CN112881463A - Method for visually processing temperature change of liquid in container - Google Patents
Method for visually processing temperature change of liquid in container Download PDFInfo
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- CN112881463A CN112881463A CN202110066262.8A CN202110066262A CN112881463A CN 112881463 A CN112881463 A CN 112881463A CN 202110066262 A CN202110066262 A CN 202110066262A CN 112881463 A CN112881463 A CN 112881463A
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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
- G01N25/20—Investigating or analyzing materials by the use of thermal means by investigating the development of heat, i.e. calorimetry, e.g. by measuring specific heat, by measuring thermal conductivity
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K7/00—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements
- G01K7/02—Measuring temperature based on the use of electric or magnetic elements directly sensitive to heat ; Power supply therefor, e.g. using thermoelectric elements using thermoelectric elements, e.g. thermocouples
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Abstract
The invention discloses a visual processing method for liquid temperature change in a container, which comprises the steps of firstly measuring and collecting the liquid temperature at each measuring point in the container in the temperature change process through a thermocouple group in the container, then carrying out temperature interpolation on positions without measuring points in the overall movement direction of the liquid by using a proximity substitution method, then converting the whole area in the container into a refined temperature grid by using a Green spline interpolation method, obtaining a corresponding temperature distribution cloud picture at the moment by filling the refined temperature grid in a gradual change color, and finally making a series of temperature cloud pictures into dynamic cloud pictures according to a time sequence. According to the temperature change characteristic of the liquid in the container, the invention accurately reduces the temperature value of the position without measuring points in the whole movement direction of the liquid by using the proximity substitution method, the reduction precision is high, on the basis, the whole temperature distribution is determined by the Green spline interpolation method, the temperature dynamic cloud chart of the whole process is manufactured, and the temperature change process of the liquid in the container is integrally and continuously presented.
Description
Technical Field
The invention relates to the field of research on temperature distribution of liquid in a container, and particularly provides a visualized processing method for temperature change of liquid in the container based on a proximity substitution method and a Greens spline interpolation method.
Background
With the continuous and rapid development of economy in China, the problem of energy supply tension is increasingly prominent, and energy conservation, emission reduction and consumption reduction become necessary requirements for the development of economy and society in China. The heat accumulation/cold water tank is widely applied to the thermoelectric decoupling direction as heat accumulation/cold equipment at abroad, and the heat accumulation/cold water tank of the thermocline is not realized in a large range in a thermal power plant in China because the domestic technology starts late.
The principle of the thermocline heat storage/cooling tank is that the cold medium and the hot medium are stored in one tank body through the processes of heat storage/cooling and heat release/cooling by utilizing the density difference of the cold medium and the hot medium. In the processes of heat accumulation/cold accumulation and heat release/cold accumulation, a cold medium and a hot medium are contacted to form a temperature transition region, the temperature transition region is called a thermocline, the cold medium is positioned at the lower part of the thermocline, and the hot medium is positioned at the upper part of the thermocline. The temperature of the cold and hot medium can be basically kept unchanged under the condition that the heat preservation performance of the tank body is good, and the heat supply/cold demand is met.
Therefore, when the influence of various factors on the heat storage/release/cooling process is experimentally researched, the accurate determination of the temperature change of the liquid in the tank body is very important for the research; and the whole temperature distribution in the experimental process tank is made into a dynamic cloud picture, experimental data is processed in a visual mode, and the whole temperature change condition in the tank body in the experimental process is restored visually, so that the dynamic cloud picture has extremely high reference and guidance effects on experimental mechanism research and numerical simulation research.
The existing data processing method has at least the following disadvantages:
1. due to the limitation of the prior art, the thermocouple measuring points in the heat storage tank body cannot be arranged tightly enough, and the direct interpolation method cannot accurately restore the liquid temperature value at the position without the measuring points in the tank body through the limited temperature measuring points.
2. The temperature values measured by the radial or axial measuring points are made into a curve chart, the temperature change conditions of the radial or axial measuring points can be only compared, all data cannot be integrally processed, and the temperature change condition in the tank body in the experimental process cannot be visually observed
Therefore, it is a problem to be solved to find an experimental data processing method to accurately reduce the temperature of the position without measuring points in the heat storage/release/cooling process and to visually and integrally present the experimental process.
Disclosure of Invention
In order to overcome the problems of the prior art and the prior art, the invention aims to provide a visualized processing method for the temperature change of the liquid in the container, so as to realize visualized processing of the whole experimental data in the heat storage/release/cooling process and visually and integrally present the experimental process.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for visualizing the temperature change of liquid in a container comprises the following steps:
s1: arranging a thermocouple in the container, and connecting the thermocouple with a temperature acquisition system;
s2: starting a temperature acquisition system, monitoring temperature values measured by all thermocouples, and removing abnormal thermocouples;
s3: under the condition of S2, calculating the deviation of the temperature values measured by the thermocouples at all temperatures, and compensating each difference value to the corresponding measuring point to ensure that the errors of the temperature values measured by all the thermocouples are within an allowable range;
s4: measuring and recording the temperature value measured by a thermocouple in the container at high frequency;
s5: selecting all temperature values at a certain moment as a group from the beginning of the temperature change process;
s6: carrying out temperature interpolation on the non-thermocouple measuring point by using a proximity substitution method;
s7: on the basis of the step S6, converting the whole temperature change area into a refined temperature grid by utilizing a Green spline interpolation method;
s8: filling the refined temperature grid with gradient color changing along with temperature to form a temperature distribution cloud picture of the inner area of the container at corresponding time in the temperature change process;
s9: selecting all temperature values at the next moment as a group, and finishing the process from the step S6 to the step S8;
s10: repeating the step S9 until the temperature change process is finished to obtain the temperature distribution cloud pictures of the inner area of the container at all times;
s11: and converting the temperature distribution cloud pictures of the whole area in the container at all the moments into the process whole temperature distribution dynamic cloud pictures according to the time sequence.
The method mainly determines the temperature change direction according to the liquid movement direction.
In step S1, thermocouple measuring points are arranged to form a two-dimensional network in the container according to the liquid movement direction and the shape of the container, a plurality of groups of thermocouples are uniformly arranged in parallel to the liquid movement direction, the distance between two adjacent groups of thermocouples is within 10cm, the smaller the distance is, the higher the precision is, and three groups of thermocouples are arranged in the direction perpendicular to the liquid movement direction and are respectively positioned at the center of the tank body, the wall surface and the midpoint of a line segment connecting the center to the wall surface. Taking a vertical cylindrical container as an example: and a group of horizontal measuring points are arranged on the rotating surface of the cylinder at intervals of 5cm in the vertical direction, and each group of measuring points are respectively arranged at the circle center, half radius and circumference of the corresponding horizontal section, so that the thermocouple measuring points form a two-dimensional network to integrally cover the rotating surface of the cylinder.
In step S2, in order to remove abnormal thermocouples, the temperature difference of the liquid filled in the container each time is not more than 10 ℃.
In step S2, after the temperature abnormal measurement points are removed, the allowable range of the error of each measurement point is 3 ℃.
In step S3, the allowable error range of each measurement point after temperature compensation is 1 ℃.
In step S4, the high frequency measurement means that the temperature acquisition and recording frequency is not less than 1/S.
In step S6, the proximity substitution method is an interpolation method that substitutes the temperature at a certain point between the measurement points with the temperature value at the previous or subsequent point corresponding to the most adjacent measurement point at a certain point in time according to the directional characteristic of the liquid movement. The heat storage process is exemplified as follows: knowing a certain point aiThe interval n of the thermocouples in the vertical direction in the tank body,the time step delta tau, the cross section area A of the heat storage tank and the outlet volume flow Q of the heat storage tank can calculate the moving speed upsilon of the fluid in the tank body along the vertical direction;
then τ0Time of day, point aiThe upper v.delta tau position temperature value can be (tau)0Δ τ) at time aiTemperature value of, measuring point aiThe lower v.delta tau position temperature value can be (tau)0+ Δ τ) time point aiInstead of the temperature value. By this method, point a is measurediUpper distance
Inner region and lower distance
The inner areas are all measured points aiAnd the measured temperature completes interpolation, namely the temperature value at a certain thermocouple-free measuring point between two adjacent measuring points in the vertical direction is replaced by the temperature value at the previous moment or the next moment of the nearest measuring point in the vertical direction.
In step S7, the green spline interpolation method is a global interpolation method that analytically calculates an interpolation surface by performing weighted superposition using a plurality of green functions whose central points are located at respective observation data points.
The invention provides a visualized processing method for liquid temperature change in a container, which utilizes a proximity substitution method to carry out temperature accurate interpolation on the whole movement direction of liquid, and utilizes a Green spline interpolation method to convert a whole area into a refined temperature grid so as to realize accurate reduction of the liquid temperature at a position without a measuring point in the container in the process and visualized processing of whole experimental data, thereby visually and integrally presenting the experimental process.
Drawings
FIG. 1 is a flow chart of a method for visualizing the temperature change of a liquid in a container according to the present invention.
FIG. 2 is a schematic diagram of the thermocouple test point arrangement of the present invention.
Fig. 3 is a schematic diagram of the refined temperature grid obtained by the present invention.
FIG. 4 is a cloud of the temperature distribution in the tank body at a certain time obtained by the present invention.
FIG. 5 is a cloud chart showing the temperature distribution in the tank body in the experimental process according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
In order to achieve the purpose, the invention adopts the following acquisition and processing method:
as shown in fig. 1, the method for visualizing the temperature change of the liquid in the container of the present invention comprises the following steps:
s1: arranging a thermocouple in the container, and connecting the thermocouple with a temperature acquisition system;
s2: starting a temperature acquisition system, monitoring temperature values measured by all thermocouples, and removing abnormal thermocouples;
s3: under the condition of S2, calculating the deviation of the temperature values measured by the thermocouples at all temperatures, and compensating each difference value to the corresponding measuring point to ensure that the errors of the temperature values measured by all the thermocouples are within an allowable range;
s4: measuring and recording the temperature value measured by a thermocouple in the container at high frequency;
s5: selecting all temperature values at a certain moment as a group from the beginning of the temperature change process;
s6: carrying out temperature interpolation on the non-thermocouple measuring point by using a proximity substitution method;
s7: on the basis of the step S6, the whole temperature change area is converted into a refined temperature grid by using a green spline interpolation method, as shown in fig. 3;
s8: the refined temperature grid is integrally filled with the gradient color changing along with the temperature change to form a temperature distribution cloud picture of the inner area of the container at the corresponding moment in the temperature change process, as shown in figure 4;
s9: selecting all temperature values at the next moment as a group, and finishing the process from the step S6 to the step S8;
s10: repeating the step S9 until the temperature change process is finished, and obtaining a cloud map of the temperature distribution of the internal region of the container at all times, as shown in fig. 5;
s11: and converting the temperature distribution cloud pictures of the whole area in the container at all the moments into the process whole temperature distribution dynamic cloud pictures according to the time sequence.
The method determines the temperature change direction according to the liquid movement direction.
In step S1, thermocouple measuring points are arranged to form a two-dimensional network in the container according to the liquid movement direction and the shape of the container, a plurality of groups of thermocouples are uniformly arranged in parallel to the liquid movement direction, the distance between two adjacent groups of thermocouples is within 10cm, the smaller the distance is, the higher the precision is, and three groups of thermocouples are arranged in the direction perpendicular to the liquid movement direction and are respectively positioned at the center of the tank body, the wall surface and the midpoint of a line segment connecting the center to the wall surface. Taking a vertical cylindrical container as an example: a group of horizontal measuring points are arranged on the rotating surface of the cylinder at intervals of 5cm in the vertical direction, and each group of measuring points are respectively arranged at the circle center, the half radius and the circumference of the corresponding horizontal section, so that thermocouple measuring points form a two-dimensional network to integrally cover the rotating surface of the cylinder, as shown in figure 2, a horizontal line segment is a group of arranged thermocouples, and each group of 3 measuring points is respectively positioned at the intersection of the horizontal line segment and the vertical line segment.
In step S2, the temperature difference of the liquid filled in the thermocouple container every time is not more than 10 ℃ for eliminating abnormal thermocouple.
In step S2, after the temperature abnormal measurement points are removed, the allowable range of the error of each measurement point is 3 ℃.
In step S3, the allowable error range of each measurement point after temperature compensation is 1 ℃.
In step S4, the frequency of temperature collection and recording is not less than 1 time/S.
In step S6, the proximity substitution method is an interpolation method that substitutes the temperature at a certain point between the measurement points with the temperature value at the previous or subsequent point corresponding to the most adjacent measurement point at a certain point in time according to the directional characteristic of the liquid movement. The heat storage process is exemplified as follows: knowing a certain point aiThe interval n of the thermocouples in the vertical direction in the tank body, the time step length delta tau, and the heat storage tankThe cross sectional area A and the outlet volume flow Q of the heat storage tank can calculate the moving speed upsilon of the fluid in the tank body along the vertical direction;
then τ0Time of day, point aiThe upper v.delta tau position temperature value can be (tau)0Δ τ) at time aiTemperature value of, measuring point aiThe lower v.delta tau position temperature value can be (tau)0+ Δ τ) time point aiInstead of the temperature value. By this method, point a is measurediUpper distance
Inner region and lower distance
The inner areas are all measured points aiAnd the measured temperature completes interpolation, namely the temperature value at a certain thermocouple-free measuring point between two adjacent measuring points in the vertical direction is replaced by the temperature value at the previous moment or the next moment of the nearest measuring point in the vertical direction.
In step S7, the green spline interpolation method is a global interpolation method that analytically calculates an interpolation surface by performing weighted superposition using a plurality of green functions whose central points are located at respective observation data points.
Claims (9)
1. A method for visualizing the temperature change of liquid in a container is characterized by comprising the following steps: the method comprises the following steps:
s1: arranging a thermocouple in the container, and connecting the thermocouple with a temperature acquisition system;
s2: starting a temperature acquisition system, monitoring temperature values measured by all thermocouples, and removing abnormal thermocouples;
s3: under the condition of S2, calculating the deviation of the temperature values measured by the thermocouples at all temperatures, and compensating each difference value to the corresponding measuring point to ensure that the errors of the temperature values measured by all the thermocouples are within an allowable range;
s4: measuring and recording the temperature value measured by a thermocouple in the container at high frequency;
s5: selecting all temperature values at a certain moment as a group from the beginning of the temperature change process;
s6: carrying out temperature interpolation on the non-thermocouple measuring point by using a proximity substitution method;
s7: on the basis of the step S6, converting the whole temperature change area into a refined temperature grid by utilizing a Green spline interpolation method;
s8: filling the refined temperature grid with gradient color changing along with temperature to form a temperature distribution cloud picture of the inner area of the container at corresponding time in the temperature change process;
s9: selecting all temperature values at the next moment as a group, and finishing the process from the step S6 to the step S8;
s10: repeating the step S9 until the temperature change process is finished to obtain the temperature distribution cloud pictures of the inner area of the container at all times;
s11: and converting the temperature distribution cloud pictures of the whole area in the container at all the moments into the process whole temperature distribution dynamic cloud pictures according to the time sequence.
2. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: and determining the temperature change direction according to the liquid movement direction.
3. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S1, thermocouple measuring points are arranged to form a two-dimensional network in the container according to the liquid movement direction and the shape of the container, a plurality of groups of thermocouples are uniformly arranged in parallel to the liquid movement direction, the distance between two adjacent groups of thermocouples is within 10cm, the smaller the distance is, the higher the precision is, and three groups of thermocouples are arranged in the direction perpendicular to the liquid movement direction and are respectively positioned at the center of the tank body, the wall surface and the midpoint of a line segment connecting the center to the wall surface.
4. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S2, in order to remove abnormal thermocouples, the temperature difference of the liquid filled in the container each time is not more than 10 ℃.
5. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S2, after the temperature abnormal measurement points are removed, the allowable range of the error of each measurement point is 3 ℃.
6. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S3, the allowable error range of each measurement point after temperature compensation is 1 ℃.
7. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S4, the high frequency measurement means that the temperature acquisition and recording frequency is not less than 1/S.
8. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S6, the proximity substitution method is an interpolation method that substitutes the temperature at a certain point between the measurement points with the temperature value at the previous or subsequent point corresponding to the most adjacent measurement point at a certain point in time according to the directional characteristic of the liquid movement.
9. The method for visually processing the temperature change of the liquid in the container according to claim 1, wherein the method comprises the following steps: in step S7, the green spline interpolation method is a global interpolation method that analytically calculates an interpolation surface by performing weighted superposition using a plurality of green functions whose central points are located at respective observation data points.
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