Asphalt sampling equipment and method

Abstract

The invention provides asphalt sampling equipment and an asphalt sampling method. A filtering and sampling process is divided into a Newtonian characteristic sampling section and a non-Newtonian characteristic sampling section according to shear rate data of asphalt at an outlet of the sampling equipment; according to the corresponding subsequences of the shear rate data in the Newton characteristic sampling section, determining a pulsation interval during asphalt flow pulsation in the filtering and sampling process; collecting pressure data at the outlet of the sampling equipment in the non-Newtonian characteristic sampling section through a pressure sensor, and determining the thixotropic index of the asphalt in the filtering and sampling process according to the corresponding subsequences of the pressure data and the shear rate data in the non-Newtonian characteristic sampling section; and determining a closed-loop control model for constructing filtering sampling through the pulsation interval and the thixotropic index, and adjusting the filtering pressure in the non-Newtonian characteristic sampling section in real time based on the closed-loop control model so as to obtain an asphalt sample. By means of the scheme, the pressure in the filtering process can be adjusted according to the material characteristics of different kinds of asphalt.

Description

Technical Field

[0001] This application relates to the technical field of asphalt detection. More specifically, this application relates to an asphalt sampling device and method. Background Art

[0002] Asphalt is a kind of high-molecular organic viscous material, which is widely used in road engineering (such as asphalt concrete pavement), waterproof materials (such as waterproof coiled materials), construction (such as roof waterproofing) and other industrial uses. Asphalt sampling refers to obtaining a representative sample from asphalt materials for physical, chemical and rheological property tests. During the production, transportation and construction of asphalt, factors such as impurity pollution, temperature fluctuation, aging effect and flow non-uniformity may affect the test results. Therefore, mechanical filtration is a common means of asphalt sampling.

[0003] In the prior art, metal mesh or filter cloth is usually used to filter asphalt at the outlet of the sampling device. And due to the high viscosity of asphalt, external pressure is usually applied during the filtration process to accelerate the filtration process. However, asphalt is a typical pseudoplastic material. When the external pressure is applied too fast, the viscosity of asphalt increases, which instead leads to a slowdown in the asphalt filtration process. Moreover, the pseudoplasticity of different asphalts is also different. Therefore, how to adjust the pressure during the filtration process according to the material characteristics of different asphalts has become a difficult problem faced by the industry. Summary of the Invention

[0004] This application provides an asphalt sampling device and method, which can adjust the pressure during the filtration process according to the material characteristics of different asphalts.

[0005] In a first aspect, this application provides an asphalt sampling control method, including: Real-time collecting the shear rate data of asphalt at the outlet of the sampling device during the filtration sampling process through a rheological sensor; Dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time, where the Newtonian property sampling section refers to the time period when the rheological property of asphalt conforms to Newtonian property during the filtration sampling process, and the non-Newtonian property sampling section refers to the time period when the rheological property of asphalt does not conform to Newtonian property during the filtration sampling process; Determining the pulsation interval when the asphalt flow rate pulsates during the filtration sampling process according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section; Collecting the pressure data received at the outlet of the sampling device during the non-Newtonian property sampling section through a pressure sensor, determining the change characteristics of the apparent viscosity of asphalt during the filtration sampling process according to the pressure data and the pressure increasing rate, and determining the thixotropic index of asphalt during the filtration sampling process according to the change characteristics and the subsequence corresponding to the shear rate data in the non-Newtonian property sampling section; Construct a closed-loop control model for filtration sampling through the pulsation interval and the thixotropy index, and adjust the filtration pressure of the sampling device based on the closed-loop control model to obtain an asphalt sample.

[0006] In some embodiments, before the shear rate data of the asphalt at the outlet of the sampling device during the filtration sampling process is collected in real time by a rheological sensor, it further includes: Start the heating device in the sampling device to preheat the sampling device; After the preheating is completed, start the sampling device to filter the asphalt at a fixed pressurization rate.

[0007] In some embodiments, dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time specifically includes: Determine the correlation characteristics of the shear rate data in time; Identify the critical point where the flow characteristics of the asphalt change according to the correlation characteristics; Determine the critical shear stress of the asphalt according to the critical point; Divide the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section based on the critical shear stress.

[0008] In some embodiments, determining the pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section specifically includes: Extract the Newtonian property subsequence from the shear rate data according to the Newtonian property sampling section; Determine the flow rate sequence according to the Newtonian property subsequence and the pipe radius at the outlet of the sampling device; Perform a flow rate pulsation analysis on the flow rate sequence to obtain the pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process.

[0009] In some embodiments, determining the change characteristics of the apparent viscosity of the asphalt in the filtration sampling process according to the pressure data and the pressurization rate specifically includes: Determine the pressure difference sequence of the asphalt in the non-Newtonian property sampling section according to the pressure data and the pressurization rate; Determine the change characteristics of the apparent viscosity of the asphalt in the filtration sampling process according to the pressure difference sequence.

[0010] In some embodiments, constructing a closed-loop control model for filtration sampling through the pulsation interval and the thixotropy index specifically includes: Determine the pulsation amplitude of the pulsation interval; Determine the blocking effect value of the asphalt according to the pulsation amplitude and the thixotropic coefficient; Determine the closed-loop control model for filtration sampling according to the blocking effect value.

[0011] In some embodiments, the asphalt is filtered and sampled by a pneumatic booster pump at a fixed boosting rate.

[0012] In a second aspect, the present application provides an asphalt sampling device, including an asphalt sampling control unit, and the asphalt sampling control unit includes: An acquisition module, configured to collect, in real time through a rheological sensor, the shear rate data of the asphalt at the outlet of the sampling device during the filtration sampling process; A processing module, configured to divide the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in terms of time, where the Newtonian property sampling section refers to the period during the filtration sampling process when the rheological properties of the asphalt conform to Newtonian properties, and the non-Newtonian property sampling section refers to the period during the filtration sampling process when the rheological properties of the asphalt do not conform to Newtonian properties; The processing module is further configured to determine the pulsation interval when the asphalt flow pulsates during the filtration sampling process according to the subsequence corresponding to the Newtonian property sampling section in the shear rate data; The processing module is further configured to collect the pressure data received at the outlet of the sampling device during the non-Newtonian property sampling section through a pressure sensor, determine the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process according to the pressure data and the boosting rate, and determine the thixotropic index of the asphalt during the filtration sampling process according to the change characteristics and the subsequence corresponding to the non-Newtonian property sampling section in the shear rate data; An execution module, configured to construct a closed-loop control model for filtration sampling through the pulsation interval and the thixotropic index, and adjust the filtration pressure of the sampling device based on the closed-loop control model, so as to obtain an asphalt sample.

[0013] In a third aspect, the present application provides a computer device, which includes a memory and a processor, the memory stores a code, and the processor is configured to obtain the code and execute the above-mentioned asphalt sampling control method.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the above-mentioned asphalt sampling control method is implemented.

[0015] The technical solutions provided by the disclosed embodiments of the present application have the following beneficial effects: In the asphalt sampling equipment and method provided by the present application, first, a rheological sensor is used to collect in real time the shear rate data of the asphalt at the outlet of the sampling equipment during the filtration sampling process; the filtration sampling process is divided into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in terms of time; the pulsation interval during the asphalt flow pulsation in the filtration sampling process is determined according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section; the pressure data received at the outlet of the sampling equipment during the non-Newtonian property sampling section is collected by a pressure sensor, and the change characteristics of the asphalt apparent viscosity during the filtration sampling process are determined according to the pressure data and the pressure increase rate. Based on the change characteristics and the subsequence corresponding to the shear rate data in the non-Newtonian property sampling section, the thixotropic index of the asphalt during the filtration sampling process is determined; a closed-loop control model for filtration sampling is constructed through the pulsation interval and the thixotropic index, and the filtration pressure of the sampling equipment is adjusted based on the closed-loop control model, thereby obtaining an asphalt sample.

[0016] It can be seen that in the present application, filtration is carried out at a fixed pressure increase rate. When the asphalt is flowing normally (i.e., conforming to the characteristics of Newtonian fluid), the pulsation interval during the asphalt flow pulsation is determined, which is to determine the flow condition of the asphalt under low shear stress. Subsequently, when the flow of the asphalt does not conform to the characteristics of Newtonian fluid (i.e., the Newtonian property sampling section), the thixotropy (i.e., the thixotropic index) of the asphalt is analyzed through the pressure difference between the upper and lower parts of the asphalt (i.e., through the pressure data received at the outlet of the sampling equipment and the pressure increase rate). Finally, a closed-loop control system is constructed based on the thixotropic index and the pulsation interval, and the pressure during the subsequent filtration process is controlled based on the closed-loop control system. In summary, the present application can adjust the pressure during the filtration process according to the material characteristics of different asphalts. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is an exemplary flowchart of an asphalt sampling control method shown according to some embodiments of the present application; Figure 2 is a schematic mechanical structure diagram of a sampling equipment shown according to some embodiments of the present application; Figure 3 is an exemplary flowchart of determining the pulsation interval shown according to some embodiments of the present application; Figure 4 is a schematic structure diagram of an asphalt sampling control unit shown according to some embodiments of the present application; Figure 5 is a schematic structure diagram of a computer device for implementing the asphalt sampling control method shown according to some embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To better understand the technical solution of the present application, the technical solution of the present application will be described in detail below in conjunction with the accompanying drawings of the specification and specific embodiments.

[0019] Referring to Figure 1 , this figure is an exemplary flowchart of an asphalt sampling control method shown in some embodiments of the present application. The asphalt sampling control method 100 mainly includes the following steps: In step 101, the shear rate data of the asphalt at the outlet of the sampling device during the filtration sampling process is collected in real time through a rheological sensor.

[0020] In some embodiments, referring to Figure 2 , this figure is a schematic mechanical structure diagram of a sampling device shown in some embodiments of the present application, including: A pressurizing device for providing pressure during the filtration sampling process; A feed pipe for introducing asphalt from a heating tank; A heating device for heating the filtration chamber; A filtration chamber, where the filter contains a filtration medium for filtering asphalt; A rheological sensor for collecting the shear rate of the asphalt at the outlet of the sampling device; A pressure sensor for collecting the pressure value received at the outlet of the sampling device.

[0021] In some embodiments, before collecting the shear rate data of the asphalt at the outlet of the sampling device in real time through a rheological sensor, it further includes: Starting the heating device in the sampling device to preheat the sampling device; After the preheating is completed, starting the sampling device to filter the asphalt at a fixed pressurization rate.

[0022] Specifically, starting the heating device in the sampling device to preheat the sampling device can be achieved in the following manner, that is: starting the heating device in the sampling device to heat the filtration chamber of the sampling device to a predetermined temperature, where the predetermined temperature can be preset according to actual needs. For example, in the present application, the predetermined temperature is set to 150°C. Those skilled in the art know that the predetermined temperature can also be set to other temperatures between 100 and 200°C, all of which fall within the protection scope of the present application and will not be elaborated here.

[0023] In specific implementation, after the preheating is completed, starting the sampling device to filter the asphalt at a fixed pressurization rate can be achieved by the following method, that is: after the preheating is completed, guiding the asphalt in the heating tank into the filtering cavity of the sampling device, and starting the pressurization device in the sampling device to pressurize at a fixed pressurization rate, where the pressurization rate can be set according to actual needs. For example, in this application, the pressurization rate is set to 0.1 MPa / min.

[0024] It should be noted that in this application, the pressurization device is a pneumatic booster pump.

[0025] In specific implementation, collecting the shear rate data of the asphalt at the outlet of the sampling device in real time during the filtering and sampling process by a rheological sensor can be achieved by the following method, that is: installing the rheological sensor at the outlet of the sampling device, collecting the shear rate of the asphalt at the outlet of the sampling device by the rheological sensor at a predetermined sampling interval, arranging all the collected shear rates in the order of sampling, and finally, taking the arranged sequence as the shear rate data of the asphalt at the outlet of the sampling device, where the sampling interval can be preset according to actual needs. For example, in this application, the sampling interval is preset to 1 second.

[0026] In step 102, the filtering and sampling process is divided into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time, where the Newtonian property sampling section refers to the time period when the rheological properties of the asphalt conform to Newtonian properties during the filtering and sampling process, and the non-Newtonian property sampling section refers to the time period when the rheological properties of the asphalt do not conform to Newtonian properties during the filtering and sampling process.

[0027] In some embodiments, dividing the filtering and sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time can be achieved by the following steps: Determine the correlation characteristics of the shear rate data in time; Identify the critical point where the flow characteristics of the asphalt change according to the correlation characteristics; Determine the critical shear stress of the asphalt according to the critical point; Divide the filtering and sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section based on the critical shear stress.

[0028] In specific implementation, the correlation feature of the shear rate data in terms of time can be implemented in the following manner: First, calculate the autocorrelation coefficients of the shear rate data at different lag times. Then, arrange all the autocorrelation coefficients in ascending order according to the lag times. Finally, use the arranged sequence as the correlation feature of the shear rate data in terms of time, where the lag time takes all integers between 1 and N, and N is the length of the shear rate data.

[0029] It should be noted that in this application, the correlation feature is a sequence describing the autocorrelation intensity of the shear rate data at different lag times.

[0030] In specific implementation, the critical point at which the flow characteristics of the asphalt change can be identified according to the correlation feature in the following manner: Compare all the autocorrelation coefficients in the correlation feature with a preset correlation threshold in sequence, and take the product of the lag time corresponding to the first autocorrelation coefficient less than the correlation threshold and the sampling interval when collecting the shear rate data as the critical point at which the flow characteristics of the asphalt change.

[0031] It should be noted that in this application, the critical point is the time point at which the flow characteristics of the asphalt start to change significantly (i.e., the change between Newtonian characteristics and non-Newtonian characteristics).

[0032] In specific implementation, the critical shear stress of the asphalt can be determined according to the critical point in the following manner: First, obtain the pressure value applied by the pressurizing device at the critical point of the sampling device and the pressure value received at the outlet of the sampling device at the critical point. Then, take the difference between the pressure value applied by the pressurizing device at the critical point of the sampling device and the pressure value received at the outlet of the sampling device at the critical point as the pressure difference. Then, convert this pressure difference into shear stress according to the Newtonian fluid model, that is, multiply this pressure difference by the pipe radius at the outlet of the sampling device and divide it by twice the pipe length at the outlet of the sampling device, and take the obtained value as the shear stress. Finally, take this shear stress as the critical shear stress of the asphalt, where the pressurizing device works at a fixed pressurizing rate, so the pressure value applied by the pressurizing device at the critical point of the sampling device can be directly obtained. In addition, the pressure value received at the outlet of the sampling device at the critical point can be collected by a pressure sensor installed at the outlet of the sampling device.

[0033] It should be noted that in this application, the critical shear stress is the shear stress received when the flow characteristics of the asphalt change significantly (i.e., the change between Newtonian characteristics and non-Newtonian characteristics).

[0034] In specific implementation, dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section based on the critical shear stress can be achieved in the following manner: First, the pressure sensor installed at the outlet of the sampling device collects the pressure value at the outlet of the sampling device at the same sampling interval as when collecting the shear rate data, and subtracts the pressure value applied by the pressure boosting device of the sampling device from each collected pressure value. Subsequently, all the differences are converted into shear stress through the Newtonian fluid model, that is, each difference is multiplied by the pipe radius at the outlet of the sampling device and then divided by twice the pipe length at the outlet of the sampling device. Then, all the obtained shear stresses are compared with the critical shear stress respectively. The time period composed of all shear stresses less than or equal to the critical shear stress is used as the Newtonian property sampling section, and the time period composed of all shear stresses greater than the critical shear stress is used as the non-Newtonian property sampling section.

[0035] It should be noted that in this application, the Newtonian property sampling section refers to the time period when the rheological properties of the asphalt in the sampling device conform to the Newtonian properties, and the non-Newtonian property sampling section refers to the time period when the rheological properties of the asphalt in the sampling device do not conform to the Newtonian properties.

[0036] In step 103, the pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process is determined according to the subsequence corresponding to the shear rate data within the Newtonian property sampling section.

[0037] In some embodiments, referring to Figure 3 , this figure is an exemplary flowchart for determining the pulsation interval according to some embodiments of this application. The pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process can be determined according to the subsequence corresponding to the shear rate data within the Newtonian property sampling section in the following steps: In step 1031, a Newtonian property subsequence is intercepted from the shear rate data according to the Newtonian property sampling section; In step 1032, a flow rate sequence is determined according to the Newtonian property subsequence and the pipe radius at the outlet of the sampling device; In step 1033, a flow rate pulsation analysis is performed on the flow rate sequence to obtain the pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process.

[0038] In specific implementation, intercepting a Newtonian property subsequence from the shear rate data according to the Newtonian property sampling section can be achieved in the following manner: The subsequence within the Newtonian property sampling section in the shear rate data is extracted, and the extracted subsequence is used as the Newtonian property subsequence.

[0039] It should be noted that in this application, the Newtonian property subsequence refers to the shear rate data within the Newtonian property sampling section.

[0040] When specifically implemented, the flow rate sequence can be determined according to the Newtonian characteristic subsequence and the pipe radius at the outlet of the sampling device in the following way, that is: First, convert each shear rate in the Newtonian characteristic subsequence into the corresponding hydrodynamic viscosity through the constitutive equation of Newtonian fluid. Subsequently, combine the hydrodynamic viscosity with the pipe radius at the outlet of the sampling device through the Hagen-Poiseuille formula to convert each hydrodynamic viscosity into the corresponding flow rate value. For example, first multiply each shear rate by the cube of the pipe radius and then multiply by one-fourth of pi, and take the obtained values as the flow rate values corresponding to each shear rate respectively. Then, arrange all the obtained flow rate values in the chronological order of the corresponding shear rate. Finally, take the arranged sequence as the flow rate sequence.

[0041] It should be noted that in this application, the flow rate sequence is a sequence describing the change of asphalt flow rate at the outlet of the sampling device.

[0042] When specifically implemented, the pulsation interval of the asphalt flow rate during the filtering sampling process can be obtained by performing a flow rate pulsation analysis on the flow rate sequence in the following way, that is: First, calculate the average value of the flow rate sequence. Then, calculate the standard deviation of the flow rate sequence, and take the sum of the average value and the standard deviation as the upper limit of the interval, and take the difference between the average value and the standard deviation as the lower limit of the interval. Finally, take the interval composed of the upper limit and the lower limit of the interval as the pulsation interval of the asphalt flow rate during the filtering sampling process.

[0043] It should be noted that in this application, the pulsation interval refers to the range of deviation of the asphalt flow rate during the filtering sampling process.

[0044] In step 104, the pressure data received at the outlet of the sampling device in the non-Newtonian characteristic sampling section is collected through a pressure sensor. According to the pressure data and the pressure increase rate, the change characteristics of the asphalt apparent viscosity during the filtering sampling process are determined. Based on the change characteristics and the corresponding subsequence of the shear rate data in the non-Newtonian characteristic sampling section, the thixotropic index of the asphalt during the filtering sampling process is determined.

[0045] When specifically implemented, the pressure data received at the outlet of the sampling device in the non-Newtonian characteristic sampling section can be collected through a pressure sensor in the following way, that is: First, install the pressure sensor at the outlet of the sampling device in the sampling device. Then, through the pressure sensor, collect the pressure values received at the outlet of the sampling device at the same sampling interval as when collecting the shear rate data. Subsequently, arrange all the pressure values in the chronological order of sampling, and intercept the subsequence within the non-Newtonian characteristic sampling section from the arranged sequence. Finally, take the intercepted subsequence as the pressure data received at the outlet of the sampling device in the non-Newtonian characteristic sampling section.

[0046] In some embodiments, the following steps may be adopted to determine the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process based on the pressure data and the pressure increase rate: Determine the pressure difference sequence of the asphalt within the non-Newtonian property sampling section based on the pressure data and the pressure increase rate; Determine the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process based on the pressure difference sequence.

[0047] Specifically, when implemented, the determination of the pressure difference sequence of the asphalt within the non-Newtonian property sampling section based on the pressure data and the pressure increase rate may be achieved in the following manner, that is: First, obtain the sampling time of each pressure value in the pressure data, calculate the pressure value applied by the pressure increasing device in the sampling device according to the pressure increase rate, then, subtract each pressure value in each pressure data from the pressure value applied by the pressure increasing device at the same sampling time, and arrange all the differences in the order of the sampling time, and take the arranged sequence as the pressure difference sequence of the asphalt within the non-Newtonian property sampling section.

[0048] It should be noted that in this application, the pressure difference sequence is a sequence describing the pressure difference between the upper and lower surfaces of the asphalt within the non-Newtonian property sampling section.

[0049] Specifically, when implemented, the determination of the change characteristics of the apparent viscosity of the asphalt within the non-Newtonian property sampling section based on the pressure difference sequence may be achieved in the following manner, that is: Calculate the variance of the pressure difference sequence, and take this variance as the change characteristics of the apparent viscosity of the asphalt within the non-Newtonian property sampling section.

[0050] It should be noted that in this application, the change characteristics are parameter values for measuring the degree of chaos of the change in the apparent viscosity of the asphalt within the non-Newtonian property sampling section.

[0051] In some embodiments, the following steps may be adopted to determine the thixotropic index of the asphalt during the filtration sampling process based on the change characteristics and the subsequence corresponding to the shear rate data within the non-Newtonian property sampling section: Fit the thixotropic curve of the asphalt during the filtration sampling process based on the change characteristics and the subsequence corresponding to the shear rate data within the non-Newtonian property sampling section; Determine the thixotropic index of the asphalt during the filtration sampling process based on the thixotropic curve.

[0052] In specific implementation, the thixotropic curve of the asphalt during the filtered sampling process can be fitted according to the change characteristics and the subsequence corresponding to the shear rate data within the non-Newtonian characteristic sampling section in the following manner: That is, the subsequence corresponding to the shear rate data within the non-Newtonian characteristic sampling section is fitted according to the power-law model by the least squares method in the prior art, where the independent variable is time and the dependent variable is the shear rate, and the change characteristics are used as the convergence condition in the least squares algorithm, that is, when the difference in the power-law exponents in the power-law model is less than the change characteristics in two consecutive iterations of the least squares method, the iteration is terminated. Finally, the curve obtained by fitting is used as the thixotropic curve of the asphalt during the filtered sampling process.

[0053] It should be noted that in this application, the thixotropic curve is a curve reflecting the change and recovery process of the rheological properties of asphalt under the action of external shear force.

[0054] In specific implementation, the thixotropic index of the asphalt during the filtered sampling process can be determined according to the thixotropic curve in the following manner: First, the thixotropic curve is divided into the curve within the Newtonian characteristic sampling section and the curve within the non-Newtonian characteristic sampling section, and the definite integrals of the curves within the Newtonian characteristic sampling section and the non-Newtonian characteristic sampling section are calculated respectively, and the difference between the two obtained definite integrals is used as the thixotropic index of the asphalt during the filtered sampling process.

[0055] It should be noted that in this application, the thixotropic index is a parameter for measuring the thixotropy of asphalt. The larger the thixotropic index, the greater the thixotropy of asphalt, and the smaller the thixotropic index, the smaller the thixotropy of asphalt.

[0056] In step 105, a closed-loop control model for filtered sampling is constructed through the pulsation interval and the thixotropic index, and the filtration pressure of the sampling device is adjusted based on the closed-loop control model, and then an asphalt sample is obtained.

[0057] In some embodiments, the construction of the closed-loop control model for filtered sampling through the pulsation interval and the thixotropic index can be achieved by the following steps: Determine the pulsation amplitude of the pulsation interval; Determine the blocking effect value of the asphalt according to the pulsation amplitude and the thixotropic coefficient; Determine the closed-loop control model for filtered sampling according to the blocking effect value.

[0058] In specific implementation, the pulsation amplitude of the pulsation interval can be determined in the following manner: That is, the difference between the upper limit and the lower limit of the pulsation interval is used as the pulsation amplitude.

[0059] In specific implementation, to determine the blocking effect value of asphalt according to the pulsation amplitude and the thixotropic coefficient, the following method can be adopted, that is: the value obtained by adding the pulsation amplitude and the thixotropic coefficient is used as the blocking effect value of asphalt.

[0060] It should be noted that in this application, the blocking effect value is a parameter value for measuring the possibility of asphalt blocking during the filtration sampling process. The pulsation amplitude reflects the fluctuation of the pressure or shear rate in the system. These fluctuations may cause local high pressure or flow rate changes, thereby promoting the formation of blockages due to solid particles or structural changes. The thixotropic coefficient describes the dynamic characteristics of the structural destruction and reorganization of asphalt under shear. A higher thixotropic coefficient means that the material is more likely to quickly recover a higher viscosity or form a network structure after shear, and is also likely to cause blockages. Therefore, the sum of the pulsation amplitude and the thixotropic coefficient can be used as the blocking effect value to measure the possibility of asphalt blocking during filtration.

[0061] In specific implementation, to adjust the filtration pressure of the sampling device based on the closed-loop control model and then obtain an asphalt sample, the following method can be adopted, that is: input the blocking effect value into the closed-loop control model, and use the output of the closed-loop control model as the filtration pressure of the sampling device. Finally, the asphalt obtained by filtration sampling is used as the asphalt sample.

[0062] In specific implementation, to determine the closed-loop control model for filtration sampling according to the blocking effect value, the following method can be adopted, that is: determine the closed-loop control system through fuzzy PID control in the prior art, and use this closed-loop control system as the closed-loop control model. Among them, the blocking effect value is used as the input of the closed-loop control system, and the pressure value applied by the booster device in the sampling device is used as the output. The standard value of the blocking effect value in the closed-loop control system can be set according to actual needs. For example, in this application, the standard value of the blocking effect value is set to 0.4.

[0063] In addition, on the other hand of this application, in some embodiments, this application provides an asphalt sampling device, which includes an asphalt sampling control unit. Refer to Figure 4 , this figure is a schematic structural diagram of the asphalt sampling control unit shown in some embodiments of this application. The asphalt sampling control unit 400 includes: a collection module 401, a processing module 402, and an execution module 403, which are described as follows: The collection module 401. In this application, the collection module 401 is mainly used to collect the shear rate data of the asphalt at the outlet of the sampling device in real time during the filtration sampling process through a rheological sensor; Processing module 402. In this application, the processing module 402 is mainly used to divide the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data over time. Among them, the Newtonian property sampling section refers to the time period during the filtration sampling process when the rheological properties of the asphalt conform to Newtonian properties, and the non-Newtonian property sampling section refers to the time period during the filtration sampling process when the rheological properties of the asphalt do not conform to Newtonian properties; It should be noted that in this application, the processing module 402 is also used to determine the pulsation interval during the pulsation of the asphalt flow rate in the filtration sampling process according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section; It should be noted that in this application, the processing module 402 is also used to collect the pressure data at the outlet of the sampling device in the non-Newtonian property sampling section through a pressure sensor, determine the change characteristics of the apparent viscosity of the asphalt in the filtration sampling process according to the pressure data and the pressure increase rate, and determine the thixotropic index of the asphalt in the filtration sampling process according to the change characteristics and the subsequence corresponding to the shear rate data in the non-Newtonian property sampling section; Execution module 403. In this application, the execution module 403 is mainly used to construct a closed-loop control model for filtration sampling through the pulsation interval and the thixotropic index, and adjust the filtration pressure of the sampling device based on the closed-loop control model, so as to obtain an asphalt sample.

[0064] In addition, this application also provides a computer device, which includes a memory and a processor. The memory stores code, and the processor is configured to obtain the code and execute the above asphalt sampling control method.

[0065] In some embodiments, refer to Figure 5 , this figure is a schematic structural diagram of a computer device for implementing the asphalt sampling control method according to some embodiments of this application. The asphalt sampling control method in the above embodiments can be implemented by Figure 5 The computer device shown. The computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0066] The processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0067] The communication bus 502 can be used to transmit information between the above components.

[0068] The memory 503 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compact discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk or other magnetic storage devices, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 503 can exist independently and be connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0069] Among them, the memory 503 is used to store the program code for executing the solution of this application and is controlled by the processor 501 to execute. The processor 501 is used to execute the program code stored in the memory 503. The program code can include one or more software modules. The asphalt sampling control method in the above embodiments can be implemented by one or more software modules in the program code in the processor 501 and the memory 503.

[0070] The communication interface 504 uses any device such as a transceiver to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0071] In a specific implementation, as an embodiment, the computer device can include multiple processors, and each of these processors can be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, the processor can refer to one or more devices, circuits, and / or processing cores for processing data (such as computer program instructions).

[0072] The computer device described above can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0073] In addition, the present application also provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the above asphalt sampling control method is implemented.

[0074] In summary, in the asphalt sampling device and method disclosed in the embodiments of the present application, first, the shear rate data of the asphalt at the outlet of the sampling device during the filtration sampling process is collected in real time through a rheological sensor; the filtration sampling process is divided into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in terms of time; the pulsation interval when the asphalt flow rate pulsates during the filtration sampling process is determined according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section; the pressure data received at the outlet of the sampling device during the non-Newtonian property sampling section is collected through a pressure sensor, and the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process are determined according to the pressure data and the pressure increase rate. Based on the change characteristics and the subsequence corresponding to the shear rate data in the non-Newtonian property sampling section, the thixotropic index of the asphalt during the filtration sampling process is determined; a closed-loop control model for filtration sampling is constructed through the pulsation interval and the thixotropic index, and the filtration pressure of the sampling device is adjusted based on the closed-loop control model, thereby obtaining an asphalt sample.

[0075] It can be seen that the present application performs filtration at a fixed pressure increase rate, and determines the pulsation interval when the asphalt flow rate pulsates when the asphalt is flowing normally (i.e., conforms to the Newtonian fluid property), that is, determines the flow condition of the asphalt under low shear stress. Subsequently, when the flow of the asphalt does not conform to the Newtonian fluid property (i.e., the Newtonian property sampling section), the thixotropy (i.e., the thixotropic index) of the asphalt is analyzed through the pressure difference between the upper and lower parts of the asphalt (i.e., through the pressure data received at the outlet of the sampling device and the pressure increase rate). Finally, a closed-loop control system is constructed according to the thixotropic index and the pulsation interval, and the pressure control is performed on the subsequent filtration process based on the closed-loop control system. In summary, the present application can adjust the pressure during the filtration process according to the material properties of different asphalts.

[0076] Although the preferred embodiments of the present application have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present application.

[0077] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A method for controlling asphalt sampling, which filters and samples asphalt by a sampling device at a fixed pressurization rate, is characterized in that, The method includes: Collecting shear rate data of asphalt at the outlet of the sampling device during the filtration sampling process through a rheological sensor; Dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time, where the Newtonian property sampling section refers to the time period when the rheological properties of asphalt conform to Newtonian properties during the filtration sampling process, and the non-Newtonian property sampling section refers to the time period when the rheological properties of asphalt do not conform to Newtonian properties during the filtration sampling process; Determining the pulsation interval during the pulsation of the asphalt flow rate during the filtration sampling process according to the subsequence corresponding to the Newtonian property sampling section in the shear rate data; Collecting pressure data received at the outlet of the sampling device during the non-Newtonian property sampling section through a pressure sensor, determining the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process according to the pressure data and the pressure increase rate, and determining the thixotropic index of the asphalt during the filtration sampling process based on the change characteristics and the subsequence corresponding to the non-Newtonian property sampling section in the shear rate data; Constructing a closed-loop control model for filtration sampling through the pulsation interval and the thixotropic index, and adjusting the filtration pressure of the sampling device based on the closed-loop control model to obtain an asphalt sample.

2. The method according to claim 1, wherein Before collecting the shear rate data of asphalt at the outlet of the sampling device in real time through a rheological sensor during the filtration sampling process, it further includes: Starting the heating device in the sampling device to preheat the sampling device; After the preheating is completed, starting the sampling device to filter the asphalt at a fixed pressure increase rate.

3. The method according to claim 1, characterized in that, Specifically, dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in time includes: Determining the correlation characteristics of the shear rate data in time; Identifying the critical point where the flow characteristics of asphalt change according to the correlation characteristics; Determining the critical shear stress of the asphalt according to the critical point; Dividing the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section based on the critical shear stress.

4. The method according to claim 1, wherein Specifically, determining the pulsation interval during the pulsation of the asphalt flow rate during the filtration sampling process according to the subsequence corresponding to the Newtonian property sampling section in the shear rate data includes: Intercepting the Newtonian property subsequence from the shear rate data according to the Newtonian property sampling section; Determining the flow rate sequence according to the Newtonian property subsequence and the pipe radius at the outlet of the sampling device; Performing flow rate pulsation analysis on the flow rate sequence to obtain the pulsation interval during the pulsation of the asphalt flow rate during the filtration sampling process.

5. The method according to claim 1, wherein Specifically, determining the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process according to the pressure data and the pressure increase rate includes: Determining the pressure difference sequence of the asphalt during the non-Newtonian property sampling section according to the pressure data and the pressure increase rate; Determining the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process according to the pressure difference sequence.

6. The method according to claim 1, wherein Specifically, constructing a closed-loop control model for filtration sampling through the pulsation interval and the thixotropic index includes: Determining the pulsation amplitude of the pulsation interval; Determine the blocking effect value of the asphalt according to the pulsation amplitude and the thixotropic coefficient; Determine the closed-loop control model for filtration sampling according to the blocking effect value.

7. The method according to claim 1, characterized in that, Filter and sample the asphalt through a pneumatic booster pump at a fixed boosting rate.

8. An asphalt sampling device, comprising an asphalt sampling control unit, characterized in that, The asphalt sampling control unit includes: An acquisition module, configured to collect, through a rheological sensor, the shear rate data of the asphalt at the outlet of the sampling device in real time during the filtration sampling process; A processing module, configured to divide the filtration sampling process into a Newtonian property sampling section and a non-Newtonian property sampling section according to the correlation characteristics of the shear rate data in terms of time, where the Newtonian property sampling section refers to the period during the filtration sampling process when the rheological properties of the asphalt conform to Newtonian properties, and the non-Newtonian property sampling section refers to the period during the filtration sampling process when the rheological properties of the asphalt do not conform to Newtonian properties; The processing module is further configured to determine the pulsation interval during the pulsation of the asphalt flow rate during the filtration sampling process according to the subsequence corresponding to the shear rate data in the Newtonian property sampling section; The processing module is further configured to collect, through a pressure sensor, the pressure data received at the outlet of the sampling device in the non-Newtonian property sampling section, determine the change characteristics of the apparent viscosity of the asphalt during the filtration sampling process according to the pressure data and the boosting rate, and determine the thixotropic index of the asphalt during the filtration sampling process based on the change characteristics and the subsequence corresponding to the shear rate data in the non-Newtonian property sampling section; An execution module, configured to construct a closed-loop control model for filtration sampling through the pulsation interval and the thixotropic index, and adjust the filtration pressure of the sampling device based on the closed-loop control model, so as to obtain an asphalt sample.

9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory stores code, and the processor is configured to obtain the code and execute the asphalt sampling control method according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the asphalt sampling control method according to any one of claims 1 to 7.

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