appb-100003
    为化学试剂的表面能非极性分量，
    Figure PCTCN2021120076-appb-100004
    为沥青的表面能极性碱分量，
    Figure PCTCN2021120076-appb-100005
    为沥青的表面能极性酸分量，
    Figure PCTCN2021120076-appb-100006
    为化学试剂的表面能极性碱分量，
    Figure PCTCN2021120076-appb-100007
    为化学试剂的表面能极性酸分量，γ L为化学试剂的表面能总量，θ为接触角。
  5. 根据权利要求4所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，具体包括：
    根据所述沥青表面能参数的多个值并以拟合误差最小值为目标值，确定化学试剂组合对应的沥青表面能参数，所述拟合误差最小值
    Figure PCTCN2021120076-appb-100008
  6. 根据权利要求1所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围，具体包括：
    在所述若干不同化学试剂中，选取两种沥青的表面能参数同时不为零的化学试剂组合，分别计算每一种化学试剂组合的不同种类沥青表面能参数的变异系数，根据不同种类沥青表面能参数的变异系数，选取化学试剂组合范围。
  7. 根据权利要求6所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，获取所述化学试剂组合范围中沥青表面能分量异常值的个数，具体包括：
    根据两种沥青的沥青表面能参数同时不为零的化学试剂组合的沥青表面能分量跳跃度，确定所述化学试剂组合范围中各个化学试剂组合沥青表面能分量的异常值个数。
  8. 根据权利要求7所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，根据所述异常值的个数，确定最终的化学试剂组合，具体包括：
    以化学试剂组合范围中沥青表面能分量的异常值个数最少的化学试剂组合，作为最终的化学试剂组合。
  9. 根据权利要求1所述的沥青材料表面能测试中化学试剂的选取方法，其特征在于，所述化学试剂组合包括3种化学试剂或者4种化学试剂。
  10. 一种沥青材料表面能测试中化学试剂的选取系统，其特征在于，包括接触角获取模块、沥青表面能参数获取模块、化学试剂组合范围获取模块及化学试剂组合确定模块；
    所述接触角获取模块，用于选取若干不同化学试剂，获取化学试剂与沥青玻片形成的接触角数值；
    所述沥青表面能参数获取模块，用于根据所述化学试剂与沥青玻片形成的接触角数值，获取化学试剂组合对应的沥青表面能参数；
    所述化学试剂组合范围获取模块，用于获取化学试剂组合对应的沥青表面能参数的变异系数，并根据所述变异系数选取化学试剂组合范围；
    所述化学试剂组合确定模块，用于获取所述化学试剂组合范围中沥青表面能分量异常值的个数，并根据所述异常值的个数，确定最终的化 学试剂组合。
PCT/CN2021/120076 2021-01-20 2021-09-24 一种沥青材料表面能测试中化学试剂的选取方法及系统 WO2022156256A1 (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
US17/863,390 US20220357308A1 (en) 2021-01-20 2022-07-13 Method and system for selecting chemical reagents in measurement of asphalt surface energy

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN202110076963.X 2021-01-20
CN202110076963.XA CN112816366A (zh) 2021-01-20 2021-01-20 一种沥青材料表面能测试中化学试剂的选取方法及系统

Related Child Applications (1)

Application Number Title Priority Date Filing Date
US17/863,390 Continuation US20220357308A1 (en) 2021-01-20 2022-07-13 Method and system for selecting chemical reagents in measurement of asphalt surface energy

Publications (1)

Publication Number Publication Date
WO2022156256A1 true WO2022156256A1 (zh) 2022-07-28

Family

ID=75858808

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2021/120076 WO2022156256A1 (zh) 2021-01-20 2021-09-24 一种沥青材料表面能测试中化学试剂的选取方法及系统

Country Status (3)

Country Link
US (1) US20220357308A1 (zh)
CN (1) CN112816366A (zh)
WO (1) WO2022156256A1 (zh)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111855498B (zh) * 2020-06-24 2023-04-07 同济大学 一种基于表面能理论的沥青混合料拌和温度确定方法
CN112816366A (zh) * 2021-01-20 2021-05-18 武汉理工大学 一种沥青材料表面能测试中化学试剂的选取方法及系统
CN117635582A (zh) * 2023-12-06 2024-03-01 淮安市博彦土木工程科学研究院有限公司 一种基于图像分析的沥青类预防性养护剂裹覆率评价方法

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005337781A (ja) * 2004-05-25 2005-12-08 Ricoh Co Ltd 固体の表面自由エネルギー測定方法及びその測定装置
CN103543090A (zh) * 2013-11-01 2014-01-29 同济大学 一种集料表面能的测试方法
CN103558124A (zh) * 2013-11-01 2014-02-05 同济大学 一种沥青材料表面能的测试方法
CN105806747A (zh) * 2016-02-24 2016-07-27 北京建筑大学 一种沥青-集料界面黏附性能测定方法
CN106290074A (zh) * 2016-09-29 2017-01-04 武汉理工大学 沥青路面填料表面能参数的检测方法
CN106290075A (zh) * 2016-09-29 2017-01-04 武汉理工大学 道路沥青表面自由能的检测方法
CN106769663A (zh) * 2016-12-09 2017-05-31 武汉理工大学 一种测试沥青材料动态表面能参数的方法
CN111595727A (zh) * 2020-06-30 2020-08-28 武汉理工大学 建立快速预测沥青-集料黏附性和沥青黏韧性评价的方法
CN111855498A (zh) * 2020-06-24 2020-10-30 同济大学 一种基于表面能理论的沥青混合料拌和温度确定方法
CN112816366A (zh) * 2021-01-20 2021-05-18 武汉理工大学 一种沥青材料表面能测试中化学试剂的选取方法及系统

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101196809A (zh) * 2006-08-28 2008-06-11 李全水 化学检验结果计算和数据处理软件包
CN104156558B (zh) * 2014-07-02 2017-04-05 中国航空工业集团公司北京航空材料研究院 一种不同化学成分分析方法结果一致性的判断方法
CN105243394B (zh) * 2015-11-03 2019-03-19 中国矿业大学 一种类不平衡对分类模型性能影响程度的评价方法
CN106649579A (zh) * 2016-11-17 2017-05-10 苏州航天系统工程有限公司 一种用于管网建模的时序数据清洗方法
RU2687717C9 (ru) * 2018-06-05 2019-07-22 Государственное бюджетное образовательное учреждение высшего образования "Альметьевский государственный нефтяной институт" Методика оценки влияния химических реагентов на реологические свойства нефти
CN110954443B (zh) * 2019-12-09 2020-11-17 武汉理工大学 采用插板法计算沥青材料动态接触角的方法

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2005337781A (ja) * 2004-05-25 2005-12-08 Ricoh Co Ltd 固体の表面自由エネルギー測定方法及びその測定装置
CN103543090A (zh) * 2013-11-01 2014-01-29 同济大学 一种集料表面能的测试方法
CN103558124A (zh) * 2013-11-01 2014-02-05 同济大学 一种沥青材料表面能的测试方法
CN105806747A (zh) * 2016-02-24 2016-07-27 北京建筑大学 一种沥青-集料界面黏附性能测定方法
CN106290074A (zh) * 2016-09-29 2017-01-04 武汉理工大学 沥青路面填料表面能参数的检测方法
CN106290075A (zh) * 2016-09-29 2017-01-04 武汉理工大学 道路沥青表面自由能的检测方法
CN106769663A (zh) * 2016-12-09 2017-05-31 武汉理工大学 一种测试沥青材料动态表面能参数的方法
CN111855498A (zh) * 2020-06-24 2020-10-30 同济大学 一种基于表面能理论的沥青混合料拌和温度确定方法
CN111595727A (zh) * 2020-06-30 2020-08-28 武汉理工大学 建立快速预测沥青-集料黏附性和沥青黏韧性评价的方法
CN112816366A (zh) * 2021-01-20 2021-05-18 武汉理工大学 一种沥青材料表面能测试中化学试剂的选取方法及系统

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
DONG HUAJUN, ZENG ZHE;LUO RONG;ZHANG DERUN;JIN LU;WANG LIJING: "Error Analysis of the Wilhelmy Plate Method to Determine the Surface Energy of Asphalt Binders", JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY(TRANSPORTATION SCIENCE & ENGINEERING), vol. 40, no. 5, 15 October 2016 (2016-10-15), pages 859 - 863, XP055952225, ISSN: 2095-3844, DOI: 10.3963/j.issn.2095-3844.2016.05.020 *
JIN LU;WANG LIJING;TU CHONGZHI;FENG GUANGLE;LUO RONG: "Experimental Study on Surface Energy Measurement of Asphalt by Wilhelmy Plate Method at Different Temperatures", JOURNAL OF WUHAN UNIVERSITY OF TECHNOLOGY(TRANSPORTATION SCIENCE & ENGINEERING), vol. 42, no. 4, 15 August 2018 (2018-08-15), pages 590 - 593, XP055952221, ISSN: 2095-3844, DOI: 10.3969/j.issn.2095-3844.2018.04.012 *

Also Published As

Publication number Publication date
CN112816366A (zh) 2021-05-18
US20220357308A1 (en) 2022-11-10

Similar Documents

Publication Publication Date Title
WO2022156256A1 (zh) 一种沥青材料表面能测试中化学试剂的选取方法及系统
Bhasin Development of methods to quantify bitumen-aggregate adhesion and loss of adhesion due to water
Gonzalez et al. Considerations on reproducibility of potential and corrosion rate measurements in reinforced concrete
BR112020020717B1 (pt) Sistema de titulação automatizado, e, método para quantificar uma concentração de analito alvo em uma corrente de amostra
US20100117666A1 (en) Method and System for Internal Standardization of Assays
CN108279220A (zh) 一种atr附件快速检测sbs改性沥青掺量的方法
WO2017215299A1 (zh) 一种微透镜(或微透镜阵列)成像检测板
US11009450B2 (en) Systems and methods for quality testing of asphalt by predicting an indirect tensile strength ratio of the asphalt sample based on the binder loss value
Luo et al. High-throughput microscopy to determine morphology, microrheology, and phase boundaries applied to phase separating coacervates
CN108344710A (zh) 一种沥青识别检验方法
CN107356650A (zh) 一种微量元素检测的数据分析方法
JP2008122170A (ja) 外装部材の耐候劣化診断方法
US8311955B2 (en) Bootstrap method for oil property prediction
US6515293B1 (en) Method and apparatus for detecting thickness of thin layer formed on a wafer
CN106324004A (zh) 一种工业碳酸锶中化学成分含量的检测方法
CN110954443B (zh) 采用插板法计算沥青材料动态接触角的方法
CN109486221B (zh) 基于相态结构确定废旧sbs改性沥青再生剂用量的方法
Wistuba et al. Adhesion of bitumen: Screening and evaluating laboratory testing techniques
JP5569738B2 (ja) 多孔質材料の含液状態評価方法および多孔質材料の含液状態評価システム
Pereira et al. Statistical validation of standardless and standard-based analysis by X-ray fluorescence spectrometry in iron ores characterisation
COFFEY Simple and practical tests for rutting evaluation of asphalt mixtures in the balanced mix design process
US20090287417A1 (en) Method for Detecting a Biochemical Interaction
Holubka et al. Acid etch resistance of automotive clearcoats. I: Laboratory test method development
CN105572924B (zh) 彩膜基板的彩色层脱落率的测试方法
Lim et al. Between and within calibration variation: implications for internal quality control rules

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 21920634

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 21920634

Country of ref document: EP

Kind code of ref document: A1