CN115170589A - Method and related device for detecting frosting degree of evaporator of refrigerating machine - Google Patents

Abstract

The application discloses a method for detecting frosting degree of a refrigerator evaporator and a related device, wherein the method comprises the following steps: taking the non-frosted image as a background image, carrying out differential processing on the image to be detected of the evaporator and the background image to obtain a differential image, and carrying out brightness correction on the differential image; denoising the difference image after brightness correction to obtain a denoised image, detecting the outline of the denoised image and calculating the area of the outline, and judging the area of the outline as a frosted area when the area of the outline is greater than a preset area threshold; calculating the minimum external matrix of the frosting area as a frame selection area, and determining the vertex of the frame selection area, thereby determining the frosting degree of the frosting area by using a dual-threshold segmentation algorithm according to the vertex; and substituting the frosting degree into a frosting value calculation formula to obtain the frosting value of the image to be detected. The problem of prior art because freezer light source environmental difference is great, the evaporimeter frosts inhomogeneously, freezer illumination changes, leads to judging the inconsistent degree standard that frosts is solved.

Description

A detection method and related device for the degree of frost formation in a refrigerator evaporator

technical field

The application relates to the technical field of refrigerators, and in particular, to a method and a related device for detecting the frosting degree of an evaporator of a refrigerator.

Background technique

Frosting phenomenon is a common problem in the refrigeration and heating industry. At present, many scholars have proposed different solutions from various technical fields. These methods can be roughly divided into three categories: defrost judgment methods based on direct measurement, defrost judgment methods based on indirect monitoring, and defrost judgment methods based on intelligent algorithms. Frosting detection technology based on image recognition belongs to the category of direct measurement. Compared with other methods, image recognition technology has the advantages of simplicity, low cost, and automatic operation. Therefore, image recognition can serve as a potential alternative to all existing frost detection methods.

In recent years, more and more frost detection algorithms based on digital image processing have been proposed. For example, the original image is converted into a grayscale image, and the grayscale value is used to describe the degree of frosting. Another example is the multi-threshold segmentation method to further improve the accuracy of frosting detection. At present, there are many images used for frosting degree detection. The processing method has been proposed, but after engineering practice, it is found that the proposed image methods all have the following problems: 1. When the light source environment of the cold storage is very different, the frosting judgment is affected by the light source; 2. When the evaporator frosting is uneven, the frosting Frost judgment still uses the original judgment threshold, which leads to inaccurate judgment of frost formation; finally, partial frost occurs in the evaporator; 3. The illumination of the cold storage changes, and the judgment of frost formation is affected by the light intensity when the light intensity fluctuates; 4. Judgment of frost The frost level standards are inconsistent, and the defrost threshold index needs to be reset for different evaporators.

SUMMARY OF THE INVENTION

The present application provides a method for detecting the frosting degree of a refrigerator evaporator and a related device, which are used to solve the problem of judging the degree of frosting in the prior art due to large differences in the light source environment of the cold storage, uneven frosting of the evaporator, and changes in the illumination of the cold storage. Standard inconsistency technical issues.

In view of this, a first aspect of the present application provides a method for detecting the frosting degree of a refrigerator evaporator, the method comprising:

Taking the unfrosted image as a background image, performing differential processing on the image to be detected of the evaporator and the background image to obtain a differential image, and performing brightness correction on the differential image;

Perform denoising processing on the difference image after brightness correction to obtain a denoised image, detect the contour of the denoised image and calculate the contour area, when the contour area is greater than a preset area threshold, then determine that the contour area is frosted area;

Calculate the minimum circumscribed matrix of the frosted area as a frame selection area, and determine the vertices of the frame selection area, so as to use a double-threshold segmentation algorithm to determine the frosting degree of the frosted area according to the vertices;

The frosting degree is substituted into the frosting value calculation formula to obtain the frosting value of the image to be detected.

Optionally, the frosting degree is substituted into the frosting value calculation formula to obtain the frosting value of the image to be detected, further comprising:

When the frosting value is greater than the first preset frosting threshold, if so, a defrosting command is generated to defrost the evaporator; when the frosting value after defrosting is still greater than the second preset frosting threshold, Then an abnormal alarm signal is generated.

Optionally, using the unfrosted image as a background image, performing a differential process on the image to be detected of the evaporator and the background image to obtain a differential image, and performing brightness correction on the differential image;

Taking the unfrosted image as the background image, performing differential processing on the image to be detected of the evaporator and the background image based on the differential formula to obtain a differential image;

The image to be detected and the background image are respectively divided into a control area and a frost detection area, and the difference between the average gray value of the control area of the image to be detected and the average gray value of the control area of the background image is substituted into the brightness correction formula , the difference image after brightness correction is obtained;

Wherein, the difference formula is:

P(x,y)=I(x,y)-B(x,y)

In the formula, (x, y) represents the pixel point of the xth row and the yth column in the image, P represents the differential image, I is the image to be detected, and B is the background image;

The brightness correction formula is:

R(x,y)=P(x,y)-C _Gap

C _Gap = PC _mean -BC _mean

In the formula, C _Cap is the difference between the average gray value PC _mean of the control area of the image to be detected and the average gray value BC _mean of the control area of the background image, and (x, y) represents the x-th row and the y-th column in the image. Pixel point, R(x,y) is the difference image after correcting the brightness.

Optionally, the calculation formula of the frosting value is:

in,

In the formula, T(x,y) is the frosting degree, 126 is the medium frosting degree, 254 is the severe frosting degree, Thresh1 and Thresh2 are the segmentation thresholds, and R(x,y) is the difference image after correction of brightness. , fv is the frosting value, N is the total number of pixels in the image to be detected, and (x, y) represents the pixel in the xth row and the yth column in the image.

A second aspect of the present application provides a system for detecting the frosting degree of a refrigerator evaporator, the system comprising:

a difference unit, configured to use the unfrosted image as a background image, perform difference processing between the image to be detected of the evaporator and the background image to obtain a difference image, and perform brightness correction on the difference image;

an analysis unit, configured to perform denoising processing on the difference image after brightness correction to obtain a denoised image, detect the contour of the denoised image and calculate the contour area, when the contour area is greater than a preset area threshold, determine The contour area is the frosted area;

The first calculation unit is used to calculate the minimum circumscribed matrix of the frosted area as a frame selection area, and determine the vertices of the frame selection area, so as to use a double-threshold segmentation algorithm to determine the frost area of the frosted area according to the vertices. degree of frost;

The second calculation unit is configured to substitute the frosting degree into the frosting value calculation formula to obtain the frosting value of the image to be detected.

Optionally, also include:

The defrosting processing unit is configured to generate a defrosting command to defrost the evaporator when the frosting value is greater than the first preset frosting threshold, and if so; when the defrosting value is still greater than the first defrosting value 2. Preset the frosting threshold, then generate an abnormal alarm signal.

Optionally, the differential unit is specifically used for:

Taking the unfrosted image as the background image, performing differential processing on the image to be detected of the evaporator and the background image based on the differential formula to obtain a differential image;

The image to be detected and the background image are respectively divided into a control area and a frost detection area, and the difference between the average gray value of the control area of the image to be detected and the average gray value of the control area of the background image is substituted into the brightness correction formula , the difference image after brightness correction is obtained;

Wherein, the difference formula is:

P(x,y)=I(x,y)-B(x,y)

In the formula, (x, y) represents the pixel point of the xth row and the yth column in the image, P represents the differential image, I is the image to be detected, and B is the background image;

The brightness correction formula is:

R(x,y)=P(x,y)-C _Gap

C _Gap = PC _mean -BC _mean

In the formula, C _Cap is the difference between the average gray value PC _mean of the control area of the image to be detected and the average gray value BC _mean of the control area of the background image, and (x, y) represents the x-th row and the y-th column in the image. Pixel point, R(x,y) is the difference image after correcting the brightness.

Optionally, the calculation formula of the frosting value is:

in,

In the formula, T(x,y) is the frosting degree, 126 is the medium frosting degree, 254 is the severe frosting degree, Thresh1 and Thresh2 are the segmentation thresholds, and R(x,y) is the difference image after correction of brightness. , fv is the frosting value, N is the total number of pixels in the image to be detected, and (x, y) represents the pixel in the xth row and the yth column in the image.

A third aspect of the present application provides a device for detecting the frosting degree of a refrigerator evaporator, the device includes a processor and a memory:

the memory is used to store program code and transmit the program code to the processor;

The processor is configured to execute, according to the instructions in the program code, the steps of the method for detecting the frosting degree of an evaporator of a refrigerator according to the first aspect.

A fourth aspect of the present application provides a computer-readable storage medium, where the computer-readable storage medium is used to store program codes, and the program codes are used to perform the detection of the degree of frost formation in the evaporator of the refrigerator according to the first aspect above. method.

As can be seen from the above technical solutions, the present application has the following advantages:

The present application provides a method for detecting the degree of frosting of an evaporator of a refrigerator, including: taking an unfrosted image as a background image, performing differential processing between an image to be detected of the evaporator and the background image to obtain a differential image, and performing a differential image on the differential image. Brightness correction; perform denoising processing on the difference image after brightness correction to obtain a denoised image, detect the contour of the denoised image and calculate the contour area, when the contour area is greater than the preset area threshold, determine the contour area as a frosted area; calculate The minimum circumscribed matrix of the frosting area is used as the frame selection area, and the vertices of the frame selection area are determined, so that the frosting degree of the frosting area is determined by the double-threshold segmentation algorithm according to the vertices; the frosting degree is substituted into the frosting value calculation formula, Obtain the frosting value of the image to be detected.

The present application is an evaporator frosting degree detection method based on image difference, using image difference technology to detect the front and back transformation of the image to judge the frosting situation, and set the frosting detection area and the control area to eliminate the brightness change. Then perform operations such as denoising and contour detection, and frame the frosted area of the image. Double-threshold segmentation is performed on the frosted area, and the frosting value is introduced to measure the degree of frosting. The solution of the invention solves the technical problem of inconsistent standards for judging the degree of frost formation in the prior art due to the large difference in the light source environment of the cold storage, the uneven frosting of the evaporator, and the variation of the illumination of the cold storage. Compared with other image processing solutions, it has stronger applicability, accuracy, anti-interference and ease of use.

Description of drawings

1 is a schematic flowchart of an embodiment of a method for detecting the frosting degree of a refrigerator evaporator provided in the embodiment of the application;

FIG. 2 is a schematic structural diagram of an embodiment of a system for detecting frosting degree of a refrigerator evaporator provided in an embodiment of the application;

3 is a schematic diagram of an image difference operation provided in an embodiment of the present application;

Figure 4a is a schematic diagram of the comparison between the light frosting and the frosting value (29.8%) provided in the examples of the application;

Figure 4b is a schematic diagram of the comparison between the moderate frosting and the frosting value (52.5%) provided in the examples of the application;

FIG. 4c is a schematic diagram of the comparison between the heavy frosting and the frosting value (62.5%) provided in the examples of the application.

Detailed ways

In order to make those skilled in the art better understand the solutions of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of the present application, but not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

Referring to FIG. 1, a method for detecting the frosting degree of a refrigerator evaporator provided in the embodiment of the present application includes:

Step 101, taking the unfrosted image as the background image, performing differential processing between the to-be-detected image of the evaporator and the background image to obtain a differential image, and performing brightness correction on the differential image;

It should be noted that, in the implementation, firstly, by selecting the unfrosted image as the image background template, the camera transmits the image to be detected at the frequency of one image per minute, and grayscale processing is performed on all the images. Subsequently, the image to be detected will be subjected to a differential operation with the template image, as shown in FIG. 3 . The specific formula of the difference is as follows:

P(x,y)=I(x,y)-B(x,y)

In the formula, (x, y) represents the pixel point in the xth row and the yth column of the image, P represents the difference image, I is the image to be detected, and B is the background image.

Since the image obtained after image difference is the result of removing the background image from the image to be detected, in the frost detection area, the remaining pixel values are the evaporator frosting points. The frosting point obtained using this method is not affected by differences in ambient light sources. Although the influence of light source differences can be removed by the differential method, there are usually light changes and other illumination changes in the cold storage. The main function of setting the control area is to detect changes in brightness. When there is a change in brightness, there will be an average grayscale difference between the background image comparison area and the to-be-detected image comparison area.

Therefore, it is only necessary to calculate the average grayscale difference of the control area to correct the brightness change. The specific operation of brightness correction is as follows: dividing the image to be detected and the background image into a control area and a frosting detection area, respectively, and dividing the average gray value of the control area of the image to be detected and the average gray value of the control area of the background image. Substitute into the brightness correction formula to obtain the differential image after brightness correction;

The brightness correction formula is:

P(x,y)=P(x,y)-C _Gap

C _Gap = PC _mean -BC _mean

In the formula, C _Cap is the difference between the average gray value PC _mean of the control area of the image to be detected and the average gray value BC _mean of the control area of the background image, and (x, y) represents the x-th row and the y-th column in the image. Pixel point, R(x,y) is the difference image after correcting the brightness.

Step 102: Perform denoising processing on the difference image after brightness correction to obtain a denoised image, detect the contour of the denoised image and calculate the contour area, when the contour area is greater than a preset area threshold, determine that the contour area is a frosted area;

It should be noted that, in the implementation, basic denoising operations such as erosion, median filtering, and dilation are first used to denoise the differential image. is 3*3; then perform the contour detection operation on the processed image, and calculate the area of all contours. If the contour area is greater than 1/10 of the image, the contour will be regarded as a frosted area.

Step 103, calculate the minimum circumscribed matrix of the frosted area as the frame selection area, and determine the vertices of the frame selection area, so as to determine the frosting degree of the frosted area by using a double threshold segmentation algorithm according to the vertex;

It should be noted that the minimum circumscribed matrix of the frosting area is first calculated as the frame selection area, and the vertices of the frame selection area are determined;

Then, the vertices are used to segment the frosted area and calculate the frosting degree, and use the double-threshold segmentation algorithm based on the difference map feature to realize the binarization conversion operation of the image. The specific operation steps of the multi-threshold segmentation algorithm based on difference map features are as follows:

Since the image difference removes the difference of the ambient light source, the difference results under different light source environments tend to be unified. The invention divides the frosting grades into two grades, moderate and severe, by counting the grayscale histogram of the difference image. Use double-threshold segmentation to set moderate and severe frosted pixels to 126 and 254, respectively. The specific implementation formula is as follows:

In the formula, T(x, y) is the frosting degree, Thresh1 and Thresh2 are segmentation thresholds, and R(x, y) is the difference image after brightness correction.

Step 104: Substitute the frosting degree into the frosting value calculation formula to obtain the frosting value of the image to be detected.

It should be noted that the frosting value parameter is finally introduced to unify the frosting severity, as shown in Figures 4a, 4b and 4c. The formula for calculating the frost value (fv frost value) is:

In the formula, R(x, y) is the difference image after correcting the brightness, fv is the frosting value, N is the total number of pixels in the image to be detected, and (x, y) represents the x-th row y-th in the image. Column of pixels.

Further, the detection method further includes: when the frosting value is greater than the first preset frosting threshold, and if so, generating a defrosting command to defrost the evaporator; when the frosting value after defrosting is still greater than the second preset threshold If the frost threshold is exceeded, an abnormal alarm signal will be generated.

It should be noted that, in the implementation, it is determined whether the frosting value exceeds 50% (the first preset frosting threshold). If the frosting value exceeds 50%, it is determined that defrosting is required, and the frosting value is detected again. If the frosting value is higher than 15% (the second preset frosting threshold), it is considered that the defrosting is abnormal, and the system will send an abnormal alarm signal.

The above is a method for detecting the degree of frost formation of a refrigerator evaporator provided in the embodiment of the application, and the following is a detection system for the degree of frost formation of a refrigerator evaporator provided in the embodiment of the application.

Referring to FIG. 2 , a system for detecting the frosting degree of a refrigerator evaporator provided in an embodiment of the present application includes:

The difference unit 201 is used for taking the unfrosted image as the background image, performing the difference processing between the to-be-detected image of the evaporator and the background image to obtain the difference image, and performing brightness correction on the difference image;

The analysis unit 202 is configured to perform denoising processing on the difference image after brightness correction to obtain a denoised image, detect the contour of the denoised image and calculate the contour area, when the contour area is greater than a preset area threshold, determine that the contour area is frosting area;

The first calculation unit 203 is used to calculate the minimum circumscribed matrix of the frosted area as the frame selection area, and determines the vertex of the frame selection area, thereby utilizing the double threshold segmentation algorithm to determine the frosting degree of the frosted area according to the vertex;

The second calculation unit 204 is configured to substitute the frosting degree into the frosting value calculation formula to obtain the frosting value of the image to be detected.

Further, the detection system further includes: a defrosting processing unit, configured to generate a defrosting command to defrost the evaporator when the frosting value is greater than the first preset frosting threshold, and if so; If the value is still greater than the second preset frosting threshold, an abnormal alarm signal is generated.

Further, an embodiment of the present application also provides a device for detecting the frosting degree of a refrigerator evaporator, and the device includes a processor and a memory:

the memory is used to store program code and transmit the program code to the processor;

The processor is configured to execute, according to the instructions in the program code, the method for detecting the frosting degree of the evaporator of the refrigerator according to the above method embodiment.

Further, the embodiments of the present application further provide a computer-readable storage medium, where the computer-readable storage medium is used to store program codes, and the program codes are used to execute the refrigerator evaporator described in the foregoing method embodiments How to test the degree of frost

Those skilled in the art can clearly understand that, for the convenience and brevity of description, for the specific working process of the system and unit described above, reference may be made to the corresponding process in the foregoing method embodiments, which will not be repeated here.

The terms "first", "second", "third", "fourth", etc. in the description of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. . It is to be understood that the data so used may be interchanged under appropriate circumstances such that the embodiments of the application described herein can, for example, be practiced in sequences other than those illustrated or described herein. Furthermore, the terms "comprising" and "having" and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those expressly listed Rather, those steps or units may include other steps or units not expressly listed or inherent to these processes, methods, products or devices.

It should be understood that, in this application, "at least one (item)" refers to one or more, and "a plurality" refers to two or more. "And/or" is used to describe the relationship between related objects, indicating that there can be three kinds of relationships, for example, "A and/or B" can mean: only A, only B, and both A and B exist , where A and B can be singular or plural. The character "/" generally indicates that the associated objects are an "or" relationship. "At least one item(s) below" or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one (a) of a, b or c, can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c" ", where a, b, c can be single or multiple.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit. The above-mentioned integrated units may be implemented in the form of hardware, or may be implemented in the form of software functional units.

The integrated unit, if implemented in the form of a software functional unit and sold or used as an independent product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the present application can be embodied in the form of software products in essence, or the parts that contribute to the prior art, or all or part of the technical solutions, and the computer software products are stored in a storage medium , including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (full English name: Read-Only Memory, English abbreviation: ROM), random access memory (English full name: Random Access Memory, English abbreviation: RAM), magnetic disks Or various media such as optical discs that can store program codes.

As mentioned above, the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand: The technical solutions recorded in the embodiments are modified, or some technical features thereof are equivalently replaced; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions in the embodiments of the present application.

Claims (10)

1. A method for detecting the frosting degree of an evaporator of a refrigerating machine is characterized by comprising the following steps:

taking the non-frosted image as a background image, carrying out differential processing on an image to be detected of an evaporator and the background image to obtain a differential image, and carrying out brightness correction on the differential image;

denoising the difference image after brightness correction to obtain a denoised image, detecting the contour of the denoised image and calculating the contour area, and judging the contour area to be a frosting area when the contour area is larger than a preset area threshold;

calculating the minimum external matrix of the frosting area as a frame selection area, and determining the vertex of the frame selection area, so as to determine the frosting degree of the frosting area by using a dual-threshold segmentation algorithm according to the vertex;

and substituting the frosting degree into a frosting value calculation formula to obtain the frosting value of the image to be detected.

2. The method for detecting the frosting degree of the evaporator of the refrigerating machine according to claim 1, wherein the frosting degree is substituted into a frosting value calculation formula to obtain a frosting value of an image to be detected, and further comprising:

when the frosting value is larger than a first preset frosting threshold value, if so, generating a defrosting command to defrost the evaporator; and when the frosting value after defrosting is still larger than a second preset frosting threshold value, generating an abnormal alarm signal.

3. The refrigerator evaporator frosting degree detection method according to claim 1, wherein the non-frosted image is used as a background image, a difference image is obtained by performing difference processing on an image to be detected of the evaporator and the background image, and brightness correction is performed on the difference image;

taking the non-frosted image as a background image, and carrying out differential processing on an image to be detected of the evaporator and the background image based on a differential formula to obtain a differential image;

dividing the image to be detected and the background image into a contrast area and a frosting detection area respectively, and substituting the difference between the average gray value of the contrast area of the image to be detected and the average gray value of the contrast area of the background image into a brightness correction formula to obtain a difference image after brightness correction;

wherein the difference formula is:

P(x,y)＝I(x,y)-B(x,y)

in the formula, (x, y) represents pixel points in the x-th row and the y-th column in the image, P represents a differential image, I is an image to be detected, and B is a background image;

the brightness correction formula is as follows:

R(x,y)＝P(x,y)-C _Gap

C _Gap ＝PC _mean -BC _mean

in the formula, wherein C _Cap Average gray value PC of contrast area for image to be detected _mean Average gray value BC of contrast area of background image _mean The difference (x, y) represents the pixel point in the x-th row and the y-th column in the image, and R (x, y) is the difference image after brightness correction.

4. The method for detecting the frosting degree of an evaporator of a refrigerating machine according to claim 1, wherein the frosting value is calculated by the formula:

wherein,

in the formula, T (x, y) is the frosting degree, 126 is the medium frosting degree, 254 is the severe frosting degree, thresh1 and Thresh2 are segmentation thresholds, R (x, y) is a differential image after brightness correction, fv is the frosting value, N is the total number of pixels of the image to be detected, and (x, y) represents pixels in the x-th row and the y-th column in the image.

5. A system for detecting the frost formation of a chiller evaporator, comprising:

the difference unit is used for taking the image without frosting as a background image, carrying out difference processing on the image to be detected of the evaporator and the background image to obtain a difference image, and carrying out brightness correction on the difference image;

the analysis unit is used for carrying out denoising treatment on the difference image after brightness correction to obtain a denoised image, detecting the outline of the denoised image and calculating the area of the outline, and judging the area of the outline as a frosted area when the area of the outline is larger than a preset area threshold;

the first calculation unit is used for calculating the minimum circumscribed matrix of the frosting area as a frame selection area, and determining the vertex of the frame selection area, so that the frosting degree of the frosting area is determined by utilizing a dual-threshold segmentation algorithm according to the vertex;

and the second calculating unit is used for substituting the frosting degree into a frosting value calculation formula to obtain the frosting value of the image to be detected.

6. The system for detecting the frost formation of an evaporator of a refrigerator according to claim 5, further comprising:

the defrosting processing unit is used for generating a defrosting command to defrost the evaporator if the frosting value is larger than a first preset frosting threshold value; and when the frosting value after defrosting is still larger than a second preset frosting threshold value, generating an abnormal alarm signal.

7. The system for detecting the frosting degree of an evaporator of a refrigerating machine according to claim 5, wherein the difference unit is specifically configured to:

taking the non-frosted image as a background image, and carrying out differential processing on an image to be detected of the evaporator and the background image based on a differential formula to obtain a differential image;

dividing the image to be detected and the background image into a contrast area and a frosting detection area respectively, and substituting the difference between the average gray value of the contrast area of the image to be detected and the average gray value of the contrast area of the background image into a brightness correction formula to obtain a difference image after brightness correction;

wherein the difference formula is:

P(x,y)＝I(x,y)-B(x,y)

in the formula, (x, y) represents the pixel points of the x row and the y column in the image, P represents a differential image, I is an image to be detected, and B is a background image;

the brightness correction formula is as follows:

R(x,y)＝P(x,y)-C _Gap

C _Gap ＝PC _mean -BC _mean

in the formula, wherein C _Cap Average gray value PC of contrast area for image to be detected _mean And the backAverage gray value BC of contrast area of scene image _mean And (x, y) represents the pixel point of the x-th row and the y-th column in the image, and R (x, y) is the differential image after brightness correction.

8. The system for detecting the frosting degree of an evaporator of a refrigerating machine according to claim 5, wherein the frosting value is calculated by the formula:

wherein,

in the formula, T (x, y) is the frosting degree, 126 is the medium frosting degree, 254 is the severe frosting degree, thresh1 and Thresh2 are segmentation thresholds, R (x, y) is a differential image after brightness correction, fv is the frosting value, N is the total number of pixels of the image to be detected, and (x, y) represents pixels in the x-th row and the y-th column in the image.

9. An apparatus for detecting a degree of frosting of a refrigerator evaporator, said apparatus comprising a processor and a memory:

the memory is used for storing program codes and transmitting the program codes to the processor;

the processor is configured to execute the method for detecting a degree of frosting on an evaporator of a chiller according to any of claims 1-4 according to instructions in the program code.

10. A computer-readable storage medium characterized by storing a program code for executing the method for detecting a degree of frosting of an evaporator of a refrigerating machine according to any one of claims 1 to 4.

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