CN112098283B - Method for measuring residence time distribution of solid particles in fluidized bed based on image recognition principle and test bed thereof - Google Patents
Method for measuring residence time distribution of solid particles in fluidized bed based on image recognition principle and test bed thereof Download PDFInfo
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Abstract
The invention provides a method for measuring the residence time distribution of solid particles in a fluidized bed based on an image recognition principle and a test bed thereof. Particles with different colors from the bed material particles are adopted for tracing, the tracing particles are injected into the bed and then sampled at the discharge end periodically, and all samples are photographed under the same light source condition. Background elimination, color enhancement and gray level adjustment are carried out on the sample image, pixels representing tracer particles are identified by means of RGB threshold segmentation, then the concentration of the tracer particles in the image is calculated, and the retention time distribution of the particles in the fluidized bed is calculated by combining the change rule of the concentration of the tracer particles along with time. The particle residence time distribution measuring method is simple to operate, high in experimental efficiency, few in error-generating links and high in accuracy.
Description
Technical Field
The invention belongs to the field of gas-solid fluidization, and particularly relates to a method for measuring retention time distribution of solid particles in a fluidized bed based on an image recognition principle.
Background
The strong back mixing of solid particles in the gas-solid fluidized bed results in uneven residence time of solid material in the fluidized bed. Some fluidized bed processes have very strict requirements on the average residence time and the residence time distribution of solid materials in a fluidized bed, and if the residence time is too short, the reaction conversion rate of the solid materials is too low, and if the residence time is too long, the physical and chemical properties of the solid materials can be deteriorated. Therefore, in the development of fluidized bed reactors, it is often necessary to measure the average residence time and residence time distribution of solid materials in the fluidized bed and to optimize the reactor structure and operating conditions based thereon. The efficient and high-precision particle residence time distribution measuring method has important significance for research and development and engineering application of the fluidized bed reactor.
In the measurement of the residence time distribution of solid particles in a fluidized bed reactor, the method of adding tracer particles into bed materials is usually adopted, and the rule of the concentration of the tracer particles changing along with the time is measured, so that the mixing condition and the residence time distribution of the particles can be obtained. The selection of tracer particles generally follows the following principles:
(1) the physical properties of the tracer particles are basically consistent with those of the main material in the fluidized bed;
(2) the interference to a gas-solid flow field is small when the tracer particles are injected;
(3) accumulation of tracer particles in the fluidised bed should be avoided;
(4) the tracer particles should be added rapidly and in sufficient quantity.
There have been a great deal of research on methods for particle tracing, such as dyed particles, salt particles, magnetic particles, radioactive particles, and hot (cold) particle tracing.
1. Tracing dyed particles: and adopting a coloring agent to dye the bed material particles to serve as the tracer particles. The experimental procedure was to inject tracer particles into the fluidized bed by pulse method, sample periodically from the outlet and determine the concentration of the dyed particles at the outlet. For large particles, the number of particles can be counted visually, and for small particles, the staining agent on the surface of the particles is dissolved in the solution, and the concentration of the staining agent in the sample solution is measured by a spectrophotometer, so that the concentration of the stained tracer particles is calculated. The method has the advantages that the physical properties of the tracer particles are basically consistent with those of the main material, the preparation of the tracer particles is simple, and the cost is controllable.
2. Salt particle tracing: salt particles (e.g., NH4Cl, KCl, etc.) are used as tracer particles. After sampling, the samples were weighed, dissolved in a fixed amount of water and analyzed for the concentration of tracer particles (salt particles) by measuring the conductivity of the solution.
3. Hot particle tracing: the experimental device consists of a quasi-steady-state hot tracer particle injection device and a movable thermistor detection device. The experimental step is to inject hot tracer particles by utilizing pulses or introduce heat by a heating coil to measure a temperature curve so as to obtain the rule that the concentration of the hot particles changes along with time.
4. Magnetic particle tracing: ferromagnetic particles are used as a tracer, and a continuous tracer particle concentration change rule can be obtained by measuring the change of the magnetic strength at the discharge port.
5. Radioactive tracing method: the concentration of the tracer particle can be obtained by detecting the radioactive intensity of the particle at the outlet using radioactive NaCO3 particles, Ga-attached particles, Si radioisotope, and the like as the tracer particles.
6. And (3) phosphorescent particle tracing: the phosphorescent particles can emit light with fixed frequency after being irradiated, and can emit afterglow after the irradiation is stopped, and the intensity of the afterglow is weakened along with time. The method requires that a flash device emits light instantaneously, a collecting device is arranged at the downstream, the intensity information of the afterglow light of the phosphorescent particles is obtained, and the residence time of the particles in the bed is calculated.
The above methods of measuring by adding tracer particles can be divided into two types, sampling measurement and continuous measurement:
the sampling and measuring method requires separate treatment of each sample, and is complicated. When a spectrophotometer is adopted for measurement, quantitative liquid extraction is needed to fully dissolve the tracer on the surfaces of the tracer particles, and the liquid is extracted through a standard glass cuvette and then is subjected to absorbance measurement and converted into the concentration of the tracer particles; salt particle tracing also needs quantitative liquid taking and dissolving, conductivity is measured again, and tracing particle concentration is calculated.
The apparatus for continuous assays is relatively complex and the experimental results are susceptible to external influences. If the hot particle tracing method needs to consider the heat exchange between particles and the environment, the accuracy is easily influenced, the calculation process is complex and some assumptions need to be introduced; the preparation cost of the tracer particles of the magnetic particle tracer method is high, and certain limitation is placed on the material type selection of the solid bed material; radioactive particles risk causing greater pollution and harm; the phosphorescent particles need more devices, have strict requirements on the external light environment and have higher cost.
In summary, the conventional methods for measuring the residence time distribution of solid particles in a fluidized bed have certain limitations, and it is necessary to develop a reliable, convenient and cost-controllable method for measuring the residence time distribution of particles.
Disclosure of Invention
In order to solve the problems of complex operation, long time consumption, large error and the like of the concentration measurement of the tracer particles in a sampling measurement method, the invention provides a method for measuring the retention time distribution of the solid particles in the fluidized bed based on an image recognition principle.
The invention adopts the following technical scheme for solving the technical problems:
a method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle comprises the following steps:
step 1: adding tracer particles when the fluidization of solid bed materials in the fluidized bed reaches a stable state; the color of the tracer particles is different from that of the solid bed material, and the mass proportion of the tracer particles is not more than 5% of that of the solid bed material;
step 2: starting timing when the tracer particles are added into the fluidized bed; sampling from the fluidized bed for a plurality of times according to the preset sampling time until only solid bed materials exist in the taken sample and no tracer particles appear;
and step 3: fully stirring the samples taken out in the step 2 respectively to ensure that the tracer particles contained in each sample can be uniformly mixed with the solid bed material in each sample;
and 4, step 4: photographing the uniformly mixed samples in the step (3) one by one under the same light source condition according to the sampling sequence to obtain corresponding images;
and 5: carrying out image processing on the images obtained in the step 4 in an HSV color space one by one according to the sampling sequence so as to eliminate the semitransparent background of each image and enhance the color of the tracer particles in each image; converting the processed images in the HSV color space into RGB color spaces one by one according to the sequence, and performing gray level processing to further eliminate the interference in the images;
step 6: performing threshold segmentation on the images processed in the step 5 one by one according to a sampling sequence, and identifying pixel points capable of representing tracer particles in each image; calculating the proportion of pixel points capable of expressing trace particles to total pixel points of the images to calculate the trace particle concentration calculation value of each image at the sampling moment;
and 7: the residence time distribution of the tracer particles in the fluidized bed is represented by the probability density function e (t) of the tracer particles:
in the formula: c (t)i) Is shown at tiAt the moment of time the actual concentration value, at, of the tracer particles in the sampleiRepresenting the time interval of two sampling processes;
wherein, satisfy between tracer particle concentration calculated value and the tracer particle concentration actual value:
ccal＝k*creal
in the formula: the coefficient k depends on the choice of the color threshold, ccalRepresenting a calculated value of the concentration of tracer particles, calculated according to step 6, crealRepresenting the actual value of the concentration of tracer particles.
Further, in the step 1, the solid bed material is semitransparent glass beads with the diameter of 0.3-0.35 mm; the tracer particles are translucent glass beads dyed with a carmine reagent.
Further, in the HSV color space in step 5, the magnification of S value is 1.9 and the magnification of V value is 1.7.
Further, in the RGB color space described in step 5, the grayscale processing uses an imadjust function, and the grayscale processing range is set to (0.35, 0.7).
Further, the color threshold r-g-b in step 5 is set.
Further, the sampling time in step 2 is prolonged along with the fluidization progress of the solid bed material, and the sampling is carried out in four batches: the sampling time of the first batch of samples is 30s, the sampling time of the second batch of samples is 1min, the sampling time of the third batch of samples is 2min, and the sampling time of the fourth batch of samples is 3 min.
Further, the light source in step 4 is a white cold light source.
Further, the threshold segmentation method in step 6 specifically includes: firstly, respectively setting a threshold R of an R value, a threshold G of a G value and a threshold B of a B value according to R, G, B values corresponding to the colors of tracer particles to obtain a threshold segmentation condition capable of representing the colors of the tracer particles; and then, judging whether R, G, B values of all pixel points in the image meet a threshold segmentation condition or not so as to screen out pixel points capable of representing the tracer particles, wherein the pixel points capable of representing the tracer particles are the pixel points meeting the threshold segmentation condition.
Further, the threshold segmentation condition of white is R > R, G > G, B > B; the black threshold segmentation conditions are R < R, G < G, B < B; red threshold segmentation conditions are R > R, G < G, B < B; the green threshold segmentation conditions are R < R, G > G, B < B; the blue threshold segmentation conditions are R < R, G < G, B > B; the yellow threshold segmentation conditions are R > R, G > G, and B < B.
The invention also aims to provide a test bed for realizing the method for measuring the residence time distribution of the solid particles in the fluidized bed based on the image recognition principle, which comprises a fluidized bed, a tracer particle bin, a material bin, a spiral feeder, a bag-type dust collector, a sampler, an air supply system and an oil-water separator; wherein: two vertical baffles are arranged in the fluidized bed, and a feed inlet and a sampling port are respectively arranged on the fluidized bed; a sample outlet pipeline of the tracer particle bin is combined with a sample outlet pipeline of the material bin and then communicated with a feed inlet of the fluidized bed, a particle control valve is installed on the sample outlet pipeline of the tracer particle bin, and the sample outlet pipeline of the material bin is connected with a power output end of the spiral feeder; the bag-type dust collector is arranged at the top of the fluidized bed, the bottom of the fluidized bed is provided with an air distribution plate, an air box is arranged below the air distribution plate, and the air box is communicated with an air outlet of the air supply system through an air rotor flow meter and an oil-water separator in sequence; the middle part position department of grid plate installs the discharge tube, and the discharge tube is worn out the bellows setting, and installs the bleeder valve on the discharge tube, and the sample connection of fluidized bed passes through the sample pipeline and is connected with the sampler, installs the sample valve on the sample pipeline.
Compared with the prior art, the technical scheme adopted by the invention has the following technical effects:
according to the method, all pictures can be processed in batch through a computer program only by photographing the sample under the same light source condition, the concentration of the colored tracer particles in the pictures is obtained, the operation is simple, the efficiency is high, the number of error-generating links is small, and the experiment efficiency and the experiment precision can be greatly improved.
Drawings
FIG. 1 is an original drawing of samples of tracer particles of different concentrations according to the present invention;
FIG. 2 is a diagram illustrating the visual effect of the step 5 image processing step according to the present invention;
FIG. 3 is an image of a sample of tracer particles of different concentrations after image processing in step 6 according to the present invention;
fig. 4 is a relationship between calculated concentration values and actual concentration values of tracer particles in images after different threshold value treatments, wherein 50, 100, 128, 150 and 200 are taken as threshold values r and g and b respectively;
FIG. 5 is a design drawing of a laboratory bench system according to the present invention;
FIG. 6 is an average value of spectrophotometric measurements and three sets of image measurements in accordance with the present invention.
Detailed Description
The present invention will be described in further detail with reference to specific examples, which are provided for illustration only and are not intended to limit the scope of the present invention.
As shown in fig. 1 to 6, the method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle of the present invention comprises the following steps:
step 1: tracer particle addition
When the fluidization of the solid bed material in the fluidized bed reaches a steady state (namely the feeding and discharging rates are equal), adding tracer particles; the color of the tracer particles is different from that of the solid bed material, and the mass proportion of the tracer particles is not more than 5% of that of the solid bed material;
step 2: sampling
Starting timing when the tracer particles are added into the fluidized bed; sampling from the fluidized bed for a plurality of times according to the preset sampling time until only solid bed materials exist in the taken sample and no tracer particles appear;
the sampling time is prolonged along with the fluidization progress of the solid bed material, and the sampling is carried out in four batches: the sampling time of the first batch of samples is 30s, the sampling time of the second batch of samples is 1min, the sampling time of the third batch of samples is 2min, and the sampling time of the fourth batch of samples is 3 min.
And step 3: sample is mixed evenly
Fully stirring the samples taken out in the step 2 respectively to ensure that the tracer particles contained in each sample can be uniformly mixed with the solid bed material in each sample;
and 4, step 4: photographing device
Photographing the uniformly mixed samples obtained in the step 3 one by one under the same light source condition according to the sampling sequence to obtain corresponding images, as shown in fig. 1;
and 5: image background elimination, color enhancement, and gray scale adjustment
The image shot in step 4 generally has larger noise interference, the shape and color of the tracing particles are not obvious, and the error of direct identification is larger. Therefore, in order to improve the accuracy of the identification of the tracer particles in the picture, background elimination and color enhancement processing are required to be carried out on the particle images before identification.
Therefore, the core of the step is to perform image processing on the images obtained in step 4 in HSV color space one by one according to the sampling sequence, so as to eliminate the semitransparent background of each image and enhance the color of the tracer particles in each image.
Specifically, the color space of the image shot in step 4 is first converted from the RGB color space to the HSV color space, and then the S, V values of the image are respectively amplified by a certain factor in the HSV color space to enhance the color of the tracer particles in the image and eliminate the impurity interference in the background, and then the image is converted back to the RGB color space. And finally, adjusting the gray scale range of the image through an Imadjust function so as to further highlight the shape of the red tracer particles. In this step, the S value is amplified by 1.9 times, the V value is amplified by 1.7 times, and the setting size of the Imadjust function is (0.3, 0.75). The image processing effect of each step is shown in fig. 2, and the image processing effect of fig. 1 is shown in fig. 3. The original image has a gray scale in the range of 0-255, such as Imadjust (0.3,0.75) indicating that gray scale values smaller than 255 × 0.3 are set to 0 and gray scale values larger than 255 × 0.75 are set to 255.
Step 6: obtaining a calculated concentration of tracer particles
In an image display apparatus, each image is composed of a number of small square dots of the same color, which are the smallest units, pixels, constituting the image. A color space is a system for displaying the colors of pixels. The RGB color space is one of the most commonly used color spaces in image processing, and color information acquired by image acquisition equipment, storage modes of most digital pictures, and color image display equipment all adopt the RGB color space. RGB refers to red (red), green (green) and blue (blue), and the whole color space is formed by mixing the three colors according to different proportions, so the three colors are called three primary colors. In the RGB color space, the three primary colors have 256 levels each, and the numerical value is taken from 0 to 255, which is called color value, and the larger the numerical value, the stronger the color light. The color of each pixel can be represented by a color value (R, G, B), such as (0,0,0) representing no color light, i.e. black; (255,255,255) indicates that all three primary colors are brightest and are superimposed to white; the RGB values corresponding to the three primary colors red, green and blue are (255,0,0), (0,255,0) and (0, 255), respectively. However, the ability of the naked eye to distinguish fine changes in color is limited, and for example, (250,0,0), (255,1,0) and (255,0,1) are both represented as red in the naked eye and are difficult to distinguish. For real objects, colors composed of a large R value, a small G value and a B value can be seen as red by naked eyes, and the same is true for other colors. Therefore, a threshold segmentation method is often used to identify a certain color pixel in an image, and if RGB color thresholds are R, G, and B, pixels whose color values satisfy the range of the corresponding threshold of the color are distinguished, for example, the threshold segmentation condition for distinguishing red pixels is generally R > R, G < G, and B < B, and the size of the color threshold can be set according to the actual situation. For common color particles, the threshold setting conditions are as in table 1.
| Colour(s) | Corresponding to RGB value | Threshold segmentation condition |
| White colour | (255,255,255) | R>r、G>g、B>b |
| Black color | (0,0,0) | R<r、G<g、B<b |
| Red colour | (255,0,0) | R>r、G<g、B<b |
| Green colour | (0,255,0) | R<r、G>g、B<b |
| Blue color | (0,0,255) | R<r、G<g、B>b |
| Yellow colour | (255,255,0) | R>r、G>g、B<b |
TABLE 1
Therefore, the core of the step is that after the images processed in the step 5 are led into the RGB color space one by one according to the sampling sequence, pixel points capable of representing tracer particles in each image are identified by adopting a threshold segmentation method; the concentration calculation value of the tracer particles at the sampling moment corresponding to each image can be calculated one by calculating the proportion of the pixel points capable of expressing the tracer particles to the total pixel points of the image.
The threshold segmentation method specifically comprises the following steps: firstly, respectively setting a threshold R of an R value, a threshold G of a G value and a threshold B of a B value according to R, G, B values corresponding to the colors of tracer particles to obtain a threshold segmentation condition capable of representing the colors of the tracer particles; and then, judging whether the R, G, B value of each pixel point in the image meets a threshold segmentation condition or not so as to screen out pixel points capable of representing the tracer particles, wherein the pixel points capable of representing the tracer particles are the pixel points meeting the threshold segmentation condition.
And 7: obtaining the residence time distribution of the tracer particles in the fluidized bed
The residence time distribution of the tracer particles in the fluidized bed is represented by the probability density function e (t) of the tracer particles:
in the formula: c (t)i) Is shown at tiAt the moment of time the actual concentration value, at, of the tracer particles in the sampleiRepresenting the time interval of two sampling processes.
Wherein, the steps 1 to 6 are repeated by configuring samples with different concentrations of the tracer particles, the relationship between the calculated value of the concentration of the tracer particles and the actual concentration value of the tracer particles is calibrated, a linear relationship is found to be basically satisfied, as shown in fig. 4, and the linear relationship is verified, and the relationship between the calculated value of the concentration of the tracer particles and the actual concentration value of the tracer particles is specifically expressed as follows:
ccal＝k*creal
in the formula: the coefficient k depends on the choice of the color threshold, ccalRepresenting a calculated value of the concentration of tracer particles, calculated according to step 6, crealRepresenting the actual value of the concentration of tracer particles.
Example 1
The invention relates to a method for measuring the residence time distribution of solid particles in a fluidized bed based on an image recognition principle, which comprises the following steps:
step 1: translucent glass beads with a diameter of 0.3-0.35mm are used as solid bed material and are dyed red by a carmine reagent as tracer particles. Because the addition amount of the tracer particles is generally within 5% of the discharge amount, only samples with the tracer particle concentration of 1%, 2%, 3% to 5% need to be prepared. Three groups of samples are prepared, all the samples are fully stirred and photographed under the same light source condition, the pictures are led into a computer, and the original pictures of the first group of tracer particle samples with different concentrations are shown in figure 1.
Step 2: the image taken in step 1 is processed by a MATLAB program. In an HSV color space, the S value of the image is amplified by 1.9, the V value of the image is amplified by 1.7 times to achieve the purposes of eliminating the semitransparent background and enhancing the color of the tracer particles, the gray range of the image is adjusted through an Imadjust function to further highlight the shape of the red tracer particles, and the Imadjust value is (0.35, 0.7). The image processing step corresponds to the visual effect shown in fig. 2, and the final image of the first set of tracer particle samples with different concentrations after image processing is shown in fig. 3. Macroscopically, in a finally processed sample image, a semitransparent material background is eliminated, and the sample image can be almost regarded as only consisting of red tracer particles and a white background, and the positions and the shapes of the tracer particles are clear and visible, so that the feasibility and the accuracy of image distinguishing are greatly improved.
It should be noted that the excessive V-value amplification may result in excessive brightness, and the edge color of part of the red tracer particles may become lighter or even be eliminated, so the V-value amplification factor should be adjusted according to the material condition.
Step 3: satisfying R for color value RGB in red threshold segmentation process of RGB color space>r、G<g、B<And b, regarding the pixel points as pixel points representing red tracer particles. The three color thresholds are set to be equal, i.e., r ═ g ═ b, and the results of distinguishing the three groups of images by setting different thresholds (50/100/128/150/200 respectively) are shown in fig. 4. Obviously, the calculated concentration value and the actual concentration value of each threshold value in the present example maintain a good linear relationship, and the linear relationship can be ccal＝k*crealMeaning that the coefficient k depends on the choice of threshold, ccalRepresents a calculated value of concentration, crealRepresenting the actual value of the concentration. And the error of the three groups of images is small, and the repeatability is high.
From this, it can be seen that by this step, the concentration value of the tracer particles in the sample can be calculated.
And 4, step 4: according to the concentration value of the tracer particles calculated in step 3, the residence time distribution of the tracer particles in the fluidized bed can be represented by the probability density function e (t) of the tracer particles:
in the formula: c (t)i) Is shown at tiAt the moment of the concentration value, at, of the tracer particles in the sampleiRepresenting the time interval of two sampling processes.
According to the expression, the probability density function E (t) of the trace particles is not influenced by the value of k, and the difference of concentration calculation values caused by different thresholds is eliminated in the calculation of E (t). In other words, the selection of the threshold value does not theoretically affect the measurement of the RTD within the calibration range herein.
Example 2
Step 1: and designing and building a test bed, wherein the design drawing of the test bed is shown in figure 5, and the sizes of the test bed are shown in table 2.
| Height of bed body | Length of bed body | Width of bed body | Number of baffles |
| 0.9m | 0.22m | 0.11 |
2 |
| Length of baffle | Number of openings of funnel cap | Number of wind caps of wind distribution plate | Diameter of opening of blast cap |
| 0.9m | 6 | 12 | 0.002m |
TABLE 2
As shown in fig. 5, the test bed comprises a fluidized bed, a tracer particle bin, a material bin, a spiral feeder, a bag-type dust collector, a sampler, an air supply system and an oil-water separator; the fluidized bed is respectively provided with a feed inlet and a sampling port; a sample outlet pipeline of the tracer particle bin is combined with a sample outlet pipeline of the material bin and then communicated with a feed inlet of the fluidized bed, a particle control valve is installed on the sample outlet pipeline of the tracer particle bin, and the sample outlet pipeline of the material bin is connected with a power output end of the spiral feeder; the bag-type dust collector is arranged at the top of the fluidized bed, the bottom of the fluidized bed is provided with an air distribution plate, an air box is arranged below the air distribution plate, and the air box is communicated with an air outlet of the air supply system through an air rotor flow meter and an oil-water separator in sequence. The middle part position department of grid plate installs the discharge tube, and the discharge tube is worn out the bellows setting, and installs the bleeder valve on the discharge tube, and the sample connection of fluidized bed passes through the sample pipeline and is connected with the sampler, installs the sample valve on the sample pipeline.
The fluidized bed body is made of colorless transparent organic glass, the cross section of the fluidized bed body is 0.22mx0.11m, and the height of the fluidized bed body is 0.9 m; in order to regulate and control the residence time of the particles in the fluidized bed, two vertical baffles are arranged, the length of the baffles is 0.18m, and the height of the baffles is 0.9 m.
Laboratory test articleThe material adopts GeldartB translucent glass beads with the average particle size of 0.344mm and the real density of 2500kg/m3. Using carmine reagent (acid Red 18, C)20H11N2Na3O10S3) And dyeing the material to obtain the tracer particles.
Step 2: the resistance characteristics of the fluidized bed were measured, and the critical fluidization velocity of the material was measured to be 0.112 m/s. Setting the gas velocity as twice of the fluidization velocity, adding 5.4kg of material for fluidization, feeding at the speed of 10.8kg/h through a spiral feeder after full fluidization, controlling the discharging speed by adjusting the opening of a discharging valve, enabling the feeding speed and the discharging speed to be equal, leading the fluidization to reach a stable state, keeping the material holding amount in a bed basically unchanged, and adding 200g of red tracer particles after balance.
And step 3: the timing was started while the red tracer particles were added and sampling was started at the sampling port and the time of sampling was recorded. Setting the sampling duration of each sample to be 30s according to experimental experience; the first 16 samples were sampled every 30s, then 8 samples every 1min, then 4 samples every 2min, then 4 samples every 3min, and finally every 4min until no tracer particles appeared in the sample cup, and the experiment was completed. The sampling interval needs to be as short as possible during periods of time when the concentration of tracer particles changes drastically. As fluidization proceeds, the tracer particle concentration becomes less and less over time, so the sampling interval can be gradually relaxed.
And 4, step 4: three replicates were performed according to steps 2, 3.
And 5: fully stirring all samples respectively, taking pictures according to a sampling sequence under the condition of the same light source (such as a white cold light source), introducing a computer program for image processing and calculation, setting the threshold values of three colors to be 128, obtaining the concentration of tracer particles in each sample through a concentration calculation value according to the linear relation of figure 4, and obtaining a density function E (t) of residence time distribution according to sampling time processing data.
In order to check the accuracy of the image recognition result, the measurement result of a widely used spectrophotometer method is compared with the image method result. The concentration characteristics of the tracer particles are not changed after the sample is stirred and photographed by the image method, so that the spectrophotometry of the sample can be measured after photographing. After photographing, sequentially weighing, washing and preparing the three groups of experimental samples, and detecting the absorbance of the solution. And calculating the mass of the tracer particles in the sample according to the linear relation between the calibrated absorbance and the mass of the tracer particles, further obtaining the concentration of the tracer particles in the sample, and taking the average value of three experiments as a result. The results of the measurements of both methods are shown in fig. 6. Obviously, the measurement result of the image method is very close to that of the traditional spectrophotometer, and the experimental result of the three times of repeated experiments is also approximately coincident, which shows that the image method has better accuracy and repeatability. In addition, the image method is used as a semi-continuous measuring method, the advantages of simple experimental device, low cost, high efficiency, accuracy and good repeatability of the continuous measuring method are combined, and the experimental efficiency can be greatly improved by calculating the image concentration through a computer program.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
The above embodiments are only for illustrating the technical idea of the present invention, and the protection scope of the present invention is not limited thereby, and any modifications made on the basis of the technical scheme according to the technical idea of the present invention fall within the protection scope of the present invention. While the embodiments of the present invention have been described in detail, the present invention is not limited to the above embodiments, and various changes can be made without departing from the spirit of the present invention within the knowledge of those skilled in the art.
Claims (9)
1. A method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle is characterized by comprising the following steps:
step 1: adding tracer particles when the fluidization of solid bed materials in the fluidized bed reaches a stable state; the color of the tracer particles is different from that of the solid bed material, and the mass proportion of the tracer particles is not more than 5% of that of the solid bed material;
step 2: starting timing when the tracer particles are added into the fluidized bed; sampling from the fluidized bed for a plurality of times according to the preset sampling time until only solid bed materials exist in the taken sample and no tracer particles appear;
and step 3: fully stirring the samples taken out in the step 2 respectively to ensure that the tracer particles contained in each sample can be uniformly mixed with the solid bed material in each sample;
and 4, step 4: photographing the uniformly mixed samples in the step (3) one by one under the same light source condition according to the sampling sequence to obtain corresponding images;
and 5: carrying out image processing on the images obtained in the step 4 in an HSV color space one by one according to the sampling sequence so as to eliminate the semitransparent background of each image and enhance the color of the tracer particles in each image; converting the processed images in the HSV color space into RGB color spaces one by one according to the sequence, and performing gray level processing to further eliminate the interference in the images;
step 6: performing threshold segmentation on the images processed in the step 5 one by one according to a sampling sequence, and identifying pixel points capable of representing tracer particles in each image; calculating the proportion of pixel points capable of expressing trace particles to total pixel points of the images to calculate the trace particle concentration calculation value of each image at the sampling moment;
and 7: the residence time distribution of the tracer particles in the fluidized bed is represented by the probability density function e (t) of the tracer particles:
in the formula: c (t)i) Is shown at tiAt the moment of time the actual concentration value, at, of the tracer particles in the sampleiRepresents two samples overThe time interval of the program;
wherein, satisfy between tracer particle concentration calculated value and the tracer particle concentration actual value:
ccal＝k*creal
in the formula: the coefficient k depends on the choice of the color threshold, ccalRepresenting the calculated value of the concentration of the tracer particles, and calculating according to the step 6; c. CrealRepresenting the actual value of the concentration of tracer particles.
2. The method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle as claimed in claim 1, wherein in the step 1, the solid bed material is translucent glass beads with the diameter of 0.3-0.35 mm; the tracer particles are translucent glass beads dyed with a carmine reagent.
3. The method for measuring the residence time distribution of solid particles in the fluidized bed based on the image recognition principle as claimed in claim 1, wherein in the HSV color space, the magnification of S value is 1.9 and the magnification of V value is 1.7 in step 5; in the RGB color space described in step 5, the gray processing adopts Imadjust function, and the gray processing range is set to (0.35, 0.7).
4. The method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle as claimed in claim 1, wherein the color threshold r-g-b in step 5 is set.
5. The method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle as claimed in claim 1, wherein the sampling time in step 2 is prolonged along with the fluidization progress of the solid bed material, and the sampling is performed in four batches: the sampling time of the first batch of samples is 30s, the sampling time of the second batch of samples is 1min, the sampling time of the third batch of samples is 2min, and the sampling time of the fourth batch of samples is 3 min.
6. The method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle as claimed in claim 1, wherein the light source in the step 4 is a white cold light source.
7. The method for measuring the residence time distribution of solid particles in the fluidized bed based on the image recognition principle as claimed in claim 1, wherein the threshold segmentation method in step 6 is specifically as follows:
firstly, respectively setting a threshold R of an R value, a threshold G of a G value and a threshold B of a B value according to R, G, B values corresponding to the colors of tracer particles so as to obtain a threshold segmentation condition capable of representing pixel points of the colors of the tracer particles; and then, judging whether the R, G, B value of each pixel point in the whole image meets a threshold segmentation condition or not so as to screen out pixel points capable of representing the tracer particles, wherein the pixel points capable of representing the tracer particles are the pixel points meeting the threshold segmentation condition.
8. The method for measuring the residence time distribution of solid particles in a fluidized bed based on the image recognition principle as claimed in claim 7, wherein the threshold segmentation condition of white color is R > R, G > G, B > B; the black threshold segmentation conditions are R < R, G < G, B < B; red threshold segmentation conditions are R > R, G < G, B < B; the green threshold segmentation conditions are R < R, G > G, B < B; the blue threshold segmentation conditions are R < R, G < G, B > B; the yellow threshold segmentation conditions are R > R, G > G, and B < B.
9. A test bed for realizing the method for measuring the residence time distribution of the solid particles in the fluidized bed based on the image recognition principle, which is disclosed by claim 1, is characterized by comprising the fluidized bed, a tracer particle bin, a material bin, a spiral feeder, a bag-type dust collector, a sampler, a gas supply system and an oil-water separator; wherein:
two vertical baffles are arranged in the fluidized bed, and a feed inlet and a sample are respectively arranged on the fluidized bed;
a sample outlet pipeline of the tracer particle bin is combined with a sample outlet pipeline of the material bin and then communicated with a feed inlet of the fluidized bed, a particle control valve is installed on the sample outlet pipeline of the tracer particle bin, and the sample outlet pipeline of the material bin is connected with a power output end of the spiral feeder;
the bag-type dust collector is arranged at the top of the fluidized bed, the bottom of the fluidized bed is provided with an air distribution plate, an air box is arranged below the air distribution plate, and the air box is communicated with an air outlet of the air supply system through an air rotor flow meter and an oil-water separator in sequence;
the middle part position department of grid plate installs the discharge tube, and the discharge tube is worn out the bellows setting, and installs the bleeder valve on the discharge tube, and the sample connection of fluidized bed passes through the sample pipeline and is connected with the sampler, installs the sample valve on the sample pipeline.
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