CN105022883A - Method for accurately estimating droplet group mixing time - Google Patents
Method for accurately estimating droplet group mixing time Download PDFInfo
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- CN105022883A CN105022883A CN201510444891.4A CN201510444891A CN105022883A CN 105022883 A CN105022883 A CN 105022883A CN 201510444891 A CN201510444891 A CN 201510444891A CN 105022883 A CN105022883 A CN 105022883A
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- 238000000034 method Methods 0.000 title claims abstract description 38
- 238000012545 processing Methods 0.000 claims abstract description 12
- 238000005516 engineering process Methods 0.000 claims abstract description 5
- 238000010348 incorporation Methods 0.000 claims description 14
- 238000001914 filtration Methods 0.000 claims description 3
- 230000009466 transformation Effects 0.000 claims description 3
- 238000003745 diagnosis Methods 0.000 abstract description 2
- 238000012360 testing method Methods 0.000 description 16
- 230000008569 process Effects 0.000 description 12
- 238000009835 boiling Methods 0.000 description 5
- 238000012546 transfer Methods 0.000 description 4
- 230000007704 transition Effects 0.000 description 4
- 230000000007 visual effect Effects 0.000 description 3
- 239000000654 additive Substances 0.000 description 2
- 230000000996 additive effect Effects 0.000 description 2
- 230000003542 behavioural effect Effects 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 238000013461 design Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 230000002195 synergetic effect Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000004931 aggregating effect Effects 0.000 description 1
- 238000003556 assay Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
- 210000004369 blood Anatomy 0.000 description 1
- 230000000052 comparative effect Effects 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
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Abstract
The present invention relates to a method for accurately estimating droplet group mixing time and belongs to the field of homology depiction of a droplet group behavior. According to the present invention, a digital image processing technology is applied to obtain a series of images convenient to accurately calculate a Betti number; a calculation homology group theory is applied to obtain a Betti number time sequence; and a probability statistics method is applied to carry out predictive diagnosis based on a 3 sigma principle on Betti number time data and a moment exceeding a predictive range is used as the optimal mixing uniform time. The method disclosed by the present invention is simple and easy to operate, is a method capable of accurately and reliably estimating the optimal mixing time and can provide the reference significance for the actual engineering application.
Description
Technical field
The present invention relates to a kind of method of accurate estimation droplet cluster incorporation time, belong to the droplet cluster behavior people having the same aspiration and interest and portray field.
Background technology
The research that ORC directly contacts the sign of the boiling of organic working medium in steam generator phase transition process droplet cluster behavior and itself and heat exchange synergistic mechanism is a very challenging job.Incorporation time characterizes the important parameter that ORC directly contacts organic working medium boiling phase transition process droplet cluster behavior in steam generator.
Summary of the invention
The object of the invention is the method for building the best heterogeneous incorporation time of a kind of that have higher using value, simple accurate estimation direct-contact heat exchanger; The present invention adopts conventional " 3 σ " principle in Probability Statistics Theory to carry out early warning diagnosis to the Betti number time series can portraying mixing uniformity, specifically comprises the following steps:
(1) use digital image processing techniques, obtain a series of image being convenient to accurately calculate Betti number;
(2) use calculating homology group theoretical, obtain Betti number time series;
(3) use probabilistic method, carry out diagnosing based on the early warning of " 3 σ " principle to Betti number time data, will the mixing time of moment as the best of early warning range be exceeded, and specifically comprise the following steps:
1. a given moment T
0, assert T
0moment and Betti number time series afterwards thereof are all in the state of mixing;
2. to T
0moment and Betti number time series afterwards thereof ask for average μ and standard deviation sigma;
3. from T
0+ t
0moment rises, and judges that whether each monodrome is double successively exceed lower limit warning line " μ-3 σ " by inverse time order;
4. doublely first to exceed in lower limit warning line the moment that first time exceeds lower limit warning line by what 3. determine and be designated as T
1;
5. by T
1as the mixing time critical point T of optimum.
The present invention uses gray processing conventional in Digital Image Processing theory, cap transformation, filtering, binaryzation and opening operation technology, finally obtains the image being suitable for immediately getting off accurately calculating Betti number;
The present invention calculates 0 dimension Betti number and the 1 dimension Betti number of binary map by means of calculating people having the same aspiration and interest planning (Computational Homology Project, CHomP) software package.
The invention has the beneficial effects as follows:
(1) the present invention sets up one based on the method based on the accurate estimation incorporation time of " 3 σ " principle in Probability Statistics Theory; Simple, can accurately, reliably estimate directly to contact boiling heat transfer process incorporation time, have wide range of applications, having for a lot of experimentation can the value of reference and application, plays directive function.
(2) the accurate estimation being applicable to heterogeneous mixed process incorporation time of the present invention, incorporation time is the primary evaluation index that ORC directly contacts organic working medium boiling phase transition process droplet cluster behavior in steam generator on the one hand, characterizing droplet group behavioral aspect, for experimental monitoring provides reference, directive function is played to the carrying out of experimentation; According to the accurate estimation of incorporation time, behavior state can be evaluated on the other hand, for further investigation droplet cluster behavior and heat exchange synergistic mechanism provide foundation.
Accompanying drawing explanation
Fig. 1 is Digital Image Processing procedure chart of the present invention;
Fig. 2 is the accurate drawing for estimate of incorporation time of the present invention.
Embodiment
Further illustrate flesh and blood of the present invention below in conjunction with accompanying drawing and example, but content of the present invention is not limited to this.
Embodiment 1
(1) the building of test design and test platform
In the present embodiment, the ORC direct contact type steam generator test platform built, orthogonal test selects four parameters of testing, and is continuous phase conduction oil liquid level, initial heat transfer temperature difference, working medium flow rate and conduction oil flow rate in ORC direct contact evapouration respectively.Each parameter one has three variablees; According to orthogonal test table, the orthogonal test of 4 factor 3 levels is selected in this test, L
9(3
4) orthogonal test factor level table refers to table 1, test design scheme refers to table 2.
(2) acquisition of droplet cluster behavior pattern
In process of the test, observed by visual window and find, in different working conditions and test period section, the diabatic process of dispersed phase drop group in continuous phase conduction oil presents complexity and the state of constantly change, high-speed camera is used to catch these patterns with the speed of 30 frames per second, each test duration takes 8 minutes, and to obtain the image of direct contact heat transfer process droplet cluster Behavioral change of 6000, each width figure wherein correspond to the little region of visual window below one; The scope that high-speed camera records is only the wall near video camera, but not from a wall to another wall; Seizable region is the cognizable region of video camera under normal assays illumination condition simultaneously.In order to reduce polarisation and the impact of glass-mirror reflection on image, test is carried out at night, and close daylight lamp in experiment shooting process, power light source is used to irradiate visual window, after such process, suffered by pattern captured by discovery, external influence is less, and can react the aggregating state of dispersed phase drop group in direct contact type evaporator more accurately.
(3) process of droplet cluster behavior pattern
In order to 0 dimension Betti number and the 1 dimension Betti number of computed image, need to carry out digitized processing to taking the color pattern obtained, choosing arbitrarily a wherein pictures is example, Fig. 1 is the processing procedure of a wherein droplet cluster pattern, concrete treatment step is as follows: gray processing, cap transformation, filtering, binaryzation and opening operation technology, finally obtains the image being suitable for immediately getting off accurately calculating Betti number;
(3) Betti number seasonal effect in time series obtains
This example ties up Betti number by the 0 dimension Betti number after finally processing in image and 1 calculated by CHomP software package under different orthogonal operating condition of test; Number according to orthogonal test the 0 dimension Betti number and 1 calculated to tie up shown in Betti number time evolution Fig. 2.
(3) non-uniform time of droplet cluster behavior evolution
Based on the accurate estimation incorporation time of " 3 σ " principle in Probability Statistics Theory; Its concrete steps are:
step 1a given moment T
0, tentatively assert T
0moment and Betti number time series afterwards thereof are all in the state of mixing; T
0value is in table 3 shown in the 2nd row.
To T
0moment and Betti number time series afterwards thereof ask for average μ and standard deviation sigma; Average μ and standard deviation sigma are respectively in table 3 shown in the 3rd row and the 4th row, and average line is as shown in Fig. 2 dot-dashed line.
From T
0+ t
0moment rises, and judges that whether each monodrome is double successively exceed lower limit warning line " μ-3 σ " by inverse time order; t
0value is in table 3 shown in the 5th row, and warning line to be shown in Fig. 2 shown in short dash line.
Will
step 3that determines doublely first to exceed in lower limit warning line the moment that first time exceeds lower limit warning line and is designated as T
1.
By T
1as the mixing time critical point T of optimum; T value in table 3 shown in the 6th row, and in fig. 2 with shown in circle ' zero '.
(4) checking of method validity
The conspiracy relation of organic working medium boiling phase transition process droplet cluster behavior and heat exchange in steam generator is directly contacted for quantizing ORC, the index of characterizing droplet group behavior is built by non-uniform time, and calculate grey relational grade and the related coefficient of itself and heat transfer coefficient, contrast with this validity that additive method (averaging method, Slope Method, standard deviation method) illustrates this method.Comparative result is as shown in table 4, and grey relational grade and related coefficient are the bigger the better.Therefore as can be seen from Table 4, the inventive method comparatively additive method there is comparatively significant validity.
Table 1
。
Table 2
。
Table 3
。
Table 4
Claims (3)
1. accurately estimate a method for droplet cluster incorporation time, it is characterized in that, specifically comprise the following steps:
(1) use digital image processing techniques, obtain a series of image being convenient to accurately calculate Betti number;
(2) use calculating homology group theoretical, obtain Betti number time series;
(3) use probabilistic method, carry out diagnosing based on the early warning of " 3 σ " principle to Betti number time data, will the mixing time of moment as the best of early warning range be exceeded, and specifically comprise the following steps:
1. a given moment T
0, assert T
0moment and Betti number time series afterwards thereof are all in the state of mixing;
2. to T
0moment and Betti number time series afterwards thereof ask for average μ and standard deviation sigma;
3. from T
0+ t
0moment rises, and judges that whether each monodrome is double successively exceed lower limit warning line " μ-3 σ " by inverse time order;
4. doublely first to exceed in lower limit warning line the moment that first time exceeds lower limit warning line by what 3. determine and be designated as T
1;
5. by T
1as the mixing time critical point T of optimum.
2. accurately estimate the method for droplet cluster incorporation time according to claim 1, it is characterized in that: use gray processing conventional in Digital Image Processing theory, cap transformation, filtering, binaryzation and opening operation technology, finally obtain the image being suitable for immediately getting off accurately calculating Betti number.
3. accurately estimate the method for droplet cluster incorporation time according to claim 1, it is characterized in that: by means of the 0 dimension Betti number and the 1 dimension Betti number that calculate people having the same aspiration and interest planning software bag calculating binary map.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101650292A (en) * | 2009-09-02 | 2010-02-17 | 昆明理工大学 | Method for measuring mixing effect of fluid |
| CN101930501A (en) * | 2010-08-24 | 2010-12-29 | 昆明理工大学 | Method for building fractal dimension-based multi-phase mixed effect prediction model |
| EP2383569A1 (en) * | 2009-01-27 | 2011-11-02 | Osaka University | Image analysis apparatus, image analysis method, image analysis program and recording medium |
-
2015
- 2015-07-27 CN CN201510444891.4A patent/CN105022883A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2383569A1 (en) * | 2009-01-27 | 2011-11-02 | Osaka University | Image analysis apparatus, image analysis method, image analysis program and recording medium |
| CN101650292A (en) * | 2009-09-02 | 2010-02-17 | 昆明理工大学 | Method for measuring mixing effect of fluid |
| CN101930501A (en) * | 2010-08-24 | 2010-12-29 | 昆明理工大学 | Method for building fractal dimension-based multi-phase mixed effect prediction model |
Non-Patent Citations (3)
| Title |
|---|
| 徐建新: "多相体系搅拌混合效果评价方法及其应用研究", 《中国博士学位论文全文数据库 工程科技I辑》 * |
| 赵从宝: "《实用材料试验数据处理》", 30 April 1992, 经济管理出版社 * |
| 黄峻伟: "ORC直接接触式蒸汽发生器的传热性能及其优化研究", 《中国博士学位论文全文数据库 工程科技II辑》 * |
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