CN115170589A - Method and related device for detecting frosting degree of evaporator of refrigerating machine - Google Patents
Method and related device for detecting frosting degree of evaporator of refrigerating machine Download PDFInfo
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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
Technical Field
The application relates to the technical field of refrigerating machines, in particular to a method and a related device for detecting frosting degree of an evaporator of a refrigerating machine.
Background
The frosting phenomenon is a common problem in the refrigeration and heating industry, and currently, a plurality of scholars propose different solutions from a plurality of technical fields. These methods can be broadly divided into three categories: a direct measurement defrosting judgment method, an indirect monitoring defrosting judgment method and an intelligent algorithm-based defrosting judgment method. The frosting detection technology based on image recognition belongs to the direct measurement category, and compared with other methods, the image recognition technology has the advantages of simplicity, low cost, automatic operation and the like. Thus, image recognition may be a potential alternative to all existing frost detection methods.
In recent years, more and more frosting detection algorithms based on digital image processing have been proposed. If the original image is converted into a grayed image, the frosting degree is described by adopting a gray value, and then the precision of frosting detection is further improved by using a multi-threshold segmentation method; at present, a plurality of image processing methods for detecting the frosting degree are proposed, but after engineering practice, the proposed image methods all have the following problems: 1. when the difference of the environment of the light source of the refrigeration house is large, the frosting judgment is influenced by the light source; 2. when the evaporator frosts unevenly, the frosting judgment still uses the original judgment threshold value, so that the frosting judgment is inaccurate; finally, the evaporator has a local frosting phenomenon; 3. the illumination of the refrigeration house is changed, and the frosting judgment is influenced by the illumination intensity when the illumination intensity is suddenly high or low; 4. and judging that the frosting degree standards are inconsistent, and resetting the defrosting threshold indexes for different evaporators.
Disclosure of Invention
The application provides a method and a related device for detecting frosting degree of a refrigerator evaporator, which are used for solving the technical problem that in the prior art, the standard of frosting degree is judged to be inconsistent due to large difference of a light source environment of a refrigeration house, uneven frosting of the evaporator and illumination change of the refrigeration house.
In view of the above, a first aspect of the present application provides a method for detecting a frosting degree of a refrigerator evaporator, the method comprising:
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 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;
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.
Optionally, substituting the frosting degree into a frosting value calculation formula to obtain a frosting value of the image to be detected, 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.
Optionally, taking the non-frosted image as a background image, performing difference processing on the image to be detected of the evaporator and the background image to obtain a difference image, and performing brightness correction 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 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 Average gray value BC of contrast area of background 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.
Optionally, the frosting value calculation formula is:
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.
A second aspect of the present application provides a system for detecting a frosting degree of a refrigerator evaporator, the system comprising:
the difference unit is used for taking the non-frosted image 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.
Optionally, the method further comprises:
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.
Optionally, 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 Average gray value BC of contrast area of background 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.
Optionally, the frosting value calculation formula is:
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.
A third aspect of the present application provides a refrigerator evaporator frosting degree detection apparatus, the 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 steps of the method for detecting the frosting degree of the evaporator of the refrigeration machine according to the first aspect described above according to the instructions in the program code.
A fourth aspect of the present application provides a computer-readable storage medium for storing program code for executing the method for detecting a frosting degree of an evaporator of a refrigerating machine according to the first aspect.
According to the technical scheme, the method has the following advantages:
the application provides a method for detecting frosting degree of a refrigerator evaporator, which 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 contour of the denoised image and calculating the contour area, and judging the contour area as 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, 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.
According to the evaporator frosting degree detection method based on the image difference, the image difference technology is used for detecting the front-back transformation of the image so as to judge the frosting condition, and a frosting detection area and a comparison area are set for eliminating the brightness change. And then, carrying out operations such as denoising, contour detection and the like, and selecting an image frosting area by a frame. And carrying out double-threshold segmentation on the frosting area, and introducing a frosting value to measure the frosting degree. The technical problem that in the prior art, due to the fact that the difference of the environment of the light source of the refrigeration house is large, the frosting of the evaporator is not uniform, and the illumination of the refrigeration house is changed, the standard of frosting degree judgment is inconsistent is solved. Compared with other image processing schemes, the method has stronger applicability, accuracy, anti-interference performance and usability.
Drawings
FIG. 1 is a schematic flow chart illustrating an embodiment of a method for detecting a frosting degree of an evaporator of a refrigerator according to an embodiment of the present disclosure;
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 present application;
FIG. 3 is a schematic diagram of an image differencing operation provided in an embodiment of the present application;
FIG. 4a is a graphical comparison of light frosting and frosting values (29.8%) provided in the examples of the present application;
FIG. 4b is a graphical comparison of moderate frost to frost values (52.5%) provided in the examples of the present application;
fig. 4c is a graphical comparison of the heavy frosting and frosting values (62.5%) provided in the examples of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Referring to fig. 1, a method for detecting a frosting degree of an evaporator of a refrigerator provided in an embodiment of the present application includes:
in implementation, an image that is not frosted is selected as an image background template, the camera transmits the image to be detected at a frequency of one image per minute, and all the images are subjected to gray processing. The image to be detected will then be differentiated from the template image, as shown in fig. 3. The difference is specifically as follows:
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 the differential image, I is the image to be detected, and B is the background image.
Because the image obtained after the image difference is the result of the image to be detected after the background image is removed, the remaining pixel values in the frosting detection area are evaporator frosting points. The frosting point obtained by the method is not influenced by the difference of the environmental light sources. Although the effect of the difference in the light sources can be removed by the difference method, the effect of the illumination variation factors such as the variation in the light is generally present in the refrigerator. The control area is set to mainly detect a change in brightness. When brightness changes exist, average gray scale difference exists between the background image contrast area and the image contrast area to be detected.
Therefore, brightness change can be corrected by only calculating the average gray difference of the contrast area. The brightness correction specifically operates as: 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;
the brightness correction formula is as follows:
P(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 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.
102, 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 frosting area when the area of the outline is larger than a preset area threshold;
it should be noted that, in implementation, basic denoising operations such as erosion, median filtering, expansion, and the like are first adopted to perform denoising processing on a difference image, and the convolution kernels of the operations such as erosion, expansion, median filtering, and the like used in this embodiment are all 3*3; and then carrying out contour detection operation on the processed image, calculating all contour areas, and if the contour areas are larger than 1/10 of the image, considering the contour as a frosted area.
103, calculating a minimum external matrix of the frosting area as a frame selection area, and determining a 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;
it should be noted that, first, the minimum external matrix of the frosting area is calculated as a frame selection area, and the vertex of the frame selection area is determined;
and then, the vertex is used for segmenting the frosted area and calculating the frosted degree, and a dual-threshold segmentation algorithm based on the characteristics of the difference image is used for realizing the binaryzation conversion operation on the image. The specific operation steps of the multi-threshold segmentation algorithm based on the differential image features are as follows:
because the difference of the image difference removes the difference of the ambient light sources, the difference results under different light source environments tend to be uniform. The invention divides the frosting grade into a medium grade and a serious grade by counting the gray histogram of the difference image. Pixels with moderate and severe frosting were set to 126, 254, respectively, using dual threshold segmentation. The concrete 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 a difference image after brightness correction.
And step 104, substituting the frosting degree into a frosting value calculation formula to obtain the frosting value of the image to be detected.
It should be noted that a frosting value parameter is finally introduced for unifying frosting severity, as shown in fig. 4a, 4b and 4c. The frosting value (fv frost value) is calculated by the formula:
in the formula, R (x, y) is a differential image after brightness correction, fv is the frosting value, N is the total number of pixel points of the image to be detected, and (x, y) represents the pixel points of the x-th row and the y-th column in the image.
Further, the detection method further comprises: 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 the second preset frosting threshold value, generating an abnormal alarm signal.
It should be noted that, in the implementation, it is determined whether the frosting value exceeds 50% (a first preset frosting threshold), if the frosting value exceeds 50%, it is determined that defrosting is required, the frosting value is detected again, and if the frosting value after defrosting is higher than 15% (a second preset frosting threshold), it is determined that defrosting is abnormal, and the system sends an abnormal warning signal.
The above is a method for detecting a frosting degree of a refrigerator evaporator provided in the embodiment of the present application, and the following is a system for detecting a frosting degree of a refrigerator evaporator provided in the embodiment of the present application.
Referring to fig. 2, a system for detecting a frosting degree of an evaporator of a refrigerator provided in an embodiment of the present application includes:
the difference unit 201 is configured to use the non-frosted image as a background image, perform difference processing on 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;
the analysis unit 202 is configured to perform denoising processing on the difference image after the brightness correction to obtain a denoised image, detect a contour of the denoised image and calculate a contour area, and when the contour area is larger than a preset area threshold, determine that the contour area is a frosted area;
the first calculating unit 203 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 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 comprises: 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 the second preset frosting threshold value, generating an abnormal alarm signal.
Further, the embodiment of the present application also provides a device for detecting the frosting degree of a refrigerator evaporator, where the device includes a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the method for detecting the frosting degree of the evaporator of the refrigerating machine according to the method embodiment according to the instructions in the program code.
Further, an embodiment of the present application provides a computer-readable storage medium, which is used for storing a program code for executing the method for detecting frosting degree of the evaporator of the refrigeration machine according to the above method embodiment
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The terms "first," "second," "third," "fourth," and the like in the description of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Moreover, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be understood that in the present application, "at least one" means one or more, "a plurality" means two or more. "and/or" for describing an association relationship of associated objects, indicating that there may be three relationships, e.g., "a and/or B" may indicate: only A, only B and both A and B are present, wherein A and B may be singular or plural. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one of the following" or similar expressions refer to any combination of these items, including any combination of single item(s) or plural items. For example, at least one (one) of a, b, or c, may represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", wherein a, b, c may be single or plural.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of 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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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110094925A (en) * | 2019-05-08 | 2019-08-06 | 南京工程学院 | A kind of evaporimeter frosting detection method and the application that defrosts |
| CN118112036A (en) * | 2024-03-05 | 2024-05-31 | 嘉兴依相动力科技有限公司 | Surface frost testing method for decompression evaporator for fuel automobile |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110094925A (en) * | 2019-05-08 | 2019-08-06 | 南京工程学院 | A kind of evaporimeter frosting detection method and the application that defrosts |
| CN110094925B (en) * | 2019-05-08 | 2023-12-29 | 南京工程学院 | Evaporator frosting detection method and defrosting application |
| CN118112036A (en) * | 2024-03-05 | 2024-05-31 | 嘉兴依相动力科技有限公司 | Surface frost testing method for decompression evaporator for fuel automobile |
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