Range hood use state detection method and device, electronic equipment and program product

Abstract

The invention provides a range hood use state detection method and device, electronic equipment and a program product, and the method comprises the steps: obtaining a noise score based on the noise frequency domain characteristics of a range hood; based on the lampblack suction image of the range hood, obtaining a lampblack suction effect score; obtaining an oil stain score of the range hood based on the oil stain image of the range hood; and obtaining a comprehensive score of the range hood based on the noise score, the oil smoke suction effect score, the oil stain score and the age limit coefficient of the range hood. According to the range hood use state detection method and device, the electronic equipment and the program product provided by the invention, the noise score, the oil stain score and the oil smoke suction effect score are respectively obtained, the comprehensive score is obtained by combining the age limit coefficient of the range hood, and a decision on whether replacement or cleaning is needed is made according to the comprehensive score, so that judgment is accurate and rapid; decision updating and reminding can be carried out in real time, and better cleaning selection is brought to the user.

Description

Technical Field

[0001] The present disclosure relates to a range hood detection method, and in particular to a range hood usage status detection method, device, electronic equipment, and program product. Background Art

[0002] Range hoods are essential kitchen appliances, and their performance directly impacts the kitchen environment and user health. Currently, users' assessments of range hood performance rely primarily on subjective perceptions, such as noise level and fume extraction effectiveness, lacking an objective, quantitative evaluation method.

[0003] Many users lack a clear understanding of the status of their range hoods. This prevents them from understanding their range hood's true condition in a timely manner, potentially leading to untimely cleaning, shortening its lifespan, premature replacement, and wasted resources. Furthermore, if the range hood is in poor condition and not replaced, it could negatively impact the user's health. Currently, there is no professional testing method to assess the status of range hoods and provide a definitive answer, allowing users to determine whether their range hood is functioning properly, should be cleaned, or should be replaced. Summary of the Invention

[0004] The technical problem to be solved by the present disclosure is to overcome the defects in the prior art and provide a usage status detection method, device, electronic equipment and program product for accurately evaluating the performance of a range hood.

[0005] The present invention solves the above technical problems through the following technical solutions: A method for detecting the use status of a range hood, comprising:

[0006] The noise score is obtained based on the frequency domain characteristics of the range hood noise;

[0007] Obtaining a fume extraction effect score based on the fume extraction image of the range hood;

[0008] Obtaining an oil pollution score of the range hood based on the oil pollution image of the range hood;

[0009] A comprehensive score of the range hood is obtained based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood.

[0010] Preferably, obtaining a noise score based on the noise frequency domain characteristics of the range hood includes:

[0011] Collect the sound signal when the range hood is in use and convert it into a spectrum;

[0012] Extracting peak and trough differences of abnormal frequency bands based on the noise spectrum of the range hood;

[0013] A noise score is derived based on the difference.

[0014] Preferably, said obtaining a noise score based on said difference comprises,

[0015] ;

[0016] S noise For rating, L s is the difference.

[0017] Preferably, the oil fume extraction effect score obtained based on the oil fume extraction image of the range hood includes:

[0018] Obtaining a front escape rate and a side escape rate based on the front fume image and the side fume image of the range hood, respectively;

[0019] The oil fume extraction effect score is obtained based on the front escape rate, the side escape rate and the corresponding coefficients.

[0020] Preferably, the oil pollution score of the range hood is obtained based on the oil pollution image of the range hood, including:

[0021] Acquiring an oil stain image of the range hood;

[0022] Obtaining the oil pollution coverage area ratio of the oil pollution image based on a preset neural network;

[0023] obtaining the saturation and brightness of the oil stain area based on the oil stain image;

[0024] Obtaining an oil stain color depth coefficient based on the saturation and brightness of the oil stain area;

[0025] The oil pollution score is obtained based on the oil pollution coverage area ratio and the oil pollution color depth coefficient.

[0026] Preferably, the comprehensive score of the range hood obtained based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood includes:

[0027] Obtaining an age coefficient based on the service life of the range hood;

[0028] Based on the age coefficient of the range hood and the weighting coefficients of the noise score, the oil fume extraction effect score, and the oil pollution score, a comprehensive score of the range hood is obtained.

[0029] Preferably, the age coefficient is obtained based on the service life of the range hood; including:

[0030] ;

[0031] Wherein age is the service life, the F age is the age coefficient.

[0032] Another aspect of the present disclosure provides a range hood usage status detection device, comprising:

[0033] Noise scoring module, used to obtain a noise score based on the noise frequency characteristics of the range hood;

[0034] A fume extraction effect scoring module is used to obtain a fume extraction effect score based on the fume extraction image of the range hood;

[0035] An oil pollution scoring module is used to obtain an oil pollution score of the range hood based on the oil pollution image of the range hood;

[0036] A comprehensive scoring module is used to obtain a comprehensive score of the range hood based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood.

[0037] Another aspect of the present disclosure provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and configured to run on the processor, wherein the processor implements any one of the above-described range hood usage status detection methods when executing the computer program.

[0038] Another aspect of the present disclosure provides a computer program product, including a computer program, which implements any one of the above-mentioned range hood usage status detection methods when executed by a processor.

[0039] On the basis of conforming to the common sense in this field, the above-mentioned preferred conditions can be arbitrarily combined to obtain the preferred embodiments of the present disclosure.

[0040] The positive progress of the present disclosure is that the range hood usage status detection method provided in the embodiment of the present disclosure obtains the noise score, oil pollution score and oil fume extraction effect score respectively, and obtains a comprehensive score in combination with the age coefficient of the range hood. The decision on whether to replace or clean the range hood is made based on the comprehensive score. Not only is the judgment accurate and fast, but the decision can also be updated and reminded in real time, giving users better cleaning options. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a range hood usage status detection method provided in Example 1 of the present disclosure;

[0042] Figure 2 A schematic flow chart of step S10 provided in Example 1 of the present disclosure;

[0043] Figure 3 A flowchart of another implementation of step S10 provided in Example 1 of the present disclosure;

[0044] Figure 4 This is a flow chart of step S20 provided in Example 1 of the present disclosure;

[0045] Figure 5 A schematic flow chart of step S30 provided in Example 1 of the present disclosure;

[0046] Figure 6 This is a flow chart of step S40 provided in Example 1 of the present disclosure;

[0047] Figure 7 A schematic diagram of the structure of a range hood usage status detection device provided in Example 2 of the present disclosure;

[0048] Figure 8 This is a schematic diagram of the structure of the electronic device provided in Example 3 of the present disclosure. DETAILED DESCRIPTION

[0049] The present disclosure is further illustrated below by way of examples, but the present disclosure is not limited to the scope of the examples.

[0050] In the embodiments of the present disclosure, prefixes such as "first" and "second" are used only to distinguish different description objects and have no limiting effect on the position, order, priority, quantity or content of the described objects. In the embodiments of the present disclosure, the use of prefixes such as ordinal numbers to distinguish description objects does not constitute a restriction on the described objects. For the statement of the described objects, please refer to the description in the context of the embodiments, and the use of such prefixes should not constitute an unnecessary restriction. In addition, in the description of this embodiment, unless otherwise specified, the meaning of "plurality" is two or more.

[0051] In the embodiments of the present disclosure, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0052] Example 1

[0053] Figure 1 A flow chart of a method for detecting the use status of a range hood provided in Example 1 of the present disclosure, the method comprising:

[0054] S10, obtains the noise score based on the noise frequency characteristics of the range hood;

[0055] S20, obtaining a fume extraction effect score based on the fume extraction image of the range hood;

[0056] S30, obtaining an oil pollution score of the range hood based on the oil pollution image of the range hood;

[0057] S40: Obtain a comprehensive score of the range hood based on the noise score, the oil fume extraction effect score, the oil pollution score, and the age coefficient of the range hood.

[0058] In the step S10, a noise score is obtained based on the noise frequency domain characteristics of the range hood, which is obtained by using a sensor to obtain the sound of the range hood in use and then analyzing the sound spectrum to obtain the noise score.

[0059] Specifically, the sound of the range hood in use is collected and processed, the difference between the peaks and troughs of the abnormal frequency is extracted, and the noise of the range hood is scored according to the segmented dynamics, such as Figure 2 As shown. Includes:

[0060] S11, collecting the sound signal of the range hood in use and converting it into a spectrum diagram; since the sound signals collected by sensors are generally time domain signals, after Fourier transform, the time domain signal can be converted into a frequency domain signal to obtain a spectrum diagram as the basis for sound analysis.

[0061] S12, based on the spectrum, extract the peak and trough difference of the abnormal frequency band; determine whether there is an obvious protrusion in the spectrum, if there is, it means there is an abnormal frequency band, extract the peak and trough value of the abnormal frequency band, for example For the crest, For the trough, The difference between the two is .

[0062] S13, obtain a noise score based on the difference. s The sound may be heard if it is greater than 14. s The larger the value, the more obvious the abnormal sound. At this time, the noise score S can be calculated according to the abnormal sound scoring formula. noise This coefficient is used to judge the use status of the range hood. s When it is less than or equal to 14dB, S noise =0; when L s Greater than 14dB and less than or equal to 17dB, S noise =0.5+0.1(L s -14); when L s Greater than 17dB, S noise =1.0+0.2(L s -17); when L s The larger the value, the more serious the abnormal sound. noise The bigger.

[0063] ;

[0064] In addition, as another embodiment, since range hoods usually have multiple gears, in order to obtain the noise score more accurately, the sound signals of the range hood at multiple gears can be measured and converted into spectrograms respectively, and the abnormal frequency bands are extracted from the spectrograms at each gear to obtain the difference. The noise scores corresponding to different gears are obtained based on the difference, and then the weighting coefficients are set according to the possible size ratios of the noise at different gears to obtain the final noise score. Figure 3 As shown,

[0065] That is, S11', collecting sound signals of the range hood at multiple gears and converting them into a spectrum;

[0066] S12′, extracting the peak and trough differences of abnormal frequency bands based on the noise spectrum of the range hood at multiple gears;

[0067] S13 ′: Obtain noise scores for multiple gears based on the differences, and determine a final noise score based on the weighted coefficient and noise score of each gear.

[0068] For example, the gears include weak gear, strong gear, and instantaneous absorption gear. The difference in each gear is 12dB, 16dB and 19dB respectively. Since the noise of the weak gear itself is not obvious and the impact is not large, the weighting coefficient is set to 0, the weighting coefficient of the strong gear is set to 0.35, and the weighting coefficient of the instantaneous absorption gear is set to 0.14. The final noise score is: 0×12+0.35×16+0.14×19=8.26.

[0069] Step S20, as Figure 4 As shown, the oil fume extraction effect score obtained based on the oil fume extraction image of the range hood includes:

[0070] S21, obtaining a front escape rate and a side escape rate based on the front fume image and the side fume image of the range hood, respectively;

[0071] S22, obtaining the oil fume extraction effect score based on the front escape rate and the side escape rate and corresponding coefficients.

[0072] This method can be measured during actual use or with the aid of a smoke generator. For example, a quantitative smoke generator, such as one that atomizes a propylene glycol glycerol solution, is used. The smoke particle size is controlled to 0.3–1 μm, and the spray velocity is set at 1.5 m / s ± 0.2, simulating actual cooking fumes. The smoke generator is placed 30 cm above the center of the stove, at a standard distance from the range hood air inlet.

[0073] Images of the range hood during fume extraction were captured from the front and sides. The front camera captured smoke intake from both sides of the range hood, while the side camera captured smoke intake from the front. The captured images were processed and analyzed, and moving smoke pixels were extracted using the background subtraction method. The front escape rate F and the side escape rate S were calculated based on the number of escaped smoke pixels and the total number of smoke pixels.

[0074] Frontal escape rate ;

[0075] Side escape rate ;

[0076] Based on the front escape rate F and the side escape rate S and their corresponding coefficients, the final oil fume extraction effect score is obtained. For example, the front coefficient is 0.7 and the side coefficient is 0.3;

[0077] Fume extraction effect rating .

[0078] Step S30, as Figure 5 As shown, the oil pollution score of the range hood is obtained based on the oil pollution image of the range hood, including:

[0079] S31, obtaining an oil stain image of the range hood; the oil stain image is an image of key parts such as the oil screen, impeller, or volute taken by a high-resolution endoscopic camera.

[0080] S32, based on a preset neural network, obtain the oil pollution coverage ratio of the oil pollution image; specifically, a U-Net convolutional neural network can be used to perform pixel-level segmentation on the oil pollution image, and then output the oil pollution coverage ratio R oil The oil pollution coverage ratio is the ratio of the area occupied by the oil pollution to the entire target area.

[0081] Specifically, the oil stain image is scaled to 512×512, normalized to the range of [0,1], the input image is forward propagated through U-Net, and the oil stain probability P(x,y)∈[0,1] of each pixel is output;

[0082] Binarization mask generation:

[0083] ;

[0084] Area ratio calculation

[0085] ;

[0086] Example: If there are 65,536 oil-stained pixels in the mask, and the total number of pixels in 512×512 is 262,144, then R oil =65,536 / 262,144≈0.25, which means the oil pollution covers 25%.

[0087] S33, based on the oil stain image, obtain the saturation and brightness of the oil stain area; convert the oil stain image into the HSV color space, extract the saturation S and brightness V of the oil stain area, the darker the oil stain color, the more serious the pollution.

[0088] S34, obtaining an oil stain color depth coefficient based on the saturation and brightness of the oil stain area; defining the oil stain color depth coefficient C oil for ; where S max =255, V max =255.

[0089] S35: Obtaining the oil pollution score based on the oil pollution coverage area ratio and the oil pollution color depth coefficient. The oil pollution color depth coefficient and the oil pollution coverage area ratio are combined to obtain the oil pollution score.

[0090] ;

[0091] in It is the reference value used to normalize the oil pollution coverage area, usually 1. Less than or equal to 0.3, it is judged as light pollution. A value greater than 0.3 and less than or equal to 0.6 is considered moderate pollution. A value greater than 0.6 is considered severe pollution.

[0092] In step S40, a comprehensive score of the range hood is obtained based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood, such as Figure 6 Shown, including,

[0093] S41, based on the service life of the range hood, obtain an age coefficient; since the range hood will experience performance degradation and aging as it ages, it is divided into three stages according to the age. The formula is as follows: the total score increases by 5% each year in the first 5 years; when the range hood is 5-10 years old, the total score increases by 10% each year; when the range hood is more than 10 years old, the total score increases by 15% each year. Age coefficient as follows:

[0094] ;

[0095] S42: Based on the age coefficient of the range hood and the weighting coefficients of the noise score, the fume extraction effect score, and the oil pollution score, a comprehensive score of the range hood is obtained. The comprehensive score formula is:

[0096] ;

[0097] 、 、 For example, since noise and fume extraction are important for range hood performance, W1=0.4, W2=0.2, and W3=0.4. When Z is greater than 0 and less than or equal to 0.4, the range hood is in good condition and no action is required. When Z is greater than 0.4 and less than or equal to 0.7, the range hood needs cleaning. When Z is greater than 0.7, the range hood needs replacement.

[0098] Therefore, the method of this embodiment obtains the noise score, oil pollution score and oil fume extraction effect score respectively, and combines the age coefficient of the range hood to obtain a comprehensive score. The decision on whether to replace or clean the range hood is made based on the comprehensive score. Not only is the judgment accurate and fast, but the decision can also be updated and reminded in real time, giving users better cleaning options.

[0099] Example 2

[0100] Corresponding to the aforementioned range hood usage status detection method embodiment, the present disclosure also provides a range hood usage status monitoring device embodiment.

[0101] Figure 7 This is a module diagram of a range hood usage status detection device provided by an exemplary embodiment of the present disclosure, the system comprising:

[0102] Noise scoring module 1, used to obtain a noise score based on the noise frequency domain characteristics of the range hood;

[0103] The oil fume extraction effect scoring module 2 is used to obtain an oil fume extraction effect score based on the oil fume extraction image of the range hood;

[0104] The oil pollution scoring module 3 is used to obtain the oil pollution score of the range hood based on the oil pollution image of the range hood;

[0105] The comprehensive scoring module 4 is configured to obtain a comprehensive score of the range hood based on the noise score, the oil fume extraction effect score, the oil pollution score, and the age coefficient of the range hood.

[0106] Noise Scoring Module 1 also includes:

[0107] The spectrum conversion module 11 is used to collect the sound signal when the range hood is in use and convert it into a spectrum diagram. Since the sound signals collected by sensors are generally time domain signals, after Fourier transform, the time domain signal can be converted into a frequency domain signal to obtain a spectrum diagram as the basis for sound analysis.

[0108] The difference acquisition module 12 is used to extract the peak and trough differences of the abnormal frequency band based on the spectrum diagram; determine whether there is an obvious protrusion in the spectrum diagram, if there is, it means there is an abnormal frequency band, and extract the peak and trough values of the abnormal frequency band, for example For the crest, For the trough, The difference between the two is .

[0109] The first scoring module 13 is used to obtain a noise score based on the difference. s The sound may be heard if it is greater than 14. s The larger the value, the more obvious the abnormal sound. At this time, the noise score S can be calculated according to the abnormal sound scoring formula. noise This coefficient is used to judge the use status of the range hood. s When it is less than or equal to 14dB, S noise =0; when L s Greater than 14dB and less than or equal to 17dB, S noise =0.5+0.1(L s -14); when L s Greater than 17dB, S noise =1.0+0.2(L s -17); when L s The larger the value, the more serious the abnormal sound. noise The bigger.

[0110] ;

[0111] In addition, as another implementation method, since range hoods usually have multiple gears, in order to obtain the noise score more accurately, the sound signals of the range hood at multiple gears can be measured and converted into spectrograms respectively, and the abnormal frequency bands are extracted from the spectrograms at each gear to obtain the difference. The noise scores corresponding to different gears are obtained based on the difference, and the weighting coefficients are set according to the possible size ratios of the noises at different gears to obtain the final noise score.

[0112] The spectrum conversion module 11 is used to collect sound signals under multiple gears of the range hood and convert them into spectrum diagrams; the difference acquisition module 12 is used to extract the peak and trough differences of the abnormal frequency band based on the noise spectrum diagrams under multiple gears of the range hood; the first scoring module 13 is used to obtain the noise scores under multiple gears based on the differences, and determine the final noise score based on the weighting coefficient and noise score of each gear.

[0113] The oil fume extraction effect scoring module 2 specifically includes:

[0114] an escape rate acquisition module 21 for respectively obtaining a front escape rate and a side escape rate based on the front fume image and the side fume image of the range hood;

[0115] The second scoring module 22 is configured to obtain the oil fume extraction effect score based on the front escape rate and the side escape rate and corresponding coefficients.

[0116] Oil pollution scoring module 3 includes:

[0117] The oil stain image acquisition module 31 is used to acquire the oil stain image of the range hood; the oil stain image is an image of key parts such as the oil screen, impeller, or volute taken by a high-resolution endoscopic camera.

[0118] The oil pollution coverage ratio acquisition module 32 is used to obtain the oil pollution coverage ratio of the oil pollution image based on a preset neural network; specifically, a U-Net convolutional neural network can be used to perform pixel-level segmentation on the oil pollution image, and then output the oil pollution coverage ratio R oil The oil pollution coverage ratio is the ratio of the area occupied by the oil pollution to the entire target area.

[0119] The color acquisition module 33 is used to obtain the saturation and brightness of the oily area based on the oily image; convert the oily image into the HSV color space, and extract the saturation S and brightness V of the oily area. The darker the oily color, the more serious the pollution.

[0120] The color depth coefficient acquisition module 34 is used to obtain the oil stain color depth coefficient based on the saturation and brightness of the oil stain area; define the oil stain color depth coefficient C oil for .

[0121] Among them S max =255, V max =255.

[0122] The third scoring module 35 obtains the oil pollution score based on the oil pollution coverage area ratio and the oil pollution color depth coefficient. The oil pollution color depth coefficient and the oil pollution coverage area ratio are combined to finally obtain the oil pollution score.

[0123] Comprehensive scoring module 4 includes,

[0124] The age coefficient acquisition module 41 is used to obtain the age coefficient based on the age of the range hood; since the range hood has performance degradation and aging as it ages, it is divided into three stages according to the age. The formula is as follows: the total score increases by 5% each year in the first 5 years; when the range hood is 5-10 years old, the total score increases by 10% each year; when the range hood is more than 10 years old, the total score increases by 15% each year. Age coefficient as follows:

[0125] ;

[0126] The fourth scoring module 42 is used to obtain a comprehensive score of the range hood based on the age coefficient of the range hood and the weight coefficients of the noise score, the fume extraction effect score, and the oil pollution score. The comprehensive scoring formula is:

[0127] ;

[0128] 、 、 For example, since noise and fume extraction are important for range hood performance, W1=0.4, W2=0.2, and W3=0.4. When Z is greater than 0 and less than or equal to 0.4, the range hood is in good condition and no action is required. When Z is greater than 0.4 and less than or equal to 0.7, the range hood needs cleaning. When Z is greater than 0.7, the range hood needs replacement.

[0129] Since the system embodiments generally correspond to the method embodiments, reference will be made to the description of the method embodiments for relevant details. The system embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components of the units may or may not be physical units, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the disclosed solution.

[0130] Example 3

[0131] Figure 8 This is a structural diagram of an electronic device showing an example embodiment of the present disclosure. The electronic device includes a memory, a processor, and a computer program stored in the memory and used to run on the processor. When the processor executes the computer program, it implements the range hood usage status detection method described in any of the above embodiments. Figure 8 The electronic device 80 shown is only an example and should not limit the functionality and scope of use of the embodiments of the present disclosure.

[0132] like Figure 8 As shown, the electronic device 80 may be a general-purpose computing device, such as a server device. Components of the electronic device 80 may include, but are not limited to, the at least one processor 81, the at least one memory 82, and a bus 83 connecting different system components (including the memory 82 and the processor 81).

[0133] The bus 83 includes a data bus, an address bus, and a control bus.

[0134] The memory 82 may include a volatile memory, such as a random access memory (RAM) 821 and / or a cache memory 822 , and may further include a read-only memory (ROM) 823 .

[0135] The memory 82 may also include a program tool 825 (or utility) having a set (at least one) of program modules 824, such program modules 824 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include an implementation of a network environment.

[0136] The processor 81 executes various functional applications and data processing by running the computer program stored in the memory 82, such as the range hood usage status detection method provided in any of the above embodiments.

[0137] The electronic device 80 can also communicate with one or more external devices 84 (e.g., a keyboard, pointing device, etc.). This communication can occur via an input / output (I / O) interface 85. Furthermore, the electronic device 80 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 86. As shown, the network adapter 86 communicates with other modules of the electronic device 80 via a bus 83. It should be understood that, although not shown, other hardware and / or software modules can be used in conjunction with the electronic device 80, including but not limited to microcode, device drivers, redundant processors, external disk drive arrays, RAID (RAID) systems, tape drives, and data backup storage systems.

[0138] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the detailed description above, this division is merely exemplary and not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided and embodied by multiple units / modules.

[0139] Example 4

[0140] An embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the range hood usage status detection method provided in any of the above embodiments.

[0141] The readable storage medium may include, but is not limited to, a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0142] Example 5

[0143] An embodiment of the present disclosure further provides a computer program product, comprising a computer program, which, when executed by a processor, implements any of the above-mentioned range hood usage status detection methods.

[0144] The program code for executing the computer program product of the present disclosure may be written in any combination of one or more programming languages, and the program code may be executed entirely on the user device, partially on the user device, as a standalone software package, partially on the user device and partially on a remote device, or entirely on the remote device.

[0145] While specific embodiments of the present disclosure have been described above, those skilled in the art will appreciate that these are merely illustrative and that the scope of protection of the present disclosure is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present disclosure, and such changes and modifications are intended to fall within the scope of protection of the present disclosure.

Claims

1. A method for detecting the use status of a range hood, characterized in that: include, The noise score is obtained based on the frequency domain characteristics of the range hood noise; Obtaining a fume extraction effect score based on the fume extraction image of the range hood; Obtaining an oil pollution score of the range hood based on the oil pollution image of the range hood; A comprehensive score of the range hood is obtained based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood.

2. The range hood usage status detection method according to claim 1, wherein: The noise score obtained based on the noise frequency domain characteristics of the range hood includes: Collect the sound signal when the range hood is in use and convert it into a spectrum; Extracting peak and trough differences of abnormal frequency bands based on the noise spectrum of the range hood; A noise score is derived based on the difference.

3. The range hood usage status detection method according to claim 2, wherein: The obtaining of a noise score based on the difference comprises, ； S noise For rating, L s is the difference.

4. The range hood usage status detection method according to claim 1, wherein: The oil fume extraction effect score obtained based on the oil fume extraction image of the range hood includes: Obtaining a front escape rate and a side escape rate based on the front fume image and the side fume image of the range hood, respectively; The oil fume extraction effect score is obtained based on the front escape rate, the side escape rate and the corresponding coefficients.

5. The range hood usage status detection method according to claim 1, wherein: The oil pollution score of the range hood is obtained based on the oil pollution image of the range hood. include, Acquiring an oil stain image of the range hood; Obtaining the oil pollution coverage area ratio of the oil pollution image based on a preset neural network; obtaining the saturation and brightness of the oil stain area based on the oil stain image; Obtaining an oil stain color depth coefficient based on the saturation and brightness of the oil stain area; The oil pollution score is obtained based on the oil pollution coverage area ratio and the oil pollution color depth coefficient.

6. The range hood usage status detection method according to claim 1, wherein: The comprehensive score of the range hood is obtained based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood. include, Obtaining an age coefficient based on the service life of the range hood; Based on the age coefficient of the range hood and the weighting coefficients of the noise score, the oil fume extraction effect score, and the oil pollution score, a comprehensive score of the range hood is obtained.

7. The range hood usage status detection method according to claim 1, wherein: The age coefficient is obtained based on the service life of the range hood; include, ； Where age is the service life, F age is the age coefficient.

8. A range hood usage status detection device, characterized in that: include, Noise scoring module, used to obtain a noise score based on the noise frequency characteristics of the range hood; A fume extraction effect scoring module is used to obtain a fume extraction effect score based on the fume extraction image of the range hood; An oil pollution scoring module is used to obtain an oil pollution score of the range hood based on the oil pollution image of the range hood; A comprehensive scoring module is used to obtain a comprehensive score of the range hood based on the noise score, the oil fume extraction effect score, the oil pollution score and the age coefficient of the range hood.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and configured to run on the processor, wherein: When the processor executes the computer program, the range hood usage status detection method according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the range hood usage status detection method according to any one of claims 1 to 7 is implemented.

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