Detection Method, Device, Equipment and Storage Medium of Engine Oil

Abstract

The present application relates to a method, device, equipment and storage medium for detecting engine oil. The method includes: acquiring a detection image in a refrigerant liquid storage tank of a compressor to be detected; extracting image features in the detection image; determining whether the image features contain preset features related to oil; and if the image features contain the preset features related to oil, determining that the refrigerant contains oil. The present application is used to reduce costs and improve the detection efficiency of engine oil.

Description

Technical Field

[0001] The present application relates to the technical field of intelligent devices, and particularly to a method, device, equipment and storage medium for detecting engine oil. Background Art

[0002] The compressor is considered the heart of the refrigeration system and thus the most important core component of the air conditioner. The engine oil in the compressor is mainly used to lubricate the internal parts of the compressor and play a certain role in heat dissipation. Among them, if the engine oil is too little, the compressor is likely to burn out; if the engine oil is too much, it will affect the refrigeration of the air conditioner. Therefore, it is crucial to detect the oil level in the compressor.

[0003] In the existing methods for detecting the oil level of the compressor, it is necessary to manually observe the passing situation of the refrigerant at the glass viewing hole of the liquid storage tank to determine whether the refrigerant contains oil. It can be seen that the existing oil level detection methods require a large amount of labor cost and time cost. Summary of the Invention

[0004] The present application provides a method, device, equipment and storage medium for detecting engine oil, so as to reduce costs and improve the detection efficiency of engine oil.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting engine oil, including:

[0006] Obtaining a detection image in a refrigerant liquid storage tank of a compressor to be detected;

[0007] Extracting image features in the detection image;

[0008] Judging whether the image features contain preset features related to oil;

[0009] If the image features contain the preset features related to oil, determining that the refrigerant contains oil.

[0010] Optionally, the obtaining a detection image in a refrigerant liquid storage tank of a compressor to be detected includes:

[0011] Controlling an illumination device to irradiate the liquid surface in the refrigerant liquid storage tank;

[0012] Collecting an image of the liquid surface in the refrigerant liquid storage tank as the detection image.

[0013] Optionally, the extracting image features in the detection image includes:

[0014] Identifying all colors in the detection image;

[0015] Taking the color information of all the colors as the image features.

[0016] Optionally, determining whether the image features include preset features related to oil includes:

[0017] If the color information is the type of color, determine whether the type of color in the detected image is within the preset type range. If so, determine that the detected image includes the preset features related to oil; otherwise, determine that the detected image does not include the preset features related to oil.

[0018] If the color information is color, determine whether the color of the detected image includes the preset color of oil. If so, determine that the detected image includes the preset features related to oil; otherwise, determine that the detected image does not include the preset features related to oil.

[0019] Optionally, extracting the image features in the detected image includes:

[0020] Perform binarization processing on the detected image to obtain multiple lines in the detected image.

[0021] Segment the binarized image according to the layout between the lines to obtain multiple different image regions in the detected image.

[0022] Perform image description processing on each of the image regions to determine the geometric features of each of the image regions, and use the determined geometric features as the image features.

[0023] Optionally, determining whether the image features include preset features related to oil includes:

[0024] Obtain a preset geometric feature library for oil on the water surface, where the preset geometric feature library includes at least one preset geometric feature.

[0025] Determine whether the geometric features in the detected image include the preset geometric features. If so, determine that the detected image includes the preset features related to oil; otherwise, determine that the detected image does not include the preset features related to oil.

[0026] Optionally, it further includes:

[0027] Obtain an image of the engine oil in the compressor to be detected.

[0028] Identify the liquid level in the image of the engine oil to obtain the amount of engine oil at the current moment.

[0029] Calculate the ratio of the amount of engine oil to the preset amount of oil.

[0030] If the ratio is not within the preset range, determine that the oil level of the engine oil is abnormal.

[0031] In a second aspect, an oil detection device provided by an embodiment of the present application includes:

[0032] An acquisition module, configured to acquire a detection image in a refrigerant liquid storage tank of a compressor to be detected;

[0033] An extraction module, configured to extract image features in the detection image;

[0034] A judgment module, configured to judge whether preset features related to oil are included in the image features;

[0035] A determination module, configured to determine that the refrigerant contains oil if the preset features related to oil are included in the image features.

[0036] In a third aspect, an electronic device provided by an embodiment of the present application includes: a processor, a memory, and a communication bus. Among them, the processor and the memory complete mutual communication through the communication bus;

[0037] The memory is used to store a computer program;

[0038] The processor is configured to execute the program stored in the memory to implement the oil detection method described in the first aspect.

[0039] In a fourth aspect, a computer-readable storage medium provided by an embodiment of the present application stores a computer program, and when the computer program is executed by a processor, it implements the oil detection method described in the first aspect.

[0040] The above technical solutions provided by the embodiments of the present application have the following advantages compared with the prior art: In the method provided by the embodiments of the present application, a detection image in a refrigerant liquid storage tank of a compressor to be detected is acquired, image features in the detection image are extracted, and it is judged whether preset features related to oil are included in the image features. It can be seen that in the present application, by extracting the image features of the detection image and judging whether there is oil in the refrigerant according to the image features, the problem of the need for manual observation of whether there is oil in the refrigerant in the prior art is solved, and when the preset features related to oil are included in the image features, it is determined that the refrigerant contains oil. In the present application, whether there is oil in the refrigerant can be obtained through the detection image, effectively saving labor costs and time costs and improving the detection efficiency of oil. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present invention and used together with the specification to explain the principles of the present invention.

[0042] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the accompanying drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a schematic flow diagram of the method for detecting engine oil in the embodiments of the present application;

[0044] Figure 2 It is a schematic flow diagram of the first process of extracting image features from the detection image in the embodiments of the present application;

[0045] Figure 3 It is a schematic flow diagram of the second process of extracting image features from the detection image in the embodiments of the present application;

[0046] Figure 4 It is a schematic flow diagram of determining whether there is an abnormality in the engine oil by the oil level of the engine oil in the embodiments of the present application;

[0047] Figure 5 It is a schematic flow diagram of the specific detection method for the first engine oil in the embodiments of the present application;

[0048] Figure 6 It is a schematic flow diagram of the specific detection method for the second engine oil in the embodiments of the present application;

[0049] Figure 7 It is a schematic flow diagram of the specific detection method for the third engine oil in the embodiments of the present application;

[0050] Figure 8 It is a schematic structural diagram of the detection device for engine oil in the embodiments of the present application;

[0051] Figure 9 It is a schematic structural diagram of the electronic device in the embodiments of the present application. Detailed implementation manners

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, rather than all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

[0053] The embodiments of the present application provide a method for detecting engine oil, which can be applied to a server or a terminal.

[0054] This application is described by taking the application of this method in a server as an example. Of course, this is only an example here and is not used to limit the protection scope of this application. Moreover, some other examples in this application are also not used to limit the protection scope of this application, so they will not be elaborated one by one.

[0055] The application scenario of this application is the test scenario of a compressor. The normal operation of a compressor requires a certain amount of engine oil. If the amount of engine oil is inappropriate, it will cause wear of the compressor. In severe cases, it will directly cause the compressor to jam during operation. Therefore, it is necessary to detect the engine oil of the compressor. For example, this compressor is the compressor installed in the outdoor unit of an air conditioner.

[0056] Transport the outdoor unit of the air conditioner equipped with the compressor to be detected to the detection station of the detection platform. The detection station includes: a lighting device, a first shooting device, and a second shooting device, so that the lighting device is aligned with the glass observation hole of the compressor liquid storage tank, and the first shooting device is aligned with the glass observation hole of the compressor liquid storage tank, and the second shooting device is aligned with the sight glass of the compressor. Among them, the lighting device can be an electric light bulb, a flashlight, etc., the first shooting device can be any camera, and the second shooting device can be a thermal imaging camera.

[0057] The lighting device is used to illuminate the refrigerant liquid storage tank through the glass observation hole of the compressor liquid storage tank.

[0058] The first shooting device is used to shoot the detection image in the refrigerant liquid storage tank of the compressor to be detected through the glass observation hole of the compressor liquid storage tank, and send the detection image to the server.

[0059] The second shooting device is used to shoot the image of the engine oil in the compressor through the sight glass of the compressor, and send the image of the engine oil to the server.

[0060] The specific implementation of this method is as Figure 1 shown:

[0061] Step 101, obtain the detection image in the refrigerant liquid storage tank of the compressor to be detected.

[0062] In a specific embodiment, control the lighting device to irradiate the liquid surface in the refrigerant liquid storage tank; collect the image of the liquid surface in the refrigerant liquid storage tank under the action of light as the detection image.

[0063] Specifically, when it is necessary to detect the engine oil of the compressor, the server sends a lighting instruction to the lighting device. The lighting device receives the lighting instruction sent by the server and irradiates the refrigerant liquid storage tank through the glass observation hole according to the lighting instruction. Of course, the lighting device can also always irradiate the refrigerant liquid storage tank through the glass observation hole without the need for message communication with the server.

[0064] Specifically, when it is necessary to detect the compressor oil, the server sends a first shooting instruction to the first shooting device. The first shooting device receives the first shooting instruction sent by the server, and according to the first shooting instruction, shoots a detection image of the refrigerant liquid storage tank in the compressor to be detected, and sends the detection image to the server. Of course, the first shooting device can also continuously shoot detection images and then send the detection images to the server.

[0065] Step 102, extract the image features in the detection image.

[0066] In a specific embodiment, the specific operation of extracting the image features in the detection image is as Figure 2 shown:

[0067] Step 201, identify all the colors in the detection image.

[0068] Step 202, use the color information of all the colors as the image features.

[0069] Among them, the color information includes: the type of color, color, the number of color types, etc.

[0070] Specifically, the detection image can be input into a color model (Hue Saturation Value, abbreviated as HSV), and all the colors in the detection image are output through the HSV model. Among them, the HSV model is trained using N sample detection images, and the sample detection images include: images of the refrigerant and images of the refrigerant containing oil, and N is an integer greater than 1.

[0071] Specifically, according to the principle of thin-film interference, when light irradiates on water containing oil, new light waves are formed due to different refractive indices. That is, if the refrigerant contains engine oil, the captured detection image includes multiple colors; if there is no engine oil in the refrigerant, the color of the captured detection image is relatively single.

[0072] In a specific embodiment, according to the principle of immiscibility of water and oil, if there is engine oil in the refrigerant, the engine oil will not mix with the refrigerant and is in the form of particles, oil beads, etc. Therefore, the geometric features in the detection image can be extracted and used as the image features. Among them, the geometric features include: the shape of the figure, the area of the figure, the perimeter of the figure, etc.

[0073] Among them, the specific operation of extracting the image features in the detection image is as Figure 3 shown:

[0074] Step 301, perform binarization processing on the detection image to obtain multiple lines in the detection image.

[0075] Specifically, the detected image is converted into a grayscale image, and then the grayscale image is binarized to obtain a binary image. Further, according to a pre-determined threshold, the threshold is compared with the grayscale value of each pixel point one by one. The pixel value of the pixel point where the threshold is greater than the grayscale value is set to 0, and the pixel value of the pixel point where the threshold is less than or equal to the grayscale value is set to 255. At this time, the whole image shows an obvious black and white effect. After resetting the pixel values, multiple lines in the detected image are obtained.

[0076] Step 302: According to the layout between the lines, the binarized image is segmented to obtain multiple different image regions in the detected image.

[0077] Specifically, after obtaining different image regions, each image region can be image-identified. A unique number, generally an integer, can be marked for each image region.

[0078] Step 303: Perform image description processing on each image region, determine the geometric features of each image region, and use the determined geometric features as image features.

[0079] Specifically, identify the shapes included in each image region, and use data, symbols, or formal languages to represent the identified shapes. Among them, any one or more of data, symbols, or formal languages can be used as geometric features.

[0080] Step 103: Determine whether the image features contain preset features related to oil.

[0081] In a specific embodiment, the following method can be used to determine whether the image features contain preset features related to oil:

[0082] If the color information is the type of color, determine whether the type of color in the detected image is within the preset type range. If so, it is determined that the detected image contains preset features related to oil; otherwise, it is determined that the detected image does not contain preset features related to oil.

[0083] If the color information is color, determine whether the color of the detected image contains the preset color of oil. If so, it is determined that the detected image contains preset features related to oil; otherwise, it is determined that the detected image does not contain preset features related to oil.

[0084] If the color information is the number of color types, determine whether the number of color types is greater than the preset number of color types. If so, it is determined that the detected image contains preset features related to oil; otherwise, it is determined that the detected image does not contain preset features related to oil.

[0085] In a specific embodiment, the following method can be used to determine whether the image features contain preset features related to oil:

[0086] Obtain a preset geometric feature library of oil on the water surface. The preset geometric feature library contains at least one preset geometric feature. Determine whether the geometric features in the detected image contain the preset geometric features. If so, it is determined that the detected image contains preset features related to oil; otherwise, it is determined that the detected image does not contain preset features related to oil.

[0087] After the detection image is obtained in the embodiment of the present application, the image features of the detection image are recognized, and according to the image features, it is determined whether the refrigerant contains engine oil. The whole process does not require manual participation and is automatically and intelligently processed throughout, saving labor costs and time costs and improving work efficiency.

[0088] Step 104, if the image features contain preset features related to oil, it is determined that the refrigerant contains oil.

[0089] Specifically, if the image features do not contain preset features related to oil, it is determined that the refrigerant does not contain oil.

[0090] In a specific embodiment, the present application can also determine whether there is an abnormality in the engine oil level of the engine oil, specifically as Figure 4 shown:

[0091] Step 401, obtain an image of the engine oil in the compressor to be detected.

[0092] In addition, when the detection of the compressor engine oil is required, the server sends a second shooting instruction to the second shooting device. The second shooting device receives the second shooting instruction sent by the server, takes an image of the engine oil in the compressor according to the second shooting instruction, and sends the image of the engine oil to the server. Of course, the second shooting device can also continuously take images of the engine oil and then send the images of the engine oil to the server.

[0093] Step 402, identify the liquid level in the image of the engine oil to obtain the amount of engine oil at the current moment.

[0094] Specifically, obtain the ambient temperature at the current moment to obtain a preset oil volume corresponding to the ambient temperature.

[0095] Step 403, calculate the ratio of the computer oil volume to the preset oil volume.

[0096] Step 404, if the ratio is not within the preset range, it is determined that the oil level of the engine oil is abnormal.

[0097] Specifically, if the ratio is within the preset range, it is determined that the oil level of the engine oil is not abnormal.

[0098] Specifically, temperature affects the oil level, that is, the oil levels of a certain amount of engine oil are inconsistent at different temperatures. Therefore, when judging whether there is an abnormality in the engine oil based on the oil quantity, the ambient temperature needs to be considered. The following is an example for illustration:

[0099] Taking a certain amount (for example, 100 g) of engine oil as an example, it is illustrated in advance by grouping according to the four seasons of spring, summer, autumn and winter and taking a week as the statistical interval:

[0100] Taking a week as the statistical interval, count the oil levels at the ambient temperature in spring;

[0101] Taking a week as the statistical interval, count the oil levels at the ambient temperature in summer;

[0102] Taking a week as the statistical interval, count the oil levels at the ambient temperature in autumn;

[0103] Taking a week as the statistical interval, count the oil levels at the ambient temperature in winter;

[0104] Using the average (avg) function, calculate the average values of the oil levels counted in each quarter, which are the first average oil level, the second average oil level, the third average oil level and the fourth average oil level respectively;

[0105] Select the median value from the four average values as the preset oil quantity.

[0106] When the image to be detected is an engine oil image and the liquid feature is the engine oil quantity, calculate the ratio of the computer-measured oil quantity to the preset oil quantity; if the ratio is within the preset range, it is determined that the engine oil is normal, otherwise, it is determined that the engine oil is abnormal.

[0107] For example, the preset range is (0.1 - 10). If the ratio is within (0.1 - 10), it is determined that the engine oil is normal and the refrigeration effect is normal, otherwise, it is determined that the engine oil is abnormal.

[0108] Of course, the preset oil quantity can also be a set of data, for example, including: the first average oil level, the second average oil level, the third average oil level and the fourth average oil level.

[0109] When the image to be detected is an engine oil image and the liquid feature is the engine oil quantity, obtain the corresponding quarter at the current moment to get the preset oil quantity corresponding to the quarter; calculate the ratio of the computer-measured oil quantity to the preset oil quantity; if the ratio is within the preset range, it is determined that the engine oil is normal, otherwise, it is determined that the engine oil is abnormal.

[0110] In addition, taking a certain amount (for example, 100 g) of engine oil as an example, it is illustrated in advance by grouping according to the temperature (ambient temperature) and taking an hour as the statistical interval:

[0111] Among them, the groups include the first group, the second group, the third group, and the fourth group. The temperature range corresponding to the first group is (-10°C, 0°C), the temperature range corresponding to the second group is (0°C, 10°C), the temperature range corresponding to the third group is (10°C, 20°C), and the temperature range corresponding to the third group is (20°C, 30°C).

[0112] Taking hours as the statistical interval, count the respective oil levels at the ambient temperature of the first group;

[0113] Taking hours as the statistical interval, count the respective oil levels at the ambient temperature of the second group;

[0114] Taking hours as the statistical interval, count the respective oil levels at the ambient temperature of the third group;

[0115] Taking hours as the statistical interval, count the respective oil levels at the ambient temperature of the fourth group;

[0116] Using the avg function, calculate the average values of the oil levels counted for each group, which are the fifth average oil level, the sixth average oil level, the seventh average oil level, and the eighth average oil level respectively.

[0117] The preset oil quantity can also be a set of data, for example, including: the fifth average oil level, the sixth average oil level, the seventh average oil level, and the eighth average oil level.

[0118] When the image to be detected is an engine oil image and the liquid feature is the engine oil quantity, obtain the corresponding ambient temperature at the current moment to get the preset oil quantity corresponding to the ambient temperature; calculate the ratio of the computer oil quantity to the preset oil quantity; if the ratio is within the preset range, determine that the engine oil is normal, otherwise, determine that the engine oil is abnormal.

[0119] Of course, in order to improve the accuracy of oil level detection, the groups can be divided more densely, and they will not be listed one by one here.

[0120] After the embodiment of the present application obtains the detection image, it identifies the liquid feature of the detection image, and based on this liquid feature, determines whether the refrigerant contains engine oil. The whole process does not require manual participation and is automatically and intelligently processed throughout, saving labor costs and time costs and improving work efficiency.

[0121] In addition, after determining that there is engine oil in the refrigerant, the operating frequency of the compressor can be increased to recover the engine oil into the storage tank.

[0122] Next, through Figure 5 Specifically illustrate the detection process of the engine oil:

[0123] Step 501, obtain the detection image in the refrigerant liquid storage tank of the compressor to be detected.

[0124] Step 502: Identify all the colors in the detected image and determine the color information of all the colors.

[0125] Step 503: If the color information is the type of color, determine whether the type of color in the detected image is within the preset type range. If so, execute Step 504; otherwise, execute Step 505.

[0126] Step 504: Determine that the detected image contains the preset features related to oil, and obtain that there is oil in the refrigerant.

[0127] Step 505: Determine that the detected image does not contain the preset features related to oil, and obtain that there is no oil in the refrigerant.

[0128] Next, through Figure 6 Specifically illustrate the detection process of engine oil:

[0129] Step 601: Obtain the detected image in the refrigerant liquid storage tank of the compressor to be detected.

[0130] Step 602: Identify all the colors in the detected image and determine the color information of all the colors.

[0131] Step 603: If the color information is color, determine whether the color of the detected image contains the preset color of oil. If so, execute Step 604; otherwise, execute Step 605.

[0132] Step 604: Determine that the detected image contains the preset features related to oil, and obtain that there is oil in the refrigerant.

[0133] Step 605: Determine that the detected image does not contain the preset features related to oil, and obtain that there is no oil in the refrigerant.

[0134] Next, through Figure 7 Specifically illustrate the detection process of engine oil:

[0135] Step 701: Obtain the detected image in the refrigerant liquid storage tank of the compressor to be detected.

[0136] Step 702: Identify the geometric features in the detected image.

[0137] Step 703: Obtain the preset geometric feature library where the oil is on the water surface.

[0138] Step 704: Determine whether the geometric features in the detected image contain the preset geometric features. If so, execute Step 705; otherwise, execute Step 706.

[0139] Step 705: Determine that the detected image contains the preset features related to oil, and obtain that there is oil in the refrigerant.

[0140] Step 706, it is determined that the detected image does not contain a preset feature related to oil, and it is obtained that there is no oil in the refrigerant.

[0141] In the method provided by the embodiment of the present application, a detected image of a refrigerant liquid storage tank in a compressor to be detected is obtained, image features in the detected image are extracted, and it is determined whether the image features contain a preset feature related to oil. It can be seen that in the present application, by extracting the image features of the detected image and judging whether there is engine oil in the refrigerant according to the image features, the problem of the existing method that requires manual observation of whether there is engine oil in the refrigerant is solved. When the image features contain a preset feature related to oil, it is determined that there is oil in the refrigerant. In the present application, whether there is engine oil in the refrigerant can be obtained through the detected image, effectively saving labor costs and time costs and improving the detection efficiency of engine oil.

[0142] Based on the same concept, an engine oil detection device is provided in the embodiment of the present application. For the specific implementation of the device, reference can be made to the description in the method embodiment part, and the repeated parts will not be elaborated. As Figure 8 shown, the device mainly includes:

[0143] An acquisition module 801, configured to acquire a detected image of a refrigerant liquid storage tank in a compressor to be detected;

[0144] An extraction module 802, configured to extract image features in the detected image;

[0145] A judgment module 803, configured to judge whether the image features contain a preset feature related to oil;

[0146] A determination module 804, configured to determine that there is oil in the refrigerant if the image features contain a preset feature related to oil.

[0147] In a specific embodiment, the acquisition module 801 is specifically configured to control an illumination device to irradiate the liquid surface in the refrigerant liquid storage tank; and collect an image of the liquid surface in the refrigerant liquid storage tank as the detected image.

[0148] In a specific embodiment, the extraction module 802 is specifically configured to identify all colors in the detected image; and use the color information of all the colors as the image features.

[0149] In a specific embodiment, the determination module 803 is specifically configured to, if the color information is the type of color, determine whether the type of color in the detected image is within a preset type range. If so, it is determined that the detected image contains the preset features related to oil; otherwise, it is determined that the detected image does not contain the preset features related to oil. If the color information is color, determine whether the color of the detected image contains the preset color of oil. If so, it is determined that the detected image contains the preset features related to oil; otherwise, it is determined that the detected image does not contain the preset features related to oil.

[0150] In a specific embodiment, the extraction module 802 is specifically configured to perform binarization processing on the detected image to obtain multiple lines in the detected image; segment the binarized image according to the layout between the lines to obtain multiple different image regions in the detected image; perform image description processing on each of the image regions to determine the geometric features of each of the image regions, and use the determined geometric features as the image features.

[0151] In a specific embodiment, the determination module 803 is specifically configured to obtain a preset geometric feature library of oil on the water surface, where the preset geometric feature library contains at least one preset geometric feature; determine whether the geometric features in the detected image contain the preset geometric feature. If so, it is determined that the detected image contains the preset features related to oil; otherwise, it is determined that the detected image does not contain the preset features related to oil.

[0152] In a specific embodiment, the device further includes an anomaly detection module, which is configured to obtain an image of the engine oil in the compressor to be detected; identify the liquid level in the image of the engine oil to obtain the amount of engine oil at the current moment; calculate the ratio of the amount of engine oil to the preset amount of oil; if the ratio is not within the preset range, determine that the oil level of the engine oil is abnormal.

[0153] Among them, the anomaly detection module includes: an engine oil image acquisition module, an identification module, a calculation module, and an anomaly determination module.

[0154] The engine oil image acquisition module is configured to obtain an image of the engine oil in the compressor to be detected;

[0155] The identification module is configured to identify the liquid level in the image of the engine oil to obtain the amount of engine oil at the current moment;

[0156] The calculation module is configured to calculate the ratio of the amount of engine oil to the preset amount of oil;

[0157] The anomaly determination module is configured to determine that the oil level of the engine oil is abnormal if the ratio is not within the preset range.

[0158] Based on the same concept, an electronic device is further provided in an embodiment of the present application. As Figure 9 shown, the electronic device mainly includes: a processor 901, a memory 902, and a communication bus 903. Among them, the processor 901 and the memory 902 complete mutual communication through the communication bus 903. Among them, a program executable by the processor 901 is stored in the memory 902, and the processor 901 executes the program stored in the memory 902 to implement the following steps: obtaining a detection image in a refrigerant liquid storage tank of a compressor to be detected; extracting image features in the detection image; determining whether the image features contain preset features related to oil; if the image features contain preset features related to oil, determining that the refrigerant contains oil.

[0159] The communication bus 903 mentioned in the above electronic device may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus 903 can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, Figure 9 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0160] The memory 902 may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor 901.

[0161] The aforementioned processor 901 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc., or may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0162] In yet another embodiment of the present application, a computer-readable storage medium is further provided. A computer program is stored in the computer-readable storage medium. When the computer program runs on a computer, the computer is caused to execute the oil detection method described in the above embodiments.

[0163] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another. For example, the computer instructions are transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, microwave, etc.). The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape, etc.), an optical medium (such as a DVD), or a semiconductor medium (such as a solid-state drive), etc.

[0164] It should be noted that in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including", or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article, or device that includes a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article, or device that includes the element.

[0165] The above are only specific embodiments of the present invention, enabling those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather will be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for detecting engine oil, characterized in that, Including: Obtain a detection image of the refrigerant liquid storage tank in the compressor to be detected; Extract the image features in the detection image; wherein, the image features at least include the geometric features of multiple different image regions in the detection image; Determine whether the image features contain preset features related to oil; If the image features contain the preset features related to oil, determine that the refrigerant contains oil; Among them, determining whether the image features contain preset features related to oil includes: Obtain a preset geometric feature library where oil is located on the water surface, and the preset geometric feature library contains at least one preset geometric feature; Determine whether the geometric features in the detection image contain the preset geometric features. If so, determine that the detection image contains the preset features related to oil; otherwise, determine that the detection image does not contain the preset features related to oil.

2. The method for detecting engine oil according to claim 1, characterized in that, The obtaining of the detection image of the refrigerant liquid storage tank in the compressor to be detected includes: Control the lighting device to irradiate the liquid surface in the refrigerant liquid storage tank; Collect the image of the liquid surface in the refrigerant liquid storage tank as the detection image.

3. The method for detecting engine oil according to claim 2, characterized in that, The extracting of the image features in the detection image includes: Identify all the colors in the detection image; Take the color information of all the colors as the image features.

4. The method for detecting engine oil according to claim 3, characterized in that, The determining whether the image features contain preset features related to oil includes: If the color information is the type of color, determine whether the type of color in the detection image is within the preset type range. If so, determine that the detection image contains the preset features related to oil; otherwise, determine that the detection image does not contain the preset features related to oil; If the color information is color, determine whether the color of the detection image contains the preset color of oil. If so, determine that the detection image contains the preset features related to oil; otherwise, determine that the detection image does not contain the preset features related to oil.

5. The method for detecting engine oil according to claim 2, characterized in that, The extracting of the image features in the detection image includes: Perform binarization processing on the detection image to obtain multiple lines in the detection image; According to the layout between the lines, perform image segmentation on the binarized image to obtain multiple different image regions in the detection image; Perform image description processing on each image region to determine the geometric features of each image region, and take the determined geometric features as the image features.

6. The method for detecting engine oil according to claim 1, characterized in that, It also includes: Obtain the image of the engine oil in the compressor to be detected; Identify the liquid level in the image of the engine oil to obtain the amount of engine oil at the current moment; Calculate the ratio of the amount of engine oil to the preset amount of oil; If the ratio is not within the preset range, determine that the oil level of the engine oil is abnormal.

7. An apparatus for detecting engine oil, characterized in that, Including: An acquisition module for obtaining a detection image of the refrigerant liquid storage tank in the compressor to be detected; An extraction module for extracting the image features in the detection image; wherein, the image features at least include the geometric features of multiple different image regions in the detection image; A judgment module, configured to judge whether the image features contain preset features related to oil; A determination module, configured to determine that the refrigerant contains oil if the image features contain the preset features related to oil; Wherein, the judgment module is specifically configured to obtain a preset geometric feature library where oil is located on the water surface, and the preset geometric feature library contains at least one preset geometric feature; judge whether the geometric features in the detected image contain the preset geometric features, and if so, determine that the detected image contains the preset features related to oil, otherwise, determine that the detected image does not contain the preset features related to oil.

8. An electronic device, characterized in that, It includes: A processor, a memory and a communication bus, wherein the processor and the memory complete communication with each other through the communication bus; The memory is used to store computer programs; The processor is configured to execute the programs stored in the memory to implement the detection method of engine oil according to any one of claims 1-6.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the detection method of engine oil according to any one of claims 1-6.

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