CN110082389A - A method of detection insulated container heat insulation effect is distributed based on temperature probability sensitivity - Google Patents
A method of detection insulated container heat insulation effect is distributed based on temperature probability sensitivity Download PDFInfo
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Abstract
The invention discloses a kind of methods that detection insulated container heat insulation effect is distributed based on temperature probability sensitivity, and this method comprises the following steps: determination of the S1. based on the insulated container interior temperature distribution of finite element means；S2. the determination of starting heat preservation stable point time and the screening in extreme value temperature difference region；S3. the Temperature Distribution actual measurement in extreme value temperature difference region；S4. the identification of extreme value temperature difference region continuum boundary；S5. the gridding temperature probability density distribution in extreme value temperature difference region is determined；S6. determine the heat preservation stable point time to the susceptibility of limiting temperature probability density numerical value；S7. the heat insulation effect based on heat-insulatied slit parameter and the distribution of temperature probability sensitivity is assessed.This method detection accuracy is high, for realizing that the real-time assessment of container holding temperature has important practical significance.
Description
Technical field
It is the present invention relates to temperature detection field, in particular to a kind of based on the distribution detection insulated container of temperature probability sensitivity
The method of heat insulation effect.
Background technique
With the development of the society, insulated container heat insulation effect differentia influence the development of industrialization and chemurgy.At this
Under the premise of the background of sample, insulating power missing will result in huge economic loss, while can also waste a large amount of resource, therefore
It is necessary and urgent for grasp to the heat insulation effect of insulated container.Insulated container heat insulation effect detection method has very much
Kind, but the heat insulation effect of integral heat insulation container is judged by the temperature value of some a small amount of measuring points mostly, this is for reality
In the case of insulated container integral heat insulation effect detection for there are many limitations, accuracy is not high, and detection efficiency is low.Such as
It is this current research field that, which carries out detection to the heat insulation effect of insulated container from the angle of the whole limit temperature difference,
Existing common problem.
Summary of the invention
Goal of the invention: it is an object of the present invention to provide one kind based on temperature probability sensitivity distribution detection insulated container heat preservation effect
The method of fruit, this method detection accuracy are high.
Technical solution: the present invention provides a kind of side that detection insulated container heat insulation effect is distributed based on temperature probability sensitivity
Method includes the following steps:
S1. based on the determination of the insulated container interior temperature distribution of finite element means:
In finite element analysis software, radiated by a fixed radioactive source to insulated container inside circumference,
A temperature field is formed in insulated container inner periphery, emulates insulated container since opening radioactive source using software analysis
The situation of change of internal Temperature Distribution and numerical value；
S2. the determination of starting heat preservation stable point time and the screening in extreme value temperature difference region:
On the basis of S1, the setting starting heat preservation stable point time；Meanwhile it analyzing to work as and reaching the starting heat preservation stable point time
When extreme value temperature difference region, and the extreme value temperature difference region area A in finite element modelsIt labels；
S3. the Temperature Distribution actual measurement in extreme value temperature difference region:
According to the starting heat preservation stable point time determined in S2 and extreme value temperature difference region, to be heated to inside insulated container
When the starting heat preservation stable point time, start Temperature Distribution and specific temperature value of the measuring device to extreme value temperature difference point near zone
It measures, delimitation measured zone area is 2As；
S4. the identification of extreme value temperature difference region continuum boundary:
It is 2A in the measurement area that S3 delimitedsRegion in, by discrete region at the form of coordinate, and to phase in region
Connect the temperature value T of two o'clock1With T2Substitute into following formula (1) calculating temperature difference continuous coefficients CtIf temperature difference continuous coefficients Ct>=5%, then
The region of noncontinuity temperature measurement value is turned off, and the temperature difference continuous coefficients of universe are calculated, and according to knot
It calculates result and determines last extreme value temperature difference region continuum boundary, the part in boundary is extreme value temperature difference continuum；
S5. the gridding temperature probability density function in extreme value temperature difference region is determined
Gridding processing is carried out to it in the extreme value temperature difference continuum j that S4 identification finishes, such as formula (2), formula (3), formula
(4), according to the temperature value of i grid in each region come temperature averages E corresponding to the j of zoningj, standard deviation VjAnd pole
The probability density function F being worth in the j of temperature difference regionj；
In formula, EjFor temperature averages corresponding to the j of region, VjFor standard deviation corresponding to the j of region, n is of grid
Number, TiFor the temperature value of i-th of grid；
In formula, FjFor the probability density function of region j, DiThe spatial position feature recorded by i-th of grid refers to
Mark, is obtained, V by the measurement of region geometry size in S4jFor standard deviation corresponding to the j of region, exp is index bottom, the number of e
Value is taken as 2.71；
S6. determine the heat preservation stable point time to the susceptibility of limiting temperature probability density numerical value；
In conjunction with gridding temperature probability density function in S5, all poles that S4 is determined are solved by formula (5), formula (6)
It is worth the probability density value I in temperature difference regionjAnd the heat preservation stable point time is to the sensitivity indexes β of region j limiting temperature probability densityj；
In formula, m is the number that extreme value temperature difference region is selected, FjFor the probability density function of region j, j is region volume
Number, SjFor the heat preservation stable point time of j numbering area；
S7. the heat insulation effect based on heat-insulatied slit parameter and the distribution of temperature probability sensitivity is assessed
In the sensitivity indexes β for the limiting temperature probability density that S6 is calculatedjOn the basis of, it is calculated by formula (7) based on guarantor
The heat insulation effect evaluation index Q of warm gap parameter and the distribution of temperature probability sensitivity；
In formula, βjIt is the heat preservation stable point time to the sensitivity indexes of region j limiting temperature probability density, m is extreme value temperature
The selected number in poor region, n are the number of grid, and j is zone number,For j i, region grid spatial location feature
The average value of index, DijmaxFor the maximum value of the i grid spatial location characteristic index in j region, DijminIt is j region i
The minimum value of grid spatial location characteristic index, TijmaxFor the maximum value of temperature value in j i, region grid, TijminFor j
The minimum value of temperature value in the grid of i, a region,For the average value of temperature value in j i, region grid, D is spatial position
Characteristic index, Q are heat insulation effect evaluation index
The utility model has the advantages that the present invention may be implemented the detection of internal container overall region temperature, and from the whole limit temperature difference
Angle set out to be detected to the heat insulation effect of insulated container, judged so as to avoid by the temperature value of measuring point
The limitation of the heat insulation effect of integral heat insulation container effectively improves the accuracy of the integral heat insulation effect detection of insulated container
With efficiency.
Detailed description of the invention
Fig. 1 is the method flow provided by the invention that detection insulated container heat insulation effect is distributed based on temperature probability sensitivity
Block diagram.
Specific embodiment
As shown in Figure 1, the present embodiment is distributed the method for detection insulated container heat insulation effect based on temperature probability sensitivity, it should
Method the following steps are included:
S1. based on the determination of the insulated container interior temperature distribution of finite element means
To an insulated container, is radiated, kept the temperature to insulated container surrounding by a fixed radioactive source
A temperature field is formed around internal container, when insulated container enters working condition, establishes having for insulated container component
Meta-model is limited, and the threedimensional model after foundation is imported into FEM-software ANSYS, be arranged by grid dividing, constraint,
Different external temperature setting steps complete the pre-treatment of insulated container finite element analyses, to pre-treatment after use ANSYS
Internal temperature under its practical working condition is analyzed, the Temperature Distribution and numerical value inside insulated container are determined with this
Situation of change；
S2. the determination of starting heat preservation stable point time and the screening in extreme value temperature difference region
In insulated container Temperature Distribution known to S1 and numerical value change, since analysis opening radioactive source to packaging
There are 80% regional temperatures to be greater than time when insulated container sets holding temperature in each regional temperature inside case, that is, originates
Keep the temperature the stable point time.Meanwhile analysis filters out insulated container internal temperature number when reaching the starting heat preservation stable point time
Value ranks the region of preceding 2% Yu rear 2%, i.e. extreme value temperature difference region, and according to the extreme value temperature difference region area in finite element model
AsIt is subject to certain label；
S3. the Temperature Distribution actual measurement in extreme value temperature difference region
The stable point time is kept the temperature according to starting fixed in S2, is divided according to extreme value temperature difference region, it will be wait keep the temperature
When internal container is heated to the starting heat preservation stable point time, while with infrared temperature sensor in insulated container work item
The Temperature Distribution of insulated container extreme value temperature difference point near zone and specific temperature value are measured under part, delimit measurement zone
Domain area 2As；
S4. the identification of extreme value temperature difference region continuum boundary
It is 2A in the measurement area that S3 delimitedsRegion in, be to be separated into the form of a coordinate by region division, working
Under the conditions of calculating temperature difference continuous coefficients CtIf temperature difference continuous coefficients Ct>=5%, then to the region of noncontinuity temperature measurement value
It turns off, and the temperature difference continuous coefficients of universe is calculated, and determine last extreme value temperature difference region according to checkout result
Continuum boundary, the part in boundary are extreme value temperature difference continuum；
Wherein, T1With T2Respectively divide the temperature value for the two o'clock that is connected in region, CtFor temperature difference continuous coefficients.
S5. the gridding temperature probability density function in extreme value temperature difference region is determined
Gridding processing is carried out to it in the extreme value temperature difference continuum j that S4 identification finishes, the area of grid is 5cm2,
According to temperature averages E corresponding to the temperature value zoning j of i grid in each regionj；
Wherein, j is the number of extreme value temperature difference continuum, and n is the number of grid, and i is i-th of grid, EjFor extreme value temperature
Temperature averages corresponding to poor continuum j, TiFor the temperature value of i-th of grid.
According to the temperature value of i-th of grid in above-mentioned each region come temperature averages E corresponding to the j of zoningj, meter
Calculate temperature standard difference V corresponding to extreme value temperature difference continuum jj；
Wherein, EjFor temperature averages corresponding to extreme value temperature difference continuum j, VjIt is right for extreme value temperature difference continuum j
The standard deviation answered, TiFor the temperature value of i-th of grid, j is the number of extreme value temperature difference continuum, and n is the number of grid, i
For i-th of grid.
The spatial position characteristic index D recorded according to i-th of the grid in each region, recordedi, above-mentioned i-th
The temperature averages E of region j corresponding to the temperature value of gridj, standard deviation Vj, calculate extreme value temperature difference continuum j in probability it is close
Spend distribution function Fj；
Wherein, j is the number of extreme value temperature difference continuum, and n is the number of grid, and i is i-th of grid, FjFor extreme value temperature
The probability density function of poor continuum j, DiThe spatial position characteristic index recorded by i-th of grid, by S4
The measurement of region geometry size obtains, VjFor standard deviation corresponding to the j of region, exp is index bottom, and the numerical value of e is taken as 2.71.
S6. determine the heat preservation stable point time to the susceptibility of limiting temperature probability density numerical value
The probability in all extreme value temperature difference region that S4 is determined is solved in conjunction with gridding temperature probability density function in S5
Density value Ij；
Wherein, m is the number that extreme value temperature difference region is selected, FjFor the probability density function of region j, j is extreme value temperature
The number of poor continuum, SjFor the heat preservation stable point time of j numbering area, IjIt is general corresponding to extreme value temperature difference continuum j
Rate density value.
In conjunction with the probability density value I in above-mentioned all extreme value temperature difference regionj, the heat preservation stable point time is calculated to the region j limit
The sensitivity indexes β of temperature probability densityj；
Wherein, j is the number of extreme value temperature difference continuum, SjFor the heat preservation stable point time of j numbering area, IjFor region j
Corresponding probability density value, βjFor sensitivity indexes corresponding to the j of region.
S7. the heat insulation effect based on heat-insulatied slit parameter and the distribution of temperature probability sensitivity is assessed
In the sensitivity indexes β for the limiting temperature probability density that S6 is calculatedjOn the basis of, identify extreme value temperature difference continuum
Temperature value T in institute's grid divisionijMaximum of TijmaxWith minimum value Tijmin, calculate extreme value temperature difference continuum institute grid division
In temperature value TijCorresponding average valueCalculate the heat preservation based on heat-insulatied slit parameter and the distribution of temperature probability sensitivity
Recruitment evaluation index Q；
Wherein, βjIt is the heat preservation stable point time to the sensitivity indexes of region j limiting temperature probability density, m is extreme value temperature
The selected number in poor region, n are the number of grid, and j is zone number,For j i, region grid spatial location feature
The average value of index, DijmaxFor the maximum value of the i grid spatial location characteristic index in j region, DijminIt is j region i
The minimum value of grid spatial location characteristic index, TijmaxFor the maximum value of temperature value in j i, region grid, TijminFor j
The minimum value of temperature value in the grid of i, a region,For the average value of temperature value in j i, region grid, D is spatial position
Characteristic index, Q are heat insulation effect evaluation index.
Claims (5)
1. a kind of method for being distributed detection insulated container heat insulation effect based on temperature probability sensitivity, it is characterised in that: including such as
Lower step:
S1. based on the determination of the insulated container interior temperature distribution of finite element means:
In finite element analysis software, is radiated, protected to insulated container inside circumference by a fixed radioactive source
A temperature field is formed around warm internal container, is emulated inside insulated container since opening radioactive source using software analysis
Temperature Distribution and numerical value situation of change；
S2. the determination of starting heat preservation stable point time and the screening in extreme value temperature difference region:
On the basis of S1, the setting starting heat preservation stable point time；Meanwhile it analyzing when reaching the starting heat preservation stable point time
Extreme value temperature difference region, and the extreme value temperature difference region area A in finite element modelsIt labels；
S3. the Temperature Distribution actual measurement in extreme value temperature difference region:
According to the starting heat preservation stable point time determined in S2 and extreme value temperature difference region, originated to be heated to inside insulated container
When keeping the temperature the stable point time, starting measuring device carries out the Temperature Distribution of extreme value temperature difference point near zone and specific temperature value
Measurement, delimitation measured zone area are 2As；
S4. the identification of extreme value temperature difference region continuum boundary:
It is 2A in the measurement area that S3 delimitedsRegion in, by discrete region at the form of coordinate, and to being connected in region
The temperature value T of two o'clock1With T2Substitute into following formula (1) calculating temperature difference continuous coefficients CtIf temperature difference continuous coefficients Ct>=5%, then to non-
The region of continuity temperature measurement value turns off, and calculates the temperature difference continuous coefficients of universe, and is tied according to clearing
Fruit determines last extreme value temperature difference region continuum boundary, and the part in boundary is extreme value temperature difference continuum；
S5. the gridding temperature probability density function in extreme value temperature difference region is determined
Gridding processing is carried out to it in the extreme value temperature difference continuum j that finishes of S4 identification, such as formula (2), formula (3), formula (4),
According to the temperature value of i grid in each region come temperature averages E corresponding to the j of zoningj, standard deviation VjAnd extreme value temperature
Probability density function F in poor region jj；
In formula, EjFor temperature averages corresponding to the j of region, VjFor standard deviation corresponding to the j of region, n is the number of grid, Ti
For the temperature value of i-th of grid；
In formula, FjFor the probability density function of region j, DiThe spatial position characteristic index recorded by i-th of grid is led to
The measurement of region geometry size in S4 is crossed to obtain, VjFor standard deviation corresponding to the j of region, exp is index bottom, and the numerical value of e takes
It is 2.71；
S6. determine the heat preservation stable point time to the susceptibility of limiting temperature probability density numerical value；
In conjunction with gridding temperature probability density function in S5, all extreme value temperature that S4 is determined are solved by formula (5), formula (6)
The probability density value I in poor regionjAnd the heat preservation stable point time is to the sensitivity indexes β of region j limiting temperature probability densityj；
In formula, m is the number that extreme value temperature difference region is selected, FjFor the probability density function of region j, j is zone number, Sj
For the heat preservation stable point time of j numbering area；
S7. the heat insulation effect based on heat-insulatied slit parameter and the distribution of temperature probability sensitivity is assessed
In the sensitivity indexes β for the limiting temperature probability density that S6 is calculatedjOn the basis of, it is calculated by formula (7) and is based on heat-insulatied slit
The heat insulation effect evaluation index Q of parameter and the distribution of temperature probability sensitivity；
In formula, βjIt is the heat preservation stable point time to the sensitivity indexes of region j limiting temperature probability density, m is extreme value temperature difference region
Selected number, n are the number of grid, and j is zone number,For j i, region grid spatial location characteristic index
Average value, DijmaxFor the maximum value of the i grid spatial location characteristic index in j region, DijminFor in j i, region grid
The minimum value of spatial position characteristic index, TijmaxFor the maximum value of temperature value in j i, region grid, TijminFor j region i
The minimum value of temperature value in a grid,For the average value of temperature value in j i, region grid, D is that spatial position feature refers to
Mark, Q are heat insulation effect evaluation index.
2. the method for detection insulated container heat insulation effect as described in claim 1, which is characterized in that the starting in step S2 is protected
The warm stable point time is that into each regional temperature of internal container, there are 80% regional temperatures to be greater than since opening radioactive source
Insulated container sets time when holding temperature.
3. the method for detection insulated container heat insulation effect as described in claim 1, which is characterized in that the extreme value temperature in step S2
Poor region is to filter out insulated container internal temperature numerical value when reaching the starting heat preservation stable point time to rank preceding 2% with after
2% region.
4. the method for detection insulated container heat insulation effect as described in claim 1, which is characterized in that grid is arranged in step S5
Area be 5cm2。
5. the method for detection insulated container heat insulation effect as described in claim 1, which is characterized in that the finite element in step S1
It analyzes software and uses ANSYS software.
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Cited By (2)
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| CN110748951A (en) * | 2019-11-01 | 2020-02-04 | 北京硕人时代科技股份有限公司 | Method, device and system for determining heat supply energy saving amount |
| CN115986874A (en) * | 2022-12-26 | 2023-04-18 | 昆山金鑫新能源科技股份有限公司 | Battery charging safety monitoring and early warning method and system |
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