CN109709060B - Method for measuring asphalt softening point, penetration degree and mass loss - Google Patents

Method for measuring asphalt softening point, penetration degree and mass loss Download PDF

Info

Publication number
CN109709060B
CN109709060B CN201910089101.3A CN201910089101A CN109709060B CN 109709060 B CN109709060 B CN 109709060B CN 201910089101 A CN201910089101 A CN 201910089101A CN 109709060 B CN109709060 B CN 109709060B
Authority
CN
China
Prior art keywords
asphalt
characteristic
infrared spectrogram
asphalt sample
softening point
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.)
Active
Application number
CN201910089101.3A
Other languages
Chinese (zh)
Other versions
CN109709060A (en
Inventor
赵静卓
魏强
王学娟
陈鹏
王晖
曹青霞
丁民
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Gansu Changlong Highway Maintenance Technology Research Institute Co ltd
Gansu Province Transportation Planning Survey and Design Institute Co Ltd
Original Assignee
Gansu Changlong Highway Maintenance Technology Research Institute Co ltd
Gansu Province Transportation Planning Survey and Design Institute Co Ltd
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 Gansu Changlong Highway Maintenance Technology Research Institute Co ltd, Gansu Province Transportation Planning Survey and Design Institute Co Ltd filed Critical Gansu Changlong Highway Maintenance Technology Research Institute Co ltd
Priority to CN201910089101.3A priority Critical patent/CN109709060B/en
Publication of CN109709060A publication Critical patent/CN109709060A/en
Application granted granted Critical
Publication of CN109709060B publication Critical patent/CN109709060B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Investigating Or Analysing Materials By Optical Means (AREA)

Abstract

The invention provides a method for measuring asphalt softening point, penetration and quality loss, belonging to the technical field of road engineering application. The test method provided by the invention comprises the following steps: testing the characteristic parameters of the asphalt sample of the modeling group, and collecting an infrared spectrogram of the asphalt sample of the modeling group; the characteristic parameter is softening point, penetration or mass loss; establishing a quantitative analysis model by using the characteristic parameters of the asphalt samples of the modeling group and the corresponding spectral information in the characteristic wavelength range; collecting an infrared spectrogram of the asphalt sample to be detected, and combining a quantitative analysis model according to spectral information in a characteristic wavelength range corresponding to the characteristic parameters in the obtained infrared spectrogram to obtain the characteristic parameter values of the asphalt sample to be detected. The testing method provided by the invention can be operated at room temperature and has the advantage of short time consumption.

Description

Method for measuring asphalt softening point, penetration degree and mass loss
Technical Field
The invention relates to the technical field of road engineering application, in particular to a method for measuring asphalt softening point, penetration and mass loss.
Background
The influence of asphalt on road quality is huge, and the phenomenon that the fake asphalt is used is occasionally happened according to the investigation that unqualified asphalt products still exist in the asphalt market in China. The traditional simple physical property detection method is time-consuming and labor-consuming, is easily influenced by additives such as a modifier and a stabilizer, and is easy to distort the test result. Due to the complexity of the chemical properties of asphalt, asphalt specifications develop tests aiming at physical properties, such as penetration, softening point, ductility and the like, the tests for the physical properties are carried out at standard test temperature, test results are used for determining whether materials meet the standards of the specifications, three performance indexes are traditional detection methods for judging the performance of the asphalt, and the simple operation is irreplaceable by other methods and is also the main method for detecting the asphalt in the highway industry so far. Although the three performance indexes are simple to operate, asphalt needs to be pre-melted, the time from molding and curing to testing is 4 to 5 hours, the time is long, and the quality of the asphalt cannot be timely and effectively judged.
Disclosure of Invention
The invention aims to provide a method for measuring asphalt softening point, penetration and mass loss, which can be carried out at room temperature and has short test time.
In order to achieve the above object, the present invention provides the following technical solutions:
the invention provides a method for measuring the softening point, penetration and mass loss of asphalt, which comprises the following steps:
testing the characteristic parameters of the asphalt sample of the modeling group, and collecting an infrared spectrogram of the asphalt sample of the modeling group; the characteristic parameter is softening point, penetration or mass loss;
establishing a quantitative analysis model by using the characteristic parameters of the asphalt samples of the modeling group and the corresponding spectral information in the characteristic wavelength range;
collecting an infrared spectrogram of the asphalt sample to be detected, and combining a quantitative analysis model according to spectral information in a characteristic wavelength range corresponding to the characteristic parameters in the obtained infrared spectrogram to obtain the characteristic parameter values of the asphalt sample to be detected.
Preferably, the building block comprises more than 20 bitumen samples.
Preferably, the characteristic parameters of the modeling asphalt sample are measured by a method disclosed in the standard with the standard number of JTG E-20-2011.
Preferably, the acquisition conditions of the infrared spectrogram are as follows: spectral scanning range 4000-10000 cm-1And the number of scans is 128.
Preferably, after acquiring the infrared spectrogram of the modeling asphalt sample and the infrared spectrogram of the asphalt sample to be detected, the method further comprises preprocessing the acquired infrared spectrogram, wherein the preprocessing comprises background subtraction, smoothing processing and baseline correction processing which are sequentially performed.
Preferably, the characteristic wavelength range corresponding to the softening point is 4204.06-4373.76 cm-1(ii) a The characteristic wavelength range corresponding to the penetration is 4448.34-4785.48 cm-1、4836.99~5342.71cm-15333.34-6063.82 cm-1(ii) a The characteristic wavelength range corresponding to the mass loss is 4180.92-6024.53 cm-1
Preferably, the quantitative analysis model is established using TQ Analyst spectral analysis software.
Preferably, a TQ Analyst spectral analysis software is adopted to calculate the characteristic parameter value of the asphalt sample to be detected.
The invention provides a method for measuring the softening point, penetration and mass loss of asphalt, which comprises the following steps: testing the characteristic parameters of the asphalt sample of the modeling group, and collecting an infrared spectrogram of the asphalt sample of the modeling group; the characteristic parameter is softening point, penetration or mass loss; establishing a quantitative analysis model by using the characteristic parameters of the asphalt samples of the modeling group and the corresponding spectral information in the characteristic wavelength range; collecting an infrared spectrogram of the asphalt sample to be detected, and combining a quantitative analysis model according to spectral information in a characteristic wavelength range corresponding to the characteristic parameters in the obtained infrared spectrogram to obtain the characteristic parameter values of the asphalt sample to be detected. The method establishes a quantitative analysis model for the characteristic parameters (softening point, penetration and quality loss) of the asphalt and the spectral information in the characteristic wavelength range in the infrared spectrogram, then obtains the characteristic parameter values of the asphalt sample to be detected by collecting the infrared spectrogram of the sample to be detected and combining the quantitative analysis model, can be operated at room temperature, and has the advantage of short time consumption.
Drawings
FIG. 1 is a correlation curve of measured values to calculated values of softening points obtained in example 1;
FIG. 2 is a correlation curve of measured value-calculated value of penetration obtained in example 1;
FIG. 3 is a correlation curve of measured mass loss value vs. calculated mass loss value obtained in example 1.
Detailed Description
The invention provides a method for measuring the softening point, penetration and mass loss of asphalt, which comprises the following steps:
testing the characteristic parameters of the asphalt sample of the modeling group, and collecting an infrared spectrogram of the asphalt sample of the modeling group; the characteristic parameter is softening point, penetration or mass loss;
establishing a quantitative analysis model by using the characteristic parameters of the asphalt samples of the modeling group and the corresponding spectral information in the characteristic wavelength range;
collecting an infrared spectrogram of the asphalt sample to be detected, and combining a quantitative analysis model according to spectral information in a characteristic wavelength range corresponding to the characteristic parameters in the obtained infrared spectrogram to obtain the characteristic parameter values of the asphalt sample to be detected.
The method comprises the steps of testing characteristic parameters of a modeling group asphalt sample, and collecting an infrared spectrogram of the modeling group asphalt sample; the characteristic parameter is a softening point, penetration or mass loss.
In the present invention, the modeling group preferably includes more than 20 kinds of asphalt samples, and more preferably includes more than 80 kinds of asphalt samples.
The source of the asphalt sample of the modeling group is not particularly limited, and the asphalt sample can be any commercially available asphalt sample. In the present invention, the asphalt samples of the modeling group are preferably a plurality of asphalt samples having large differences in the values of the characteristic parameters.
In the invention, the characteristic parameters of the asphalt samples in the modeling group are preferably measured by a method disclosed in the standard with the standard number of JTGE-20-2011.
In the present invention, the acquisition conditions of the infrared spectrogram are preferably: spectral scanning range 4000-10000 cm-1And the number of scans is 128.
After the infrared spectrogram of the asphalt sample of the modeling group is collected, the method preferably further comprises the step of preprocessing the obtained infrared spectrogram, wherein the preprocessing preferably comprises the steps of background subtraction, smoothing and baseline correction which are sequentially carried out, so that the infrared spectrogram of the asphalt sample of the modeling group is obtained.
In the present invention, the preprocessing further preferably includes one or more of a cancellation constant, a first order derivation, and a second order derivation. In the present invention, the skilled person can select whether to adopt the above-mentioned pretreatment operation according to the needs.
In the present invention, the infrared spectrogram is preferably preprocessed using TQ Analyst spectral analysis software.
And after the characteristic parameters and the infrared spectrogram of the asphalt sample of the modeling group are obtained, establishing a quantitative analysis model by using the characteristic parameters and the corresponding spectral information within the characteristic wavelength range of the asphalt sample of the modeling group.
In the invention, the characteristic wavelength range corresponding to the softening point is preferably 4204.06-4373.76 cm-1(ii) a The characteristic wavelength range corresponding to the penetration is preferably 4448.34-4785.48 cm-1、4836.99~5342.71cm-15333.34-6063.82 cm-1(ii) a The characteristic wavelength range corresponding to the mass loss is preferably 4180.92-6024.53 cm-1
In the present invention, preferably, TQ Analyst spectral analysis software is used to build the quantitative analysis model; the proposed method of the quantitative analysis model preferably comprises the following steps:
entering an operation interface of TQ Analyst spectral analysis software → selecting a modeling algorithm → defining components to be measured (namely, inputting the name, softening point, penetration and quality loss of the asphalt sample of the modeling group) → importing an infrared spectrogram of the sample of the modeling group → selecting a characteristic wavelength range corresponding to characteristic parameters → calculating a model, and obtaining a quantitative analysis model.
In the present invention, the modeling algorithm is preferably a partial least squares method.
After the quantitative analysis model is obtained, the invention collects the infrared spectrogram of the asphalt sample to be detected, and obtains the characteristic parameter value of the asphalt sample to be detected by combining the quantitative analysis model according to the spectral information in the characteristic wavelength range corresponding to the characteristic parameter in the obtained infrared spectrogram.
In the invention, after the infrared spectrogram of the asphalt sample to be detected is acquired, the acquired infrared spectrogram is preferably preprocessed; the pretreatment is preferably the same as the pretreatment method of the infrared spectrogram of the asphalt sample of the modeling group, and the details are not repeated.
In the present invention, the calculation of the characteristic parameter value of the asphalt sample to be measured preferably includes the following steps:
and (4) introducing an infrared spectrogram of the asphalt sample to be detected → selecting a characteristic wavelength range corresponding to the characteristic parameter → quantifying to obtain the characteristic parameter value.
The method for measuring the softening point, penetration and mass loss of asphalt according to the present invention will be described in detail with reference to the following examples, but they should not be construed as limiting the scope of the present invention.
Example 1
Taking SK90#, SK70#, Zhehai 90#, Zhehai 70#, Kehai 90# and Kehai 70# asphalt samples of different batches as modeling group samples, and measuring the softening point, penetration (the test conditions are 25 ℃, the load is 100g and the penetration time is 5s) and mass loss (the test conditions are 163 ℃ and the ageing is 85min) of 80 samples by adopting a method disclosed by a standard number JTG E-20-2011. The spectral scanning range of the Fourier infrared spectrometer is 4000-10000 cm-1Scanning for 128 times, and acquiring infrared spectrograms of the 80 samples;
entering an operation interface of TQ Analyst spectral analysis software, selecting a partial least square method as a modeling algorithm, defining a component to be detected, inputting the name, the softening point, the penetration and the mass loss of an asphalt sample of a modeling group, introducing an infrared spectrogram of the sample of the modeling group, and sequentially carrying out background subtraction, smoothing and baseline correction to obtain a preprocessed infrared spectrogram;
selecting a characteristic wavelength range (the characteristic wavelength range corresponding to a softening point is 4204.06-4373.76 cm)-1(ii) a The characteristic wavelength range corresponding to the penetration is 4448.34-4785.48 cm-1、4836.99~5342.71cm-15333.34-6063.82 cm-1(ii) a The characteristic wavelength range corresponding to the mass loss is 4180.92-6024.53 cm-1) Calculating a model (clicking "calibration") to obtain a quantitative analysis model, and giving a softening point measured value-calculated value correlation curve (as shown in fig. 1, the abscissa is measured value and the ordinate is calculated value), a penetration measured value-calculated value correlation curve (as shown in fig. 2) and a mass loss measured value-calculated value correlation curve (as shown in fig. 3) by software;
the softening point, penetration and quality loss (marked as a true value) of 5 samples to be tested are measured by adopting a method disclosed by a standard number JTG E-20-2011, the results are shown in table 1, an infrared spectrogram of the samples to be tested is collected according to a method for collecting the infrared spectrogram by a modeling group, the infrared spectrogram of the samples to be tested is led into TQ Analyst spectral analysis software, background subtraction, smoothing and baseline correction are sequentially carried out, then a characteristic wavelength range (the specific range is the same as that of the asphalt samples of the modeling group) is selected, quantification (the 'Quantify' is clicked) is carried out, and test values are obtained, and the results are shown in table 1.
TABLE 1 comparison of the values of the characteristic parameters obtained by the test method according to the invention with the true values obtained by the standard method
Figure BDA0001962699740000051
Figure BDA0001962699740000061
As can be seen from fig. 1 to 3, the correlation coefficients of the measured value and the calculated value predicted by the asphalt sample of the modeling group are all above 0.9, which indicates that the calculated value obtained by the measurement method provided by the present invention is very close to the measured value obtained by the conventional standard method, and the test method provided by the present invention has higher accuracy. As shown in Table 1, the test values obtained by the method of the present invention are consistent with the true values obtained by the standard method, and the error is very small, which further indicates that the method of the present invention has high reliability.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (2)

1. A method for measuring the softening point, penetration and mass loss of asphalt comprises the following steps:
testing the characteristic parameters of the asphalt sample of the modeling group, and collecting an infrared spectrogram of the asphalt sample of the modeling group; the characteristic parameter is softening point, penetration or mass loss;
establishing a quantitative analysis model by using the characteristic parameters of the asphalt samples of the modeling group and the corresponding spectral information in the characteristic wavelength range;
acquiring an infrared spectrogram of an asphalt sample to be detected, and combining a quantitative analysis model according to spectral information in a characteristic wavelength range corresponding to characteristic parameters in the acquired infrared spectrogram to obtain characteristic parameter values of the asphalt sample to be detected;
adopting TQ Analyst spectral analysis software to establish the quantitative analysis model, and adopting the TQ Analyst spectral analysis software to calculate the characteristic parameter value of the asphalt sample to be detected;
the building module comprises more than 20 asphalt samples;
the acquisition conditions of the infrared spectrogram are as follows: spectral scanning range 4000-10000 cm-1Scan number 128;
after acquiring the infrared spectrogram of the asphalt sample of the modeling group and the infrared spectrogram of the asphalt sample to be detected, preprocessing the obtained infrared spectrogram, wherein the preprocessing comprises background subtraction, smoothing processing and baseline correction processing which are sequentially performed; the preprocessing further comprises one or more of eliminating constants, first-order derivatives and second-order derivatives;
the characteristic wave number range corresponding to the softening point is 4204.06-4373.76 cm-1(ii) a The characteristic wave number range corresponding to the penetration is 4448.34-4785.48 cm-1、4836.99~5342.71cm-15333.34-6063.82 cm-1(ii) a The characteristic wave number range corresponding to the mass loss is 4180.92-6024.53 cm-1
2. The method according to claim 1, wherein the characteristic parameters of the model asphalt sample are measured by a method disclosed in standard JTG E-20-2011.
CN201910089101.3A 2019-01-30 2019-01-30 Method for measuring asphalt softening point, penetration degree and mass loss Active CN109709060B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910089101.3A CN109709060B (en) 2019-01-30 2019-01-30 Method for measuring asphalt softening point, penetration degree and mass loss

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910089101.3A CN109709060B (en) 2019-01-30 2019-01-30 Method for measuring asphalt softening point, penetration degree and mass loss

Publications (2)

Publication Number Publication Date
CN109709060A CN109709060A (en) 2019-05-03
CN109709060B true CN109709060B (en) 2021-12-07

Family

ID=66262079

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910089101.3A Active CN109709060B (en) 2019-01-30 2019-01-30 Method for measuring asphalt softening point, penetration degree and mass loss

Country Status (1)

Country Link
CN (1) CN109709060B (en)

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111965140B (en) * 2020-08-24 2022-03-01 四川长虹电器股份有限公司 Wavelength point recombination method based on characteristic peak
CN113867292B (en) * 2021-10-09 2023-09-19 益路恒丰衡水沥青科技有限公司 Rubber asphalt quality control method

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103868882A (en) * 2012-12-13 2014-06-18 中国石油化工股份有限公司 Method for determining contents of various components in asphalt
CN109001151A (en) * 2018-09-30 2018-12-14 江苏中路工程技术研究院有限公司 A method of quickly detecting pitch macro-indicators based on near-infrared spectrum technique

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101368905B (en) * 2008-09-08 2011-01-12 淮阴工学院 Infrared spectrum non-linear modeling quantitative anslysis method
KR101121663B1 (en) * 2009-05-22 2012-03-09 한국석유공사 Prediction method of bitumen content in oil sand using FT-IR measurement
CN104792686A (en) * 2014-01-22 2015-07-22 重庆医科大学 Method for detecting microbe quantity and drug content of semisolid preparation through near infrared spectroscopy
CN105372200B (en) * 2015-10-16 2018-07-31 内蒙古自治区交通建设工程质量监督局 SBS modified asphalt modifier method for quickly detecting contents
CN107782693A (en) * 2017-10-25 2018-03-09 中石油燃料油有限责任公司研究院 A kind of infrared spectrum analysis of Asphalt Penetration
CN108344710A (en) * 2017-12-19 2018-07-31 中设设计集团股份有限公司 A kind of pitch test for identification method
CN107941739A (en) * 2017-12-29 2018-04-20 交通运输部公路科学研究所 A kind of SBS performance of modified bitumen index method for rapidly judging
CN108398398A (en) * 2018-02-12 2018-08-14 山西省交通科学研究院 The method for identifying asphalt quality using decaying In situ ATR-FTIR standard spectrogram

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103868882A (en) * 2012-12-13 2014-06-18 中国石油化工股份有限公司 Method for determining contents of various components in asphalt
CN109001151A (en) * 2018-09-30 2018-12-14 江苏中路工程技术研究院有限公司 A method of quickly detecting pitch macro-indicators based on near-infrared spectrum technique

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Applications of Fourier transform infrared spectroscopy technologies on asphalt materials;Hou Xiangdao等;《Measurement》;20180302;第121卷;第304-316页 *
对沥青化学组分分析方法的研究;***等;《黑龙江交通科技》;20140831(第8期);第17-18页 *
红外光谱仪快速测试沥青原理及可靠性检测;张晓香;《中国公路》;20150331(第5期);第126-127页 *

Also Published As

Publication number Publication date
CN109709060A (en) 2019-05-03

Similar Documents

Publication Publication Date Title
CN102590129B (en) Method for detecting content of amino acid in peanuts by near infrared method
CN108181266B (en) TD L AS gas concentration detection method
CN103018195B (en) Method for determination of PCTFE content in PBX explosive by near infrared spectrum
CN103837492B (en) A kind of Kiwi berry based on near-infrared spectrum technique expand fruit lossless detection method
CN107703097B (en) Method for constructing model for rapidly predicting crude oil property by using near-infrared spectrometer
CN105372200A (en) Rapid detection method for SBS modified asphalt modifier contents
CN109709060B (en) Method for measuring asphalt softening point, penetration degree and mass loss
CN109211829A (en) A method of moisture content in the near infrared spectroscopy measurement rice based on SiPLS
CN112179871B (en) Method for nondestructive detection of caprolactam content in sauce food
CN102393376A (en) Support vector regression-based near infrared spectroscopy for detecting content of multiple components of fish ball
CN109615145A (en) A kind of method of the physical property of quick predict difference degree of aging matrix pitch
CN111879709B (en) Lake water body spectral reflectivity inspection method and device
WO2020248961A1 (en) Method for selecting spectral wavenumber without reference value
CN115993344A (en) Quality monitoring and analyzing system and method for near infrared spectrum analyzer
CN112331281A (en) High polymer material service life prediction method based on environmental big data and machine learning
CN104596979A (en) Method for measuring cellulose of reconstituted tobacco by virtue of near infrared reflectance spectroscopy technique
CN104316492A (en) Method for near-infrared spectrum measurement of protein content in potato tuber
CN113030007B (en) Method for rapidly testing quality stability of tobacco essence based on similarity learning algorithm
CN113655027A (en) Method for rapidly detecting tannin content in plant by near infrared
CN105954228A (en) Method for measuring content of sodium metal in oil sand based on near infrared spectrum
CN111337452A (en) Method for verifying feasibility of spectral data model transfer algorithm
CN110186870B (en) Method for distinguishing fresh tea leaf producing area of Enshi Yulu tea by extreme learning machine spectrum model
CN111896497A (en) Spectral data correction method based on predicted value
CN103743697A (en) Method for monitoring tea production in real time by adopting near infrared spectrum
CN111141809A (en) Soil nutrient ion content detection method based on non-contact type conductivity signal

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant