CN110672463B - Asphalt softening point monitoring method - Google Patents
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- CN110672463B CN110672463B CN201911093852.9A CN201911093852A CN110672463B CN 110672463 B CN110672463 B CN 110672463B CN 201911093852 A CN201911093852 A CN 201911093852A CN 110672463 B CN110672463 B CN 110672463B
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- 239000010426 asphalt Substances 0.000 title claims abstract description 230
- 238000000034 method Methods 0.000 title claims abstract description 30
- 238000012544 monitoring process Methods 0.000 title claims abstract description 26
- 230000005484 gravity Effects 0.000 claims abstract description 52
- 238000004364 calculation method Methods 0.000 claims abstract description 40
- 238000001514 detection method Methods 0.000 claims abstract description 18
- 238000004519 manufacturing process Methods 0.000 claims abstract description 17
- 239000010779 crude oil Substances 0.000 claims description 8
- 230000001419 dependent effect Effects 0.000 claims description 6
- 239000000203 mixture Substances 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 238000005070 sampling Methods 0.000 abstract description 13
- 238000004458 analytical method Methods 0.000 abstract description 5
- 238000012417 linear regression Methods 0.000 abstract description 5
- 238000010924 continuous production Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000000605 extraction Methods 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000002360 preparation method Methods 0.000 description 2
- 238000012797 qualification Methods 0.000 description 2
- 238000004904 shortening Methods 0.000 description 2
- 238000012952 Resampling Methods 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N9/00—Investigating density or specific gravity of materials; Analysing materials by determining density or specific gravity
- G01N9/36—Analysing materials by measuring the density or specific gravity, e.g. determining quantity of moisture
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N25/00—Investigating or analyzing materials by the use of thermal means
- G01N25/02—Investigating or analyzing materials by the use of thermal means by investigating changes of state or changes of phase; by investigating sintering
- G01N25/04—Investigating or analyzing materials by the use of thermal means by investigating changes of state or changes of phase; by investigating sintering of melting point; of freezing point; of softening point
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Abstract
The invention belongs to the field of asphalt, and particularly relates to a method for monitoring an asphalt softening point, which comprises the following steps: a) in the asphalt production process, monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline; b) calculating to obtain an asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and a pre-fitted asphalt softening point calculation formula; the asphalt softening point calculation formula is obtained according to the following steps: extracting a plurality of samples from an asphalt finished product output pipeline, performing linear regression analysis on the specific gravity, the temperature and the softening point of the asphalt samples, and fitting to obtain an asphalt softening point calculation formula. The monitoring method provided by the invention can realize on-line monitoring of the softening point of the asphalt finished product in the asphalt production process, and does not need to frequently perform manual sampling and traditional softening point detection operation.
Description
Technical Field
The invention belongs to the field of asphalt, and particularly relates to a method for monitoring an asphalt softening point.
Background
In the asphalt production industry, the softening point index is an important numerical value for evaluating the high-temperature performance of asphalt, a softening point determination method in the JTG E20-2011 traffic industry standard uses a special device and instrument, an asphalt sample is manually taken out and manually prepared in the detection process, the ring-and-ball method detection is carried out according to the standard requirement steps, and the index is obtained by simple calculation. The whole process including sampling, sample preparation, equipment preparation and personnel detection is completed within at least 1.5h, and errors such as instrument and equipment, climatic environment, personnel operation and the like also exist.
In the asphalt production industry, the capacity of devices can basically reach 400T/h, and gradually increase, some devices can even reach 1000T/h, if the operation parameters of equipment are adjusted after the asphalt softening point is manually detected, the time for effectively adjusting the precision of production equipment is delayed by more than one hour, and thus, the cost and the material are greatly wasted. Therefore, it is especially important to find an advanced and feasible method for rapidly monitoring the softening point of asphalt on line.
Disclosure of Invention
In view of the above, the present invention provides a method for monitoring a softening point of asphalt, which can realize on-line monitoring of a softening point of an asphalt product in an asphalt production process without frequent manual sampling and conventional softening point detection operations.
The invention provides a method for monitoring the softening point of asphalt, which comprises the following steps:
a) in the asphalt production process, monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline;
b) calculating to obtain an asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and a pre-fitted asphalt softening point calculation formula;
the asphalt softening point calculation formula is obtained according to the following steps:
i) extracting a plurality of samples from an asphalt finished product output pipeline, recording the asphalt specific gravity and the asphalt temperature when each sample is extracted, and detecting the asphalt softening point of each sample;
ii) fitting to obtain an asphalt softening point calculation formula according to the asphalt specific gravity, the asphalt temperature and the asphalt softening point data of each sample obtained in the step i) by taking the asphalt specific gravity and the asphalt temperature as independent variables and the asphalt softening point as dependent variables.
Preferably, the number of the samples is more than or equal to 10.
Preferably, the number of the samples is more than or equal to 50.
Preferably, the specific gravity and the temperature of the asphalt are monitored by a quality flow meter arranged on an asphalt finished product output pipeline.
Preferably, the functional relation used for fitting the asphalt softening point calculation formula is as follows:
y＝β0+β1x1+β2x2+β3x1 2+β4x1x2+β5x2 2formula (I);
in the formula (I), y is the softening point of the asphalt and x1Is the specific gravity of the asphalt,x2is the temperature of the asphalt, beta0Is a constant term, β1、β2、β3、β4And beta5Are coefficients.
Preferably, during the asphalt production process, if the asphalt is produced by changing different crude oils, the sample is re-extracted and the asphalt softening point calculation formula is fitted.
Preferably, in the step i), the method for detecting the softening point of the asphalt is a softening point detection method recorded in road engineering asphalt and asphalt mixture test specification JTG E20-2011.
Compared with the prior art, the invention provides a method for monitoring the softening point of asphalt. The monitoring method provided by the invention comprises the following steps: a) in the asphalt production process, monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline; b) calculating to obtain an asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and a pre-fitted asphalt softening point calculation formula; the asphalt softening point calculation formula is obtained according to the following steps: i) extracting a plurality of samples from an asphalt finished product output pipeline, recording the asphalt specific gravity and the asphalt temperature when each sample is extracted, and detecting the asphalt softening point of each sample; ii) fitting to obtain an asphalt softening point calculation formula according to the asphalt specific gravity, the asphalt temperature and the asphalt softening point data of each sample obtained in the step i) by taking the asphalt specific gravity and the asphalt temperature as independent variables and the asphalt softening point as dependent variables. The present invention calculates the softening point of asphalt by performing linear regression analysis on the specific gravity, temperature and softening point of an asphalt sample and fitting the results of such linear regression analysis into the form of a formula. The method provided by the invention only needs to carry out manual sampling and traditional softening point detection operation in the stage of fitting the asphalt softening point calculation formula, so that frequent manual operation is not needed, and the operation errors of various links such as human, equipment and environment can be effectively reduced and eliminated. Meanwhile, the specific gravity and temperature data of the finished asphalt product can be monitored online in real time in the production process of the asphalt, so that the method provided by the invention can calculate the corresponding softening point according to the specific gravity and temperature data of the asphalt monitored online in real time, thereby realizing the online monitoring of the softening point of the finished asphalt product in real time, providing online guidance for the continuous production of the asphalt, shortening the debugging working hours, improving the product qualification rate and the product quality, and having remarkable economic benefit.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a method for monitoring the softening point of asphalt, which comprises the following steps:
a) in the asphalt production process, monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline;
b) calculating to obtain an asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and a pre-fitted asphalt softening point calculation formula;
the asphalt softening point calculation formula is obtained according to the following steps:
i) extracting a plurality of samples from an asphalt finished product output pipeline, recording the asphalt specific gravity and the asphalt temperature when each sample is extracted, and detecting the asphalt softening point of each sample;
ii) fitting to obtain an asphalt softening point calculation formula according to the specific gravity, the temperature and the softening point data of each sample obtained in the step i) by taking the asphalt specific gravity and the asphalt temperature as independent variables and the asphalt softening point as dependent variables.
In the detection method provided by the invention, firstly, an asphalt softening point calculation formula is obtained, and the specific steps comprise:
i) extracting a plurality of samples from an asphalt finished product output pipeline, recording the asphalt specific gravity and the asphalt temperature when each sample is extracted, and detecting the asphalt softening point of each sample;
ii) fitting to obtain an asphalt softening point calculation formula according to the asphalt specific gravity, the asphalt temperature and the asphalt softening point data of each sample obtained in the step i) by taking the asphalt specific gravity and the asphalt temperature as independent variables and the asphalt softening point as dependent variables.
In the step of obtaining the asphalt softening point calculation formula provided by the invention, a plurality of samples are firstly extracted from an asphalt finished product output pipeline, and the asphalt specific gravity and the asphalt temperature when each sample is extracted are recorded. Wherein, if pitch finished product output pipeline does not possess when drawing the sample and detecting pitch proportion, temperature's function, then will reform transform pitch finished product output pipeline earlier, concrete step includes: a sampling port is arranged on an asphalt finished product output pipeline, and a quality flow meter for detecting the specific gravity and the temperature of asphalt is arranged on the asphalt finished product output pipeline. In the invention, along the conveying direction of the finished asphalt product, the position of the sampling port is preferably located at the downstream of the installation position of the mass flow meter, and the distance between the sampling port and the installation position of the mass flow meter is preferably less than or equal to 5 m. In the invention, the number of the samples is preferably more than or equal to 10, more preferably more than or equal to 50, and the more the samples are, the better the accuracy of the asphalt softening point calculation formula obtained by subsequent fitting is.
In the step of obtaining the asphalt softening point calculation formula provided by the invention, the asphalt softening point of each sample is detected after sample extraction and specific gravity and temperature recording of the sample are completed. The method for detecting the softening point of the asphalt is preferably a softening point detection method recorded in road engineering asphalt and asphalt mixture test specification JTG E20-2011.
In the step of fitting the asphalt softening point calculation formula provided by the invention, after the asphalt specific gravity, the asphalt temperature and the asphalt softening point data of each sample are obtained, the asphalt specific gravity and the asphalt temperature are used as independent variables, the asphalt softening point is used as a dependent variable, and the asphalt softening point calculation formula is obtained by fitting. Wherein the functional relation formula adopted for fitting the asphalt softening point calculation formula is as follows:
y＝β0+β1x1+β2x2+β3x1 2+β4x1x2+β5x2 2formula (I);
in the formula (I), y is the softening point of the asphalt and x1Is the specific gravity of asphalt, x2Is asphaltTemperature, beta0Is a constant term, β1、β2、β3、β4And beta5Are coefficients.
In the step of obtaining the asphalt softening point calculation formula provided by the invention, the fitting of the asphalt softening point calculation formula is preferably performed in a computer, and the software used for fitting the asphalt softening point calculation formula is preferably Matlab software.
In the detection method provided by the invention, the asphalt softening point in an asphalt finished product output pipeline in the asphalt production process can be monitored on line in real time after the asphalt softening point calculation formula is obtained, and the detection method comprises the following specific steps: monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline; and then calculating to obtain the asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and the asphalt softening point calculation formula.
In the detection method provided by the invention, in order to improve the detection accuracy, if the asphalt is produced by replacing different crude oils, a sample is extracted again and the asphalt softening point calculation formula is fitted. That is, in the detection method provided by the present invention, when the replaced crude oil is different from the crude oil used for producing asphalt for fitting the asphalt softening point before, the sample database needs to be re-established and a new fitting asphalt softening point calculation formula needs to be fitted; if the same crude oil is adopted to produce the asphalt, the sample database and the fitted asphalt softening point calculation formula do not need to be repeatedly established.
The present invention calculates the softening point of asphalt by performing linear regression analysis on the specific gravity, temperature and softening point of an asphalt sample and fitting the results of such linear regression analysis into the form of a formula. The method provided by the invention only needs to carry out manual sampling and traditional softening point detection operation in the stage of fitting the asphalt softening point calculation formula, so that frequent manual operation is not needed, and the operation errors of various links such as human, equipment and environment can be effectively reduced and eliminated. Meanwhile, the specific gravity and temperature data of the finished asphalt product can be monitored online in real time in the production process of the asphalt, so that the method provided by the invention can calculate the corresponding softening point according to the specific gravity and temperature data of the asphalt monitored online in real time, thereby realizing the online monitoring of the softening point of the finished asphalt product in real time, providing online guidance for the continuous production of the asphalt, shortening the debugging working hours, improving the product qualification rate and the product quality, and having remarkable economic benefit.
For the sake of clarity, the following examples are provided for illustrative purposes.
Example 1
A mass flow meter is installed on an asphalt finished product output pipeline of an asphalt production enterprise, and a corresponding sampling port is arranged, so that the purpose of the sampling port is to prepare for taking a standard sample in the early stage and establish a basic database. After the database is established, when different crude oils are replaced, resampling and establishing the database are needed, and if the same crude oil is used, reference data do not need to be repeatedly established.
1. Installing a quality flow meter: the thermal mass flowmeter A is additionally arranged on an asphalt finished product output pipeline, the mass flowmeter is arranged on an external pipeline of the device, and the displayed specific gravity and temperature are transmitted to a communication data terminal for extraction on line.
2. Installing an asphalt sampling port: and a sampling port B is arranged and is arranged within 5 meters behind the flowmeter A.
3. And (3) standard data acquisition: establishing a basic database, drawing up 10 samples, and respectively recording the specific gravity and the temperature real-time numerical value displayed on the mass flowmeter A before sampling.
The softening point of the asphalt of 10 samples was detected by the softening point detection method in JTG E20-2011, as shown in Table 1:
asphalt specific gravity, asphalt temperature and softening point data for the 110 samples in Table
Specific gravity, temperature, softening point were recorded in an excel table using Matlab software to form three rowsAccording to, and are respectively named as X1、X2And Y are three series.
Since x has only two independent variables, namely specific gravity and temperature, the functional relationship used to fit the asphalt softening point calculation formula can be derived as:
y＝β0+β1x1+β2x2+β3x1 2+β4x1x2+β5x2 2formula (I);
in the formula (I), y is the softening point of the asphalt and x1Is specific gravity of asphalt, x2Is the temperature of the asphalt, beta0Is a constant term, β1、β2、β3、β4And beta5Are coefficients.
Finally, analyzing the data by Matlab software to obtain an asphalt softening point calculation formula:
y＝506190.032223855-953.589426300317×x1-632.586389608487×x2+0.598548690210378×x1×x2+0.448836255474366×x1 2+0.192058541790403×x2 2formula (II);
in the formula (II), y is the softening point of the asphalt and x1Is specific gravity of asphalt, x2Is the asphalt temperature.
4. And (3) evaluating the on-line monitoring accuracy of the softening point of the asphalt finished product: in the asphalt production process, asphalt specific gravity and temperature data in an asphalt finished product output pipeline are monitored, and an online monitoring numerical value of an asphalt softening point is calculated according to a formula (II). Then, the calculated values are compared with the corresponding measured softening point values of the finished asphalt products, and the results are shown in table 2:
TABLE 2 comparison table of calculated values and actual detection values in the method
As can be seen from Table 2, the difference between the calculated value and the measured value is less than 0.5, which indicates that the method has better accuracy.
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 (6)
1. A method for monitoring the softening point of asphalt comprises the following steps:
a) in the asphalt production process, monitoring the asphalt specific gravity and the asphalt temperature in an asphalt finished product output pipeline;
b) calculating to obtain an asphalt softening point according to the monitored asphalt specific gravity and asphalt temperature data and a pre-fitted asphalt softening point calculation formula;
the asphalt softening point calculation formula is obtained according to the following steps:
i) extracting a plurality of samples from an asphalt finished product output pipeline, recording the asphalt specific gravity and the asphalt temperature when each sample is extracted, and detecting the asphalt softening point of each sample;
ii) fitting to obtain an asphalt softening point calculation formula according to the asphalt specific gravity, the asphalt temperature and the asphalt softening point data of each sample obtained in the step i) by taking the asphalt specific gravity and the asphalt temperature as independent variables and the asphalt softening point as dependent variables;
the functional relation formula adopted for fitting the asphalt softening point calculation formula is as follows:
y＝β0+β1x1+β2x2+β3x1 2+β4x1x2+β5x2 2formula (I);
in the formula (I), y is the softening point of the asphalt and x1Is the specific gravity of asphalt, x2Is the temperature of the asphalt, beta0Is a constant term, β1、β2、β3、β4And beta5Are coefficients.
2. The method of claim 1, wherein the number of samples is greater than or equal to 10.
3. The method of claim 2, wherein the number of samples is greater than or equal to 50.
4. The monitoring method according to claim 1, wherein the asphalt specific gravity and the asphalt temperature are monitored by a quality flow meter provided on an asphalt finished product output pipeline.
5. The method of claim 1, wherein the sample is re-extracted and fitted to the asphalt softening point calculation formula if the asphalt is produced by a different crude oil during the asphalt production process.
6. The monitoring method according to any one of claims 1 to 5, wherein in step i), the method for detecting the softening point of the asphalt is a softening point detection method described in road engineering asphalt and asphalt mixture test protocol JTG E20-2011.
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|---|---|---|---|---|
| JP2001348485A (en) * | 2000-06-07 | 2001-12-18 | Nisshin Kogyo Co Ltd | Modified asphalt and manufacturing method therefor |
| CN101256162A (en) * | 2008-03-20 | 2008-09-03 | 山东省交通科学研究所 | Method for measuring natural ganoine bitumen softening point |
| CN101832994A (en) * | 2010-04-15 | 2010-09-15 | 同济大学 | Method for testing property of low-carbon asphalt and low-carbon asphalt mixtures |
| CN105784543A (en) * | 2016-05-25 | 2016-07-20 | 王壹帆 | Waste tire rubber powder asphalt separation test and evaluation method |
| CN106407628A (en) * | 2016-11-26 | 2017-02-15 | 何恺源 | Method and system for determining asphalt concoction scheme based on viscosity model |
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- 2019-11-11 CN CN201911093852.9A patent/CN110672463B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2001348485A (en) * | 2000-06-07 | 2001-12-18 | Nisshin Kogyo Co Ltd | Modified asphalt and manufacturing method therefor |
| CN101256162A (en) * | 2008-03-20 | 2008-09-03 | 山东省交通科学研究所 | Method for measuring natural ganoine bitumen softening point |
| CN101832994A (en) * | 2010-04-15 | 2010-09-15 | 同济大学 | Method for testing property of low-carbon asphalt and low-carbon asphalt mixtures |
| CN105784543A (en) * | 2016-05-25 | 2016-07-20 | 王壹帆 | Waste tire rubber powder asphalt separation test and evaluation method |
| CN106407628A (en) * | 2016-11-26 | 2017-02-15 | 何恺源 | Method and system for determining asphalt concoction scheme based on viscosity model |
Non-Patent Citations (1)
| Title |
|---|
| 沥青输送泵的选型计算;明文雪;《轻金属》;20070831;第35-39页 * |
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