A scale thickness detection method, device, equipment and storage medium
By acquiring baseline humidity and temperature data from kitchen appliances and calculating scale thickness using the law of thermal conduction, the problem of uneven scale distribution is solved, enabling real-time detection and early warning of scale thickness, thus improving the accuracy and timeliness of detection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-01-21
- Publication Date
- 2026-05-29
AI Technical Summary
The uneven distribution of limescale in existing kitchen appliances makes it difficult for users to accurately determine whether cleaning is needed, resulting in delayed cleaning, which affects the normal use of the equipment and increases energy consumption.
By acquiring baseline humidity and temperature data at a preset temperature, using infrared and humidity sensors to collect pixel data in a scale-free state, and combining Fourier's law of thermal conductivity to calculate scale thickness, real-time detection and early warning can be achieved.
It enables real-time detection and early warning of scale thickness, improving the accuracy and timeliness of detection and avoiding the adverse effects of scale accumulation on equipment.
Smart Images
Figure CN122108029A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of intelligent kitchen appliance testing technology, and in particular to a method, apparatus, equipment and storage medium for detecting scale thickness. Background Technology
[0002] With the improvement of people's living standards and the promotion and popularization of technologies such as the Internet, big data, artificial intelligence, and voice interaction, more and more traditional lifestyles are gradually changing, and the use of kitchen appliances is gradually moving towards intelligence. During daily cooking, kitchen appliances such as steam ovens, steam ovens, or kettles produce water steam. When the temperature of tap water rises, soluble bicarbonates decompose into insoluble carbonates, which adhere to the surface of the cavity, forming limescale. Limescale has a low thermal conductivity, and long-term accumulation can lead to a decrease in the thermal efficiency of kitchen appliances, increased energy consumption, and, with the accumulation of limescale, it can also clog and corrode steam pipes, wasting energy and posing safety hazards.
[0003] In existing technologies, descaling is mainly done actively, which means that users subjectively judge the thickness of the scale layer and actively clean it. However, the scale is unevenly distributed inside the cavity, and users cannot accurately judge whether cleaning is needed at this time, which often results in the inability to clean the scale in time and affects the normal use of kitchen appliances. Summary of the Invention
[0004] To address existing problems, this invention provides a method, apparatus, device, and storage medium for detecting scale thickness. It acquires humidity and temperature at a preset temperature in a scale-free state. After a period of use, humidity is acquired at the same temperature. Without affecting detection, the scale thickness at each pixel is determined using the current temperature and a reference temperature. The scale thickness is calculated pixel by pixel using temperature data. This solves the problem of complex and difficult-to-quantify scale distribution, achieving real-time scale thickness detection and early warning. It also considers the impact of steam and humidity on detection accuracy, improving the accuracy of scale thickness detection.
[0005] In a first aspect, embodiments of this application provide a method for detecting scale thickness, the method comprising: At a preset temperature, acquire baseline humidity data and baseline temperature data for multiple pixels; the baseline humidity data and baseline temperature data are the humidity data and temperature data of the cavity to be tested in a scale-free state; Obtain current humidity data at a preset temperature; If the current humidity data is less than or equal to the baseline humidity data, obtain the current temperature data of multiple pixels; Based on the reference temperature data and current temperature data of multiple pixels, the scale thickness data of multiple pixels is determined.
[0006] In an optional embodiment, after acquiring the current humidity data at a preset temperature, the method further includes: If the current humidity data is greater than the baseline humidity data, a drying command is sent to the drying module of the cavity to be tested; the drying command is used to instruct the drying module to dry the cavity to be tested. Acquire the current temperature data of multiple pixels at a preset temperature.
[0007] In one optional embodiment, the scale thickness data of multiple pixels is determined based on reference temperature data and current temperature data of multiple pixels, including: Acquire the heat transfer area, current voltage data, current current data, and thermal conductivity of the scale layer of the cavity under test; Perform the following for each pixel out of a total of pixels: The pixel being processed is identified as the current pixel. Based on the reference temperature data of the current pixel, determine the temperature difference of the scale layer at the current pixel. The scale thickness data for the current pixel is determined based on the scale temperature difference, heat transfer area, current voltage data, current current data, and scale thermal conductivity.
[0008] In an optional embodiment, after determining the scale thickness data for multiple pixels based on reference temperature data and current temperature data for multiple pixels, the method further includes: The average scale thickness is determined based on scale thickness data from multiple pixels. If the average scale thickness is greater than the first thickness threshold, a descaling command is sent to the descaling module of the cavity to be tested.
[0009] In an optional embodiment, after determining the scale thickness data for multiple pixels based on reference temperature data and current temperature data for multiple pixels, the method further includes: The first thickness data and the second thickness data are determined from the scale thickness data of multiple pixels; the first thickness data is greater than or equal to other thickness data of the multiple scale thickness data except the first thickness data; the second thickness data is less than or equal to other thickness data of the multiple scale thickness data except the second thickness data. Based on the scale thickness data of multiple pixels, the first thickness data, and the second thickness data, the gray value corresponding to the scale thickness data of each pixel is determined. A thermal imaging pseudo-color coding algorithm is used to generate pseudo-color images based on multiple grayscale values.
[0010] In an optional embodiment, after determining the scale thickness data for multiple pixels based on reference temperature data and current temperature data for multiple pixels, the method further includes: The cumulative thickness data is determined by summing the dirt thickness data of multiple pixels; If the cumulative thickness data is greater than the second thickness threshold, the first thickness data is determined by the dirt thickness data of multiple pixels. Determine the first position data of the pixel corresponding to the first thickness data in the cavity to be detected; Descaling prompts are generated based on the first thickness data and the first position data.
[0011] In an optional embodiment, after determining the scale thickness data for multiple pixels based on reference temperature data and current temperature data for multiple pixels, the method further includes: Obtain the cooking interval duration and the previous scale thickness data for multiple pixels; the cooking interval duration is the time elapsed since the last cooking. The scale thickness growth rate is determined based on the cooking interval, scale thickness data of multiple pixels, and previous scale thickness data. If the rate of increase in scale thickness exceeds the growth rate threshold, a drying prompt message is generated; the drying prompt message is used to remind the user to dry the chamber to be tested.
[0012] Secondly, embodiments of this application provide a scale thickness detection device, the device comprising: The first acquisition module is used to acquire reference humidity data and reference temperature data of multiple pixels at a preset temperature; the reference humidity data and reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state. The second acquisition module is used to acquire current humidity data at a preset temperature. The third acquisition module is used to acquire the current temperature data of multiple pixels when the current humidity data is less than or equal to the reference humidity data; The determination module is used to determine the scale thickness data of multiple pixels based on the reference temperature data and the current temperature data of multiple pixels.
[0013] Thirdly, embodiments of this application provide an intelligent kitchen appliance, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor loads and executes the at least one instruction, at least one program, code set, or instruction set to implement the scale thickness detection method of the first aspect.
[0014] Fourthly, embodiments of this application provide a computer-readable storage medium storing at least one instruction or at least one program, wherein the at least one instruction or at least one program is loaded and executed by a processor to implement the scale thickness detection method of the first aspect.
[0015] Fifthly, embodiments of this application provide a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the scale thickness detection method of the first aspect.
[0016] The scale thickness detection method, apparatus, equipment, and storage medium provided in this application have the following technical effects: The process involves acquiring baseline humidity data and baseline temperature data for multiple pixels at a preset temperature. The baseline humidity and temperature data represent the humidity and temperature data of the chamber under test in a scale-free state. Current humidity data is acquired at the preset temperature. If the current humidity data is less than or equal to the baseline humidity data, current temperature data for multiple pixels is acquired. Based on the baseline temperature data and current temperature data for multiple pixels, the scale thickness data for multiple pixels is determined. In this embodiment, humidity and temperature are acquired at a preset temperature in a scale-free state. After a period of use, humidity is acquired at the same temperature. Without affecting the detection, the scale thickness for each pixel is determined using the current temperature and the baseline temperature. By calculating the scale thickness pixel by pixel using temperature data, the problem of complex and difficult-to-quantify scale distribution is solved, achieving real-time scale thickness detection and early warning. Simultaneously, the impact of steam and humidity on detection accuracy is considered, improving the accuracy of scale thickness detection. Attached Figure Description
[0017] To more clearly illustrate the technical solutions and advantages in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0018] Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 1 ; Figure 3 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 2 ; Figure 4 This is a flowchart illustrating a method for generating a pseudo-color image according to an embodiment of this application; Figure 5This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 3 ; Figure 6 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 4 ; Figure 7 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 5 ; Figure 8 This is a schematic diagram of the structure of a scale thickness detection device provided in an embodiment of this application; Figure 9 This is a hardware structure block diagram of a server for a scale thickness detection method provided in an embodiment of this application. Detailed Implementation
[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.
[0020] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or server that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices.
[0021] Please see Figure 1 , Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application. The steam oven 100 includes an infrared sensor 101, a control module 102, a heating module 103, a drying module 104, and a humidity sensor 105.
[0022] In one possible embodiment, the steam oven 100 includes a cavity to be tested, in which scale accumulates and is unevenly distributed.
[0023] In one possible embodiment, the infrared sensor 101 and the humidity sensor 105 are disposed inside the cavity to be tested in the steam oven 100. The infrared temperature data can be collected at a set collection frequency and sent to the control module 102. The humidity sensor 105 collects the humidity data in the cavity to be tested according to the instructions and sends it to the control module 102.
[0024] In one possible embodiment, the heating module 103 is part of the steam oven 100 and can heat the cavity to be tested to a set temperature according to the set temperature.
[0025] In one possible embodiment, the drying module 104 is part of the steam oven 100 and can dry the cavity to be tested according to instructions to remove residual moisture in the cavity.
[0026] In one possible embodiment, the control module 102 acquires reference humidity data and reference temperature data of multiple pixels at a preset temperature; the reference humidity data and reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state; acquires current humidity data at the preset temperature; acquires current temperature data of multiple pixels when the current humidity data is less than or equal to the reference humidity data; and determines scale thickness data of multiple pixels based on the reference temperature data and current temperature data of multiple pixels.
[0027] In this embodiment, humidity and temperature are acquired at a preset temperature under a scale-free state. After a period of use, humidity is acquired at the same temperature. Without affecting the detection, the scale thickness at each pixel is determined using the current temperature and a reference temperature. By calculating the scale thickness pixel by pixel using temperature data, the problem of complex planar distribution of scale, which is difficult to quantify and evaluate, is solved. This achieves the technical effect of real-time scale thickness detection and early warning, while also taking into account the impact of steam and humidity on detection accuracy, thus improving the accuracy of scale thickness detection.
[0028] The following describes a specific embodiment of a scale thickness detection method according to this application. Figure 2 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 1 This specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many and does not represent the only execution order. In actual system or server products, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment). Specifically, as shown in the embodiments or drawings... Figure 2 As shown, it may include: S201: Acquire reference humidity data and reference temperature data of multiple pixels at a preset temperature; the reference humidity data and reference temperature data are the humidity data and temperature data of the cavity to be tested in a scale-free state.
[0029] S202: Obtain current humidity data at a preset temperature.
[0030] S203: When the current humidity data is less than or equal to the reference humidity data, obtain the current temperature data of multiple pixels.
[0031] S204: Determine the scale thickness data of multiple pixels based on the reference temperature data and current temperature data of multiple pixels.
[0032] Figure 3 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 2 The method may include: S301: Establish the mapping relationship between the infrared sensor and the cavity to be detected.
[0033] In one possible embodiment, the mapping relationship between the infrared sensor and the coordinate system of the cavity to be detected can convert the pixel position of the infrared image into the physical spatial position of the cavity to be detected. In other words, the pixel position of the pixel on the infrared image can be converted into the actual position on the cavity to be detected through the mapping relationship.
[0034] Specifically, the process of establishing the mapping relationship between the infrared sensor and the coordinate system of the cavity to be detected can include: First, establishing a two-dimensional image coordinate system with the origin (0, 0) at the center of the infrared focal plane array and a unit pixel spacing; establishing a three-dimensional physical coordinate system (x, y, z) with the geometric center of the cavity to be detected as the origin; attaching high emissivity feature points, such as black cross marks or ceramic dots, to the inner surface of the cavity; accurately measuring the three-dimensional coordinates of each point in the cavity coordinate system; the infrared sensor perpendicularly aligning with the cavity surface to capture images, obtaining the pixel coordinates of the feature points in the infrared image; establishing a projection model using a perspective projection transformation model; constructing a system of equations for N sets of feature points (N≥6); and then solving for the optimal rotation and translation matrix from the sensor to the cavity using the least squares algorithm; finally, lens distortion, including radial and tangential distortion, can be compensated. The rotation and translation matrix after distortion compensation is the mapping relationship described in this application.
[0035] S302: Acquire reference humidity data and reference temperature data of multiple pixels at a preset temperature.
[0036] In one possible embodiment, the reference humidity data and reference temperature data are the humidity data and temperature data of the cavity to be tested in a scale-free state.
[0037] Specifically, when the steam oven is new and has no thermal resistance (i.e., the scale thickness is 0 and there is no scale), it automatically starts the scale self-check mode. The user sets the temperature T as the preset temperature. After the operating temperature stabilizes, the infrared sensor collects and records the temperature data of each pixel as the reference temperature data T. h (x, y), humidity data collected by the humidity sensor is used as the reference humidity data RH. h .
[0038] S303: Obtain current humidity data at a preset temperature.
[0039] In this embodiment of the application, after running for a period of time, scale gradually accumulates, and a self-test mode is activated to detect the scale thickness.
[0040] S304: Determine if the current humidity data is greater than the baseline humidity data. If yes, execute S305; otherwise, execute S306.
[0041] S305: Sends a drying command to the drying module of the cavity to be tested. First, obtain the current humidity data (RH) at the preset temperature. s Determine the current humidity data (RH). s Is it greater than the baseline humidity data (RH)? h If RH s >RH h Send a drying command to the drying module of the cavity to be tested to dry the accumulated water. If RH s ≤RH h This allows for subsequent temperature monitoring. In this embodiment, the drying command is used to instruct the drying module to dry the cavity to be tested and reset the temperature to the preset temperature to remove the water accumulated in the cavity to be tested, so as to avoid the interference of steam generated after heating on the infrared data.
[0042] S306: Obtain the current temperature data of multiple pixels at a preset temperature.
[0043] In one possible embodiment, an infrared sensor acquires the current temperature data T of multiple pixels under scale-inhibiting conditions at a preset temperature. s (x, y).
[0044] S307: Determine the scale thickness data of multiple pixels based on the reference temperature data and current temperature data of multiple pixels.
[0045] Because scale and metal substrates have different temperature conduction properties, the scale thickness data of each pixel can be used to form a detailed and complete scale thickness distribution data by using Fourier's law of heat conduction.
[0046] In one optional embodiment, the scale thickness data of multiple pixels is determined based on reference temperature data and current temperature data of multiple pixels, including: S3071: Obtain the heat transfer area, current voltage data, current current data, and thermal conductivity of the scale layer of the cavity to be tested.
[0047] In this embodiment, the heat transfer area of the cavity to be tested is A, the current voltage data is U, the current current data is I, and the thermal conductivity of the scale layer is k.
[0048] Perform the following for each pixel out of a total of pixels: S3072: Determine the currently executing pixel as the current pixel.
[0049] S3073: Determine the temperature difference of the scale layer at the current pixel based on the reference temperature data and the current temperature data.
[0050] In this embodiment, the temperature difference of the scale layer can be determined as Th(x,y)-T using reference temperature data and current temperature data. s (x, y).
[0051] S3074: Determine the scale thickness data of the current pixel based on the scale temperature difference, heat transfer area, current voltage data, current current data, and scale thermal conductivity.
[0052] According to Fourier's law of heat conduction, heat flux density Therefore, the thickness of the dirt layer on a single pixel .
[0053] In this embodiment, the heating power data P is first calculated by multiplying the current voltage data U and the current current data I, and then the heat flux density is calculated by multiplying the heating power data P and the heat transfer area A. Finally, the scale thickness data of the current pixel is calculated using the heat flux density q and the scale thermal conductivity k. .
[0054] By calculating the scale thickness data of each pixel in real time, a scale distribution heat map is generated and the currently detected scale thickness data is stored.
[0055] Figure 4 This is a flowchart illustrating a method for generating a pseudo-color image according to an embodiment of this application. The method may include: S401: Determine the first thickness data and the second thickness data from the dirt thickness data of multiple pixels.
[0056] In one possible embodiment, the first thickness data is greater than or equal to other thickness data among a plurality of scale thickness data, excluding the first thickness data, which is the maximum scale thickness.
[0057] In one possible embodiment, the second thickness data is less than or equal to other thickness data among a plurality of scale thickness data, excluding the second thickness data, which is the minimum scale thickness.
[0058] S402: Based on the scale thickness data of multiple pixels, the first thickness data, and the second thickness data, determine the gray value corresponding to the scale thickness data of each pixel.
[0059] In this embodiment, the scale thickness is mapped to a grayscale range of 0-255 to avoid data overload. Specifically, the mapping value = (scale thickness value) / (scale thickness value) (Minimum scale thickness) / (Maximum scale thickness) Minimum scale thickness) × 255.
[0060] S403: A pseudo-color image is generated based on multiple grayscale values using a thermal imaging pseudo-color coding algorithm.
[0061] Then, a thermal imaging pseudo-color coding algorithm is used to convert the temperature value into a pseudo-color image. The values of the three channels are R=a×|sin(b×x)|, G=a×|sin(b×x+c)|, and B=a×|sin(b×x+2c)|, where a=255, b=2π / 255, c=π / 5, and x is the gray value after temperature mapping.
[0062] By mapping the scale thickness to a grayscale range and combining it with a thermal imaging pseudo-color coding algorithm, the scale thickness on the inner wall of the cavity under test can be displayed intuitively on a screen, solving the problem of insufficiently intuitive scale distribution and achieving the technical effect of visualizing scale thickness.
[0063] Figure 5 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 3 The method may include: S501: Determine the average scale thickness based on scale thickness data from multiple pixels.
[0064] S502: Determine whether the average scale thickness is greater than the first thickness threshold. If yes, execute S503; otherwise, execute S504.
[0065] S503: Send a descaling command to the descaling module of the cavity to be tested.
[0066] S504: Continue testing.
[0067] In one possible embodiment, the average scale thickness is calculated using the scale thickness data of all pixels. If the average scale thickness is greater than a first thickness threshold, it indicates that there is a lot of scale, which may affect normal use, and the descaling program needs to be started to remove the scale. If the average scale thickness is less than or equal to the first thickness threshold, it indicates that there is less scale, and the scale needs to be detected again. After a set time, the self-test mode is started to continue detecting the scale thickness.
[0068] Figure 6 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 4 The method may include: S601: Determine the cumulative thickness data based on the sum of the dirt thickness data of multiple pixels.
[0069] S602: Determine whether the cumulative thickness data is greater than the second thickness threshold. If yes, execute S603; otherwise, execute S406.
[0070] S603: Determine the first thickness data from the dirt thickness data of multiple pixels.
[0071] S604: Determine the first position data of the pixel corresponding to the first thickness data in the cavity to be detected.
[0072] S605: Generate descaling prompt information based on the first thickness data and the first position data.
[0073] S606: Continue testing.
[0074] In one possible embodiment, the cumulative thickness data is obtained by calculating the sum of the scale thickness data of multiple pixels. If the cumulative thickness data is greater than the second thickness threshold, it indicates that there is a lot of scale at this time, and the user needs to be prompted to remove the scale, but it does not affect normal use. If the cumulative thickness data is less than or equal to the second thickness threshold, it indicates that there is less scale at this time, and scale needs to be detected again. After a set time, the self-test mode is activated to continue detecting the scale thickness.
[0075] In this embodiment, the first thickness data, i.e., the maximum scale thickness, is determined from the scale thickness data of multiple pixels. The first position data of the maximum scale thickness within the cavity to be tested is also determined. Based on the maximum scale thickness and its position, a descaling prompt message is generated and sent to the user. Alternatively, a flashing red descaling alarm light can be used to prompt the user to perform descaling in a timely manner.
[0076] Figure 7 This is a flowchart illustrating a method for detecting scale thickness provided in an embodiment of this application. Figure 5 The method may include: S701: Obtain the cooking interval duration and the previous scale thickness data for multiple pixels.
[0077] In this embodiment of the application, the cooking interval duration T n This refers to the time elapsed since the last cooking, and the previous scale thickness data. This is the scale thickness data obtained after the previous cooking.
[0078] S702: Determine the scale thickness growth rate based on cooking interval duration, scale thickness data of multiple pixels, and previous scale thickness data.
[0079] In this embodiment of the application, based on the cooking interval T n Data on the thickness of the scale layer at multiple pixels Compared with the previous dirt thickness data Calculate the fouling thickness growth rate .
[0080] S703: Determine whether the fouling thickness growth rate is greater than the growth rate threshold. If yes, execute S704; otherwise, execute S705.
[0081] S704: Generate drying prompt information.
[0082] In this embodiment, the drying prompt information is used to remind the user to dry the cavity to be tested.
[0083] S705: Continue testing.
[0084] In one possible embodiment, by calculating the scale thickness growth rate, if the scale thickness growth rate is greater than the growth rate threshold, it indicates that the scale is growing rapidly and the user needs to be prompted to perform descaling, but this does not affect normal use and automatic descaling is not required. If the scale thickness growth rate is less than or equal to the growth rate threshold, it indicates that the scale is growing slowly and the scale needs to be monitored. After a set time, the self-test mode is activated to continue monitoring the scale thickness.
[0085] This application also provides a scale thickness detection device. Figure 8 This is a schematic diagram of a scale thickness detection device provided in an embodiment of this application, as shown below. Figure 8 As shown, the device 800 includes: The first acquisition module 801 is used to acquire reference humidity data and reference temperature data of multiple pixels at a preset temperature; the reference humidity data and reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state. The second acquisition module 802 is used to acquire current humidity data at a preset temperature; The third acquisition module 803 is used to acquire the current temperature data of multiple pixels when the current humidity data is less than or equal to the reference humidity data. The determination module 804 is used to determine the scale thickness data of multiple pixels based on the reference temperature data and the current temperature data of multiple pixels.
[0086] In an optional embodiment, it further includes: The first sending module is used to send a drying command to the drying module of the cavity to be tested when the current humidity data is greater than the reference humidity data; the drying command is used to instruct the drying module to dry the cavity to be tested. The fourth acquisition module is used to acquire the current temperature data of multiple pixels at a preset temperature.
[0087] In an optional embodiment, it further includes: The fifth acquisition module is used to acquire the heat transfer area, current voltage data, current current data, and thermal conductivity of the scale layer of the cavity to be tested. Perform the following for each pixel out of a total of pixels: The first determining module is used to determine the pixel being executed as the current pixel. The second determining module is used to determine the scale temperature difference of the current pixel based on the reference temperature data of the current pixel. The third determination module is used to determine the scale thickness data of the current pixel based on the scale temperature difference, heat transfer area, current voltage data, current current data, and scale thermal conductivity.
[0088] In an optional embodiment, after determining the scale thickness data for multiple pixels based on reference temperature data and current temperature data for multiple pixels, the method further includes: The fourth determination module is used to determine the average scale thickness based on scale thickness data from multiple pixels. The second sending module is used to send a descaling command to the descaling module of the cavity to be tested if the average scale thickness is greater than the first thickness threshold.
[0089] In an optional embodiment, it further includes: The fifth determining module is used to determine a first thickness data and a second thickness data from the scale thickness data of multiple pixels; the first thickness data is greater than or equal to other thickness data other than the first thickness data among the multiple scale thickness data; the second thickness data is less than or equal to other thickness data other than the second thickness data among the multiple scale thickness data. The sixth determining module is used to determine the gray value corresponding to the scale thickness data of each pixel based on the scale thickness data of multiple pixels, the first thickness data, and the second thickness data. The image generation module is used to generate a pseudo-color image based on multiple grayscale values using a thermal imaging pseudo-color coding algorithm.
[0090] In an optional embodiment, it further includes: The seventh determination module is used to determine the cumulative thickness data based on the sum of the dirt thickness data of multiple pixels; The eighth determining module is used to determine the first thickness data based on the dirt thickness data of multiple pixels if the cumulative thickness data is greater than the second thickness threshold. The ninth determining module is used to determine the first position data of the pixel corresponding to the first thickness data in the cavity to be detected; The first information generation module is used to generate descaling prompt information based on the first thickness data and the first position data.
[0091] In an optional embodiment, it further includes: The sixth acquisition module is used to acquire the cooking interval duration and the previous dirt thickness data of multiple pixels; the cooking interval duration is the time since the last cooking. The tenth determination module is used to determine the scale thickness growth rate based on the cooking interval duration, scale thickness data of multiple pixels, and previous scale thickness data; The second information generation module is used to generate a drying prompt message if the scale thickness growth rate is greater than the growth rate threshold; the drying prompt message is used to remind the user to dry the cavity to be tested.
[0092] The apparatus and method embodiments in this application are based on the same application concept.
[0093] The methods and embodiments provided in this application can be executed on a computer terminal, server, or similar computing device. Taking running on a server as an example, Figure 9 This is a hardware structure block diagram of a server for a scale thickness detection method provided in an embodiment of this application. For example... Figure 9As shown, the server 900 can vary significantly due to different configurations or performance. It may include one or more central processing units (CPUs) 910 (CPUs 910 may include, but are not limited to, microprocessors such as MCUs or programmable logic devices such as FPGAs), a memory 930 for storing data, and one or more storage media 920 (e.g., one or more mass storage devices) for storing application programs 923 or data 922. The memory 930 and storage media 920 may be temporary or persistent storage. The program stored in the storage media 920 may include one or more modules, each module may include a series of instruction operations on the server. Furthermore, the CPU 910 may be configured to communicate with the storage media 920 and execute the series of instruction operations stored in the storage media 920 on the server 900. Server 900 may also include one or more power supplies 960, one or more wired or wireless network interfaces 950, one or more input / output interfaces 940, and / or one or more operating systems 921, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.
[0094] The input / output interface 940 can be used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of server 900. In one example, the input / output interface 940 includes a network interface controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the input / output interface 940 may be a radio frequency (RF) module used for wireless communication with the Internet.
[0095] Those skilled in the art will understand that Figure 9 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, server 900 may also include... Figure 9 The more or fewer components shown, or having the same Figure 9 The different configurations shown.
[0096] This application provides an intelligent kitchen appliance, which includes a processor and a memory. The memory stores at least one instruction, at least one program, code set, or instruction set. The processor loads and executes the at least one instruction, at least one program, code set, or instruction set to implement the above-described data processing method.
[0097] Embodiments of this application also provide a computer-readable storage medium, which can be disposed in a server to store at least one instruction, at least one program, code set, or instruction set related to implementing a scale thickness detection method in the method embodiment. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the above-described scale thickness detection method.
[0098] Optionally, in this embodiment, the storage medium may be located at at least one of the multiple network servers in a computer network. Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.
[0099] As can be seen from the embodiments of the scale thickness detection method, apparatus, device, or storage medium provided in this application, this application acquires reference humidity data and reference temperature data of multiple pixels at a preset temperature; the reference humidity data and reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state; the current humidity data is acquired at the preset temperature; when the current humidity data is less than or equal to the reference humidity data, the current temperature data of multiple pixels is acquired; based on the reference temperature data and current temperature data of multiple pixels, the scale thickness data of multiple pixels is determined. In the embodiments of this application, humidity and temperature at a preset temperature are acquired in a scale-free state, and after a period of use, humidity is acquired at the same temperature. When humidity does not affect the detection, the scale thickness of each pixel is determined using the current temperature and the reference temperature. By solving the scale thickness pixel by pixel using temperature data, the problem of complex planar distribution of scale that is difficult to quantify and evaluate is solved, achieving the technical effect of real-time detection and early warning of scale thickness, while taking into account the influence of steam and humidity on the detection accuracy, thus improving the accuracy of scale thickness detection.
[0100] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. Furthermore, specific embodiments have been described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
[0101] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.
[0102] Those skilled in the art will understand that all or part of the steps of the above embodiments can be implemented by hardware or by a program instructing related hardware. The program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk.
[0103] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.
Claims
1. A method for detecting scale thickness, characterized in that, include: Acquire baseline humidity data and baseline temperature data for multiple pixels at a preset temperature; The reference humidity data and the reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state. Obtain the current humidity data at the preset temperature; If the current humidity data is less than or equal to the reference humidity data, the current temperature data of the plurality of pixels is obtained; Based on the reference temperature data and current temperature data of the multiple pixels, the scale thickness data of the multiple pixels is determined.
2. The method for detecting scale thickness according to claim 1, characterized in that, After acquiring the current humidity data at the preset temperature, the process further includes: If the current humidity data is greater than the reference humidity data, a drying command is sent to the drying module of the cavity to be tested; the drying command is used to instruct the drying module to dry the cavity to be tested. The current temperature data of the plurality of pixels is obtained at the preset temperature.
3. The method for detecting scale thickness according to claim 1, characterized in that, The determination of the scale thickness data of the multiple pixels based on the reference temperature data and the current temperature data of the multiple pixels includes: The heat transfer area, current voltage data, current current data, and thermal conductivity of the scale layer of the cavity under test are obtained. Perform the following for each of the plurality of pixels: The pixel being executed is identified as the current pixel; Based on the reference temperature data of the current pixel and the current temperature data, the scale temperature difference of the current pixel is determined; Based on the scale temperature difference, heat transfer area, current voltage data, current current data, and scale thermal conductivity, the scale thickness data of the current pixel is determined.
4. The method for detecting scale thickness according to claim 1, characterized in that, After determining the scale thickness data of the plurality of pixels based on the reference temperature data and the current temperature data of the plurality of pixels, the method further includes: The average scale thickness is determined based on the scale thickness data of the multiple pixels. If the average scale thickness is greater than the first thickness threshold, a descaling command is sent to the descaling module of the cavity to be tested.
5. The method for detecting scale thickness according to claim 1, characterized in that, After determining the scale thickness data of the plurality of pixels based on the reference temperature data and the current temperature data of the plurality of pixels, the method further includes: A first thickness data and a second thickness data are determined from the scale thickness data of the plurality of pixels; the first thickness data is greater than or equal to other thickness data among the plurality of scale thickness data except the first thickness data; the second thickness data is less than or equal to other thickness data among the plurality of scale thickness data except the second thickness data. Based on the scale thickness data of the multiple pixels, the first thickness data and the second thickness data, determine the gray value corresponding to the scale thickness data of each pixel; A pseudo-color image is generated based on multiple grayscale values using a thermal imaging pseudo-color coding algorithm.
6. The method for detecting scale thickness according to claim 1, characterized in that, After determining the scale thickness data of the plurality of pixels based on the reference temperature data and the current temperature data of the plurality of pixels, the method further includes: The cumulative thickness data is determined based on the sum of the dirt thickness data of the multiple pixels; If the cumulative thickness data is greater than the second thickness threshold, the first thickness data is determined from the dirt thickness data of the plurality of pixels. Determine the first position data of the pixel point corresponding to the first thickness data in the cavity to be detected; Descaling prompts are generated based on the first thickness data and the first location data.
7. The method for detecting scale thickness according to claim 1, characterized in that, After determining the scale thickness data of the plurality of pixels based on the reference temperature data and the current temperature data of the plurality of pixels, the method further includes: Obtain the cooking interval duration and the previous scale thickness data of the multiple pixels; the cooking interval duration is the time elapsed since the last cooking. Based on the cooking interval duration, the scale thickness data of the multiple pixels, and the previous scale thickness data, the scale thickness growth rate is determined. If the rate of increase in scale thickness is greater than the growth rate threshold, a drying prompt message is generated; the drying prompt message is used to remind the user to dry the cavity to be tested.
8. A scale thickness detection device, characterized in that, include: The first acquisition module is used to acquire reference humidity data and reference temperature data of multiple pixels at a preset temperature. The reference humidity data and the reference temperature data are humidity data and temperature data of the cavity to be tested in a scale-free state. The second acquisition module is used to acquire current humidity data at the preset temperature; The third acquisition module is used to acquire the current temperature data of the plurality of pixels when the current humidity data is less than or equal to the reference humidity data; The determination module is used to determine the scale thickness data of the multiple pixels based on the reference temperature data and the current temperature data of the multiple pixels.
9. A smart kitchen appliance, characterized in that, The intelligent kitchen appliance includes a processor and a memory. The memory stores at least one instruction, at least one program, a code set, or an instruction set. The at least one instruction, the at least one program, the code set, or the instruction set is loaded and executed by the processor to implement the scale thickness detection method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one instruction or at least one program, which is loaded and executed by a processor to implement the scale thickness detection method as described in any one of claims 1-7.