Ice crystal melting rate measurement system and method

Abstract

The present invention discloses a system and method for measuring the melting rate of ice crystals, which are used to calculate the melting rate of ice crystals of different particle sizes during the melting process. The method includes: obtaining an image of ice crystals; reading the original image of the ice crystals; copying the original image; performing median filtering to reduce noise; converting to a grayscale image; automatically identifying circular areas; deleting the background outside the circular area; adaptive histogram equalization; adaptive local threshold binarization; drawing the outline of the ice core using a magnetic lasso; and calculating the melting rate of ice crystals using an ice crystal melting rate equivalent model. This method is a direct measurement method that directly identifies the ice-water interface through an image and calculates the melting rate. At the same time, since the surface tension suspension method is used to perform the melting experiment, the vibration or flipping of ice crystal particles due to the influence of the external environment is greatly reduced, and the measurement results are more stable.

Description

Technical Field

[0001] The invention relates to an ice crystal melting rate measurement system and method. Background Art

[0002] The problem of aircraft icing has been recognized almost since the beginning of modern flight. The first discovery and study involved the freezing of supercooled water, which can occur on or within various aircraft components. However, since the 1990s, numerous engine thrust loss incidents have occurred at altitudes above 6.7 km, where supercooled water droplets are unlikely to exist. These incidents are primarily caused by ice crystals ingested by the engine and then adhering to and freezing. Once drawn into the engine, the ice crystals exchange heat with the hot air flow within the flow path, melting into a mixture of ice and water or a mixture of ice crystals and liquid droplets. These ice crystals then collide with the engine and adhere to the surface. Adherent ice accumulation can lead to reduced engine performance, damage to engine components, and even serious hazards such as engine surge and shutdown at high altitude.

[0003] Ice crystal impact, adhesion, and ice accumulation are closely related to ice crystal melt rates. Therefore, characterizing ice crystal melt rates during phase transitions is fundamental to understanding the mechanisms of ice crystal icing within engines and crucial for accurately predicting ice crystal icing and preventing and deicing. However, due to the small size of ice crystals and the lack of clear distinction between the ice and water phases, measuring and processing their melt rates presents a significant experimental challenge. Summary of the Invention

[0004] In view of this, the present invention provides an ice crystal melting rate measurement system and method, which can be used to calculate the melting rate of ice crystals with different particle sizes during the melting process.

[0005] In order to solve the above problems, in a first aspect, an embodiment of the present invention provides a method for measuring ice crystal melting rate, which is special in that it includes the following steps:

[0006] Step 1: Get a picture of ice crystals;

[0007] Step 2: Read the original ice crystal image;

[0008] Step 3: Copy the original image;

[0009] Step 4: Median filtering for noise reduction;

[0010] Step 5: Convert to grayscale image;

[0011] Step 6: Automatically identify the circular area;

[0012] Step 7. Delete the background outside the circular area;

[0013] Step 8: Adaptive histogram equalization;

[0014] Step 9: Adaptive local threshold binarization;

[0015] Step 10: Use magnetic lasso to draw the ice core outline;

[0016] Step 11, calculating the melting rate of ice crystals using an ice crystal melting rate equivalent model;

[0017] The ice crystal melting rate equivalent model is specifically:

[0018] Assuming that the ice core is a sphere and that a water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated as follows:

[0019] First calculate the equivalent radius of the ice core:

[0020]

[0021] Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program.

[0022] Define the volume fraction of the ice core η v :

[0023]

[0024] Where: η v ——Volume proportion of ice core; r——Radius of ice crystal / px, obtained when ice crystal position is identified by ice core water film interface identification program.

[0025] The ratio of ice core mass to total ice crystal mass is defined as solid ice content:

[0026]

[0027] Where: η m,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 .

[0028] Finally, the definition of ice crystal melting rate is given:

[0029]

[0030] Where: η m,w ——Ice crystal melting rate.

[0031] Furthermore, the step 1 specifically includes: extracting images of ice crystals at the same time intervals during the melting process through Adobe Premiere Pro 2022, and storing all the same set of ice crystal images in the same folder;

[0032] Furthermore, the step 2 is specifically as follows: batch read the pictures in the folder of the previous step through Python code and name them in chronological order, and compile the code through the software Anaconda Navigator.

[0033] Furthermore, the step 3 is specifically as follows: copying the image read in the previous step through the code, and recording the original image for subsequent calculation and comparison;

[0034] Furthermore, the step 4 is specifically: implementing median filtering through Python code to eliminate noise.

[0035] Furthermore, the step 5 is specifically as follows: converting the image from the RGB color space to the gray space through code, that is, generating a grayscale image to facilitate calculations in subsequent steps.

[0036] Furthermore, step 6 specifically implements automatic identification of circular ice crystal areas through code: using the Hough gradient method, first use Canny edge detection on the grayscale image to find possible circles, and for each point on the circumference, calculate its gradient. Based on the gradient, a tangent about this point can be made. The direction perpendicular to the tangent is the gradient direction. The intersection of the gradient directions of each point is the center of the circle, and then the radius can be determined based on the position of the center of the circle.

[0037] Furthermore, step 8 is specifically to implement adaptive histogram equalization through code to improve image contrast: first, the image is divided into 8 vertical and 8 horizontal blocks, totaling 64 blocks, and then each block is subjected to histogram equalization processing, that is, an image block with a known grayscale probability density distribution is transformed into a new image block with a uniform grayscale probability density distribution, and finally spliced into a new image.

[0038] Furthermore, the step 9 is specifically as follows: binarizing the image using an adaptive local threshold, wherein the threshold of each pixel in the image is different and is determined by the weighted average of the image pixels in its field, and the interface is more clearly distinguished after binarization.

[0039] Furthermore, step 10 is specifically as follows: importing the binary image obtained in the previous step into Adobe Photoshop 2022, using the magnetic lasso to draw the ice core outline, and storing it separately.

[0040] In a second aspect, based on the above-mentioned ice crystal melting rate measurement method, the present invention further proposes an ice crystal melting rate measurement system, which is special in that it includes:

[0041] Image acquisition module, image processing module and ice crystal melting rate calculation module;

[0042] The image acquisition module is used to acquire pictures of ice crystals;

[0043] The image acquisition module is used to extract images of ice crystals at the same time intervals during the melting process through Adobe Premiere Pro 2022, and the same group of ice crystal images are all stored in the same folder.

[0044] The image processing module is used to process the ice crystal image obtained by the image acquisition module and finally draw the ice core outline. The ice crystal melting rate calculation module is used to calculate the area of the ice core through the ice core outline to obtain the ice core equivalent radius, and then calculate the ice crystal melting rate, which specifically includes:

[0045] The melting rate of ice crystals is calculated using the ice crystal melting rate equivalent model;

[0046] The ice crystal melting rate equivalent model is specifically:

[0047] Assuming that the ice core is a sphere and that a water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated as follows:

[0048] First calculate the equivalent radius of the ice core:

[0049]

[0050] Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program.

[0051] Define the volume fraction of the ice core η v :

[0052]

[0053] Where: η v ——Volume proportion of ice core; r——Radius of ice crystal / px, obtained when ice crystal position is identified by ice core water film interface identification program.

[0054] The ratio of ice core mass to total ice crystal mass is defined as solid ice content:

[0055]

[0056] Where: ηm,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 .

[0057] Finally, the definition of ice crystal melting rate is given:

[0058]

[0059] Where: η m,w ——Ice crystal melting rate.

[0060] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the ice crystal melting rate measurement method according to the first aspect is implemented.

[0061] Compared with the prior art, the ice crystal melting rate measurement system and method proposed in the present invention have at least the following beneficial effects:

[0062] 1) More intuitive and stable measurement of the melting rate of tiny ice crystals. This method is a direct measurement method that directly identifies the ice-water interface through images and calculates the melting rate. Furthermore, the use of surface tension suspension for melting experiments greatly reduces the risk of ice crystal particles vibrating or flipping due to external environmental influences, resulting in more stable measurement results.

[0063] 2) This method is more convenient and can quickly process images in batches, and obtain the melting rate results through automatic calculation by the program.

[0064] 3) The results are more accurate and reliable. The uncertainty of ice crystal radius recognition is ±2px, and the uncertainty of ice core equivalent radius recognition is ±5px. According to the melt rate calculation formula, the uncertainty of melt rate measurement is 7.8%.

[0065] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and implement it according to the contents of the specification, the following is a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0067] Figure 1The ice crystal image is obtained by the image acquisition module;

[0068] Figure 2 It is a processing flow chart of the image processing module;

[0069] Figure 3 This is the effect diagram of the image processing module during the processing process;

[0070] Figure 4 is the equivalent model of ice crystal melting rate;

[0071] Figure 5 These are the ice crystal melting results at different times after the image processing module processes a certain working condition. DETAILED DESCRIPTION

[0072] To further illustrate the technical means and effects employed by the present invention to achieve its intended objectives, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention is provided in conjunction with the accompanying drawings and preferred embodiments. In the following description, different references to "one embodiment" or "embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0073] The particle size of ice crystals is very small, and the distinction between ice and water phases is not obvious, so the measurement and processing of ice crystal melting rate is a major difficulty in the experiment. The present invention proposes a new measurement method and system for ice crystal melting rate by shooting images of ice crystal melting process, obtaining ice core contours through image recognition, and using melting rate equivalent model to calculate ice crystal melting rate. The measurement principle of the present invention is: the solubility of air in ice is much lower than that of water, so during the freezing process of droplets, excess gas will be expelled into the unfrozen liquid, and light will be scattered by tiny bubbles inside the ice crystals, making the ice crystals opaque; when the ice crystals melt, the air in the melted area will dissolve in the water and appear transparent, while the unmelted area of the ice crystals remains opaque, that is, the solid phase and liquid phase of the ice crystals will present different appearances during the melting process. The experimental observation diagrams of complete freezing and partial melting of ice crystals are shown in the following figure. Figure 1 shown.

[0074] Example 1

[0075] This embodiment provides a method for measuring ice crystal melting rate. Figure 2 , including the following steps:

[0076] Step 1: Get a picture of ice crystals.

[0077] Step 1 is specifically as follows: using Adobe Premiere Pro 2022 to extract images of ice crystals taken by a microscope at the same time intervals during the melting process, and the same group of ice crystal images are all stored in the same folder.

[0078] Step 2: Read the original ice crystal image.

[0079] Step 2 is as follows: use Python code to batch read the images in the folder in the previous step and name them in chronological order, and compile the code using the software Anaconda Navigator.

[0080] Step 3: Copy the original image.

[0081] Step 3 is as follows: copy the image read in the previous step through the code, and record the original image for subsequent calculation and comparison.

[0082] Step 4: Median filtering for noise reduction;

[0083] Step 4 is to implement median filtering in Python to eliminate noise. This is done by taking the pixel values of the current pixel and its surrounding pixels (there is an odd number of pixels), sorting them, and then taking the pixel value in the middle as the pixel value of the current pixel.

[0084] Step 5: Convert to grayscale image;

[0085] Step 5 is specifically as follows: converting the image from RGB color space to gray space through code, that is, generating a grayscale image to facilitate calculations in subsequent steps.

[0086] Step 6: Automatically identify the circular area;

[0087] Step 6 involves implementing automatic identification of circular ice crystal regions through code. Using the Hough gradient method, Canny edge detection is first applied to the grayscale image to identify possible circles. For each point on the circle, the gradient is calculated. Based on the gradient, a tangent line about that point is drawn. The direction perpendicular to the tangent line is the gradient direction. The intersection of the gradient directions at each point is the center of the circle. The radius of the circle is then determined based on the position of the center.

[0088] Step 7. Delete the background outside the circular area.

[0089] Step 7 is specifically as follows: The purpose of this step is to retain the circular ice crystal area identified in the previous step and delete other background areas to prevent them from interfering with subsequent processing.

[0090] Step 8: Adaptive histogram equalization.

[0091] Step 8 is as follows: To improve image contrast, adaptive histogram equalization is implemented through code. The image is first divided into 64 blocks (8 vertical and 8 horizontal). Each block is then subjected to histogram equalization. This transforms an image block with a known grayscale probability density distribution into a new image block with a uniform grayscale probability density distribution. The blocks are then stitched together to form a new image.

[0092] Step 9: Adaptive local threshold binarization.

[0093] Step 9 is specifically as follows: binarize the image using an adaptive local threshold. The threshold of each pixel in the image is different in the adaptive threshold. The threshold is determined by the weighted average of the image pixels in its field. After binarization, the distinction between the phase interfaces is more obvious.

[0094] Step 10: Use the magnetic lasso to draw the outline of the ice core.

[0095] Step 10 is as follows: import the binary image obtained in the previous step into Adobe Photoshop 2022, use the magnetic lasso to draw the ice core outline, and save it separately. Figure 3 The ice core outline drawn by the lasso is exactly the maximum envelope of all bubble edges.

[0096] Step 11: Calculate the melting rate of ice crystals using an ice crystal melting rate equivalent model.

[0097] The ice crystal melting rate can be calculated through the ice core contour, but in actual experiments, the ice core is not a sphere. Therefore, the present invention proposes an ice crystal melting rate equivalent model to calculate the ice crystal melting rate.

[0098] The ice crystal melting rate equivalent model is specifically:

[0099] See also Figure 4 Assuming that the ice core is a sphere and the water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated:

[0100] First calculate the equivalent radius of the ice core:

[0101]

[0102] Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program.

[0103] Define the volume fraction of the ice core η v :

[0104]

[0105] Where: η v ——Volume proportion of ice core; r——Radius of ice crystal / px, obtained when ice crystal position is identified by ice core water film interface identification program.

[0106] The ratio of ice core mass to total ice crystal mass is defined as solid ice content:

[0107]

[0108] Where: η m,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 .

[0109] Finally, the definition of ice crystal melting rate is given:

[0110]

[0111] Where: η m,w ——Ice crystal melting rate.

[0112] Combining the above ice crystal ice core contour recognition method with ice crystal melting rate calculation method, AnacondaNavigator was used to write a Python program to batch process the ice core contours of the corresponding image ice crystals and calculate the melting rate of the ice crystals. Some processed images are as follows Figure 5 shown.

[0113] In this embodiment, steps 2-10 are all processed using Python code developed based on the OpenCV library and compiled in the Anaconda Navigator software. The calculation process of step 11 is also implemented by the developed Python code, which automatically reads the image saved in step 10 and calculates the melt rate.

[0114] Example 2

[0115] Correspondingly, the present invention also provides an ice crystal melting rate measurement system for implementing one or more aspects of the above method.

[0116] The ice crystal melting rate measurement system includes an image acquisition module, an image processing module and an ice crystal melting rate calculation module.

[0117] The image acquisition module is used to acquire images of ice crystals. Specifically, it is used to extract images of ice crystals at the same time interval during the melting process through Adobe Premiere Pro 2022, and the same set of ice crystal images are all stored in the same folder.

[0118] See also Figure 3 The image processing module is used to process the ice crystal image obtained by the image acquisition module and finally draw the ice core contour. The processing of the ice crystal image specifically includes: reading the original ice crystal image; obtaining a picture of the ice crystal; reading the original ice crystal image; copying the original image; median filtering for noise reduction; converting to a grayscale image; automatically identifying circular areas; deleting the background outside the circular area; adaptive histogram equalization; adaptive local threshold binarization; and drawing the ice core contour with a magnetic lasso.

[0119] The reading of the original ice crystal image is specifically as follows: the pictures in the folder of the previous step are read in batches by python code and named in chronological order, and the code is compiled by the software Anaconda Navigator. The copying of the original image is specifically as follows: the above-mentioned read picture is copied by code, and the original image is recorded for subsequent calculation and comparison. The median filtering noise reduction is specifically as follows: median filtering is implemented by python code to eliminate noise. Specifically including: taking the pixel values of the current pixel and its surrounding adjacent pixels (a total of an odd number of pixels), sorting these pixel values, and then using the pixel value in the middle position as the pixel value of the current pixel. The conversion to grayscale image is specifically as follows: the image is converted from RGB color space to gray space by code, that is, a grayscale image is generated to facilitate the calculation of subsequent steps. The automatic identification of circular areas is specifically as follows: automatic identification of circular ice crystal areas is implemented by code. Using the Hough gradient method, we first apply Canny edge detection to the grayscale image to identify possible circles. For each point on the circle's circumference, we calculate its gradient. Based on the gradient, we can draw a tangent about that point. The direction perpendicular to the tangent is the gradient direction. The intersection of the gradient directions at each point is the center of the circle. The radius of the circle can then be determined based on the center's position. Background outside the circular area is removed by retaining the circular ice crystal region identified in the previous step and removing other background areas to prevent interference with subsequent processing. Adaptive histogram equalization is implemented in code to improve image contrast. The image is first divided into 64 blocks (8 vertical and 8 horizontal). Histogram equalization is then performed on each block. This transforms an image block with a known grayscale probability density distribution into a new image block with a uniform grayscale probability density distribution. Finally, the blocks are stitched together to create the new image. Adaptive local threshold binarization is specifically as follows: the image is binarized using adaptive local thresholding. In the adaptive thresholding, the threshold of each pixel in the image is different. The threshold is determined by the weighted average of the image pixels in its area. After binarization, the distinction between phase interfaces is more obvious. Magnetic lasso drawing of ice core contours is specifically as follows: import the binary image obtained in the previous step into Adobe Photoshop 2022, use magnetic lasso to draw the ice core contour, and save it separately. Figure 3 The ice core outline drawn by the lasso is exactly the maximum envelope of all bubble edges.

[0120] The ice crystal melting rate calculation module is used to calculate the area of the ice core through the ice core contour map to obtain the ice core equivalent radius, and then calculate the ice crystal melting rate, specifically including: calculating the ice crystal melting rate through the ice crystal melting rate equivalent model.

[0121] The ice crystal melting rate equivalent model is specifically:

[0122] Assuming that the ice core is a sphere and that a water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated as follows:

[0123] First calculate the equivalent radius of the ice core:

[0124]

[0125] Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program.

[0126] Define the volume fraction of the ice core η v :

[0127]

[0128] Where: η v ——Volume proportion of ice core; r——Radius of ice crystal / px, obtained when ice crystal position is identified by ice core water film interface identification program.

[0129] The ratio of ice core mass to total ice crystal mass is defined as solid ice content:

[0130]

[0131] Where: η m,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 .

[0132] Finally, the definition of ice crystal melting rate is given:

[0133]

[0134] Where: η m,w ——Ice crystal melting rate.

[0135] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0136] Computer-readable storage media can be a tangible device that holds and stores the instructions used by an instruction execution device. Computer-readable storage media can, for example, include, but are not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, a punch card or a raised structure in a groove on which instructions are stored, for example, and any suitable combination thereof.

[0137] It is easy for those skilled in the art to understand that, under the premise of no conflict, the above-mentioned advantageous technical features can be freely combined and superimposed.

[0138] The above are merely preferred embodiments of the present invention and do not constitute any form of limitation to the present invention. Any simple modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A method for measuring ice crystal melting rate, characterized in that: The following steps are involved: Step 1: Get a picture of ice crystals; Step 2: Read the original ice crystal image; Step 3: Copy the original image; Step 4: Median filter noise reduction; Step 5: Convert to grayscale image; Step 6: Automatically identify the circular area; Step 7. Delete the background outside the circular area; Step 8: Adaptive histogram equalization; Step 9: Adaptive local threshold binarization; Step 10: Use magnetic lasso to draw the ice core outline; Step 11, calculating the melting rate of ice crystals using an ice crystal melting rate equivalent model; The ice crystal melting rate equivalent model is specifically: Assuming that the ice core is a sphere and that a water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated as follows: First calculate the equivalent radius of the ice core: Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program; Define the volume fraction of the ice core η v : Where: η v ——the proportion of ice core volume; r——the radius of ice crystal / px, obtained when the ice crystal position is identified by the ice core water film phase interface identification program; The ratio of ice core mass to total ice crystal mass is defined as solid ice content: Where: η m,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 ; Finally, the definition of ice crystal melting rate is given: Where: η m,w ——Ice crystal melting rate.

2. The ice crystal melting rate measuring method according to claim 1, wherein: The step 1 specifically comprises: extracting images of ice crystals at the same time intervals during the melting process using the software Adobe Premiere Pro 2022, and storing all the same set of ice crystal images in the same folder; The step 2 is specifically as follows: using Python code to batch read the images in the folder of the previous step and name them in chronological order, and compiling the code using the software Anaconda Navigator.

3. The ice crystal melting rate measuring method according to claim 2, wherein: The step 3 is specifically as follows: copying the image read in the previous step through the code, and recording the original image for subsequent calculation and comparison; The step 4 is specifically: implementing median filtering through Python code to eliminate noise.

4. The ice crystal melting rate measuring method according to claim 3, wherein: The step 5 is specifically: converting the image from the RGB color space to the gray space through code, that is, generating a grayscale image to facilitate calculations in subsequent steps.

5. The ice crystal melting rate measuring method according to claim 4, characterized in that: The step 6 specifically implements the automatic identification of circular ice crystal areas through code: using the Hough gradient method, first use Canny edge detection on the grayscale image to find possible circles, and for each point on the circumference, calculate its gradient. Based on the gradient, a tangent about this point can be made. The direction perpendicular to the tangent is the gradient direction. The intersection of the gradient directions of each point is the center of the circle, and then its radius is determined based on the position of the center of the circle.

6. The ice crystal melting rate measuring method according to claim 5, characterized in that: The step 8 specifically implements adaptive histogram equalization through code to improve image contrast: first, the image is divided into 8 vertical and 8 horizontal blocks, totaling 64 blocks, and then histogram equalization is performed on each block, that is, an image block with a known grayscale probability density distribution is transformed into a new image block with a uniform grayscale probability density distribution, and finally spliced into a new image.

7. The ice crystal melting rate measuring method according to claim 6, characterized in that: The step 9 is specifically as follows: binarizing the image using an adaptive local threshold, wherein the threshold of each pixel in the image is different and is determined by the weighted average of the image pixels in its area. After binarization, the distinction between the phase interfaces is more obvious.

8. The ice crystal melting rate measuring method according to claim 7, characterized in that: The step 10 specifically includes: importing the binary image obtained in the previous step into the software Adobe Photoshop 2022, using the magnetic lasso to draw the ice core outline, and storing it separately.

9. An ice crystal melting rate measurement system, characterized by: It includes an image acquisition module, an image processing module and an ice crystal melting rate calculation module; The image acquisition module is used to acquire pictures of ice crystals; The image acquisition module is used to extract images of ice crystals at the same time intervals during the melting process using the software Adobe Premiere Pro 2022, and all the same set of ice crystal images are stored in the same folder; The image processing module is used to process the ice crystal image obtained by the image acquisition module and finally draw the ice core outline. The ice crystal melting rate calculation module is used to calculate the area of the ice core through the ice core outline to obtain the ice core equivalent radius, and then calculate the ice crystal melting rate, which specifically includes: The melting rate of ice crystals is calculated using the ice crystal melting rate equivalent model; The ice crystal melting rate equivalent model is specifically: Assuming that the ice core is a sphere and that a water film evenly covers the surface of the ice core, the area of the ice core is calculated using the ice core contour map obtained in the above steps to obtain the ice core equivalent radius, and then the ice crystal melting rate is calculated as follows: First calculate the equivalent radius of the ice core: Where: r1 is the equivalent radius of the ice core / px; A is the area of the ice core / px 2 , obtained by identifying the ice core contour using an ice crystal melting rate calculation program; Define the volume fraction of the ice core η v : Where: η v ——the proportion of ice core volume; r——the radius of ice crystal / px, obtained when the ice crystal position is identified by the ice core water film phase interface identification program; The ratio of ice core mass to total ice crystal mass is defined as solid ice content: Where: η m,i ——solid ice content of ice crystals; ρ i ——Density of ice core / kg·m -3 ρ w ——Density of liquid water / kg·m -3 ; Finally, the definition of ice crystal melting rate is given: Where: η m,w ——Ice crystal melting rate.

10. A computer-readable storage medium having a computer program stored thereon, wherein: When the program is executed by a processor, the ice crystal melting rate measuring method according to any one of claims 1 to 8 is implemented.

Images