Temperature detection method and device, extractor hood and medium

Abstract

The application provides a temperature detection method and device, a range hood and a medium, which can be widely applied to the technical field of intelligent detection. The method comprises the following steps: obtaining a plurality of temperature data of a to-be-detected cooking area to form a temperature matrix; performing data preprocessing on the temperature matrix to obtain a filtering matrix, and performing binaryzation on the temperature data in the filtering matrix to obtain a binary matrix; extracting a connected domain from the binary matrix to obtain a high-temperature area; and obtaining a temperature detection result of the to-be-detected cooking area according to the temperature data corresponding to the high-temperature area in the temperature matrix. The application obtains the high-temperature area through the to-be-detected cooking area, dynamically tracks the high-temperature area, and then obtains the temperature detection result of the to-be-detected cooking area according to the temperature data corresponding to the high-temperature area in the temperature matrix, thereby relieving the problem of low detection accuracy caused by the unchanged area of temperature detection in the related art. The application embodiment is beneficial to improving the accuracy of temperature detection of the range hood.

Description

Technical Field

[0001] This application relates to the field of intelligent detection technology, and more specifically, to a temperature detection method, device, range hood, and medium. Background Technology

[0002] Smoke hoods play a vital role in production and daily life by removing smoke and other harmful gases, and are widely used in these areas.

[0003] In related technologies, infrared temperature probes are installed on the range hood to detect the temperature of the cooking area of ​​the stove. The average temperature of the area detected by the infrared temperature probe is taken as the current cooking temperature, and the range hood status is adjusted according to the current cooking temperature, which helps to realize the automatic smoke exhaust of the range hood.

[0004] However, the installation environment of a user's range hood varies, such as the distance between the range hood and the cooktop. Since infrared temperature probes are usually fixed and their detection angle cannot be adjusted, there will be a discrepancy between the detection area and the actual cooking area when the infrared temperature probe measures the temperature of the cooktop. This results in the problem of low temperature detection accuracy in the above-mentioned method of measuring the temperature of a fixed area. Summary of the Invention

[0005] The first technical problem solved by this application is to provide a temperature detection method that effectively alleviates the problem of low detection accuracy caused by the invariance of the temperature detection area in related technologies, and improves the accuracy of temperature detection in range hoods.

[0006] The second technical problem solved by this application is to provide a temperature detection method and apparatus that effectively alleviates the problem of low detection accuracy caused by the invariance of the temperature detection area in related technologies, and improves the accuracy of temperature detection in the smoke machine.

[0007] The third technical problem solved by this application is to provide a range hood that effectively alleviates the problem of low detection accuracy caused by the constant temperature detection area in related technologies, and improves the accuracy of temperature detection in the range hood.

[0008] The fourth technical problem solved by this application is to provide a computer-readable storage medium that effectively alleviates the problem of low detection accuracy caused by the invariance of the temperature detection area in the related art, and improves the accuracy of temperature detection in the smoke machine.

[0009] The first technical problem mentioned above is solved by the following technical solution:

[0010] A temperature detection method, comprising:

[0011] Acquire multiple temperature data points of the cooking area to be detected and form a temperature matrix;

[0012] The temperature matrix is ​​preprocessed to obtain a filtering matrix, and the temperature data in the filtering matrix is ​​binarized to obtain a binary matrix.

[0013] The high-temperature region is obtained by extracting the connected components from the binary matrix.

[0014] Based on the temperature data corresponding to the high-temperature region in the temperature matrix, the temperature detection result of the cooking area to be detected is obtained.

[0015] Compared with the prior art, the temperature detection method described in this application has the following advantages: by acquiring temperature data from multiple temperature regions of the cooking area to be detected, a temperature matrix is ​​obtained; then, the temperature data is binarized to form a binary matrix, and the high-temperature region is obtained through connected component extraction; thereby, the high-temperature region that best reflects the cooking state of the cooking area to be detected is dynamically tracked, and the temperature detection result of the cooking area to be detected is obtained based on the temperature data corresponding to the high-temperature region in the temperature matrix, which alleviates the problem of low detection accuracy caused by the invariance of the temperature detection region in related technologies; and is conducive to improving the accuracy of temperature detection of the range hood.

[0016] In one embodiment, obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature region in the temperature matrix includes:

[0017] Summing all temperature data corresponding to the highest temperature region with the largest area in the temperature matrix yields the sum of temperatures.

[0018] The sum of the areas corresponding to all high-temperature regions in the temperature matrix is ​​obtained.

[0019] The average temperature is determined based on the quotient of the sum of the temperatures and the sum of the areas.

[0020] The temperature detection result is determined based on the product of the mean temperature and the area weighting factor.

[0021] In one embodiment, before determining the temperature detection result based on the average temperature and the area weighting factor, the method further includes:

[0022] The area ratio is determined by the quotient of the area of ​​the high-temperature zone and the reference area; wherein the reference area is related to the heating area of ​​the stove.

[0023] The area weighting factor is determined based on the product of the area ratio and the area weighting coefficient; wherein the area weighting coefficient is related to one or more of the following: stove power, stove size, stove shape, and stove material.

[0024] In one embodiment, obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature region in the temperature matrix includes:

[0025] ;

[0026] in, The temperature detection result is... This refers to the high-temperature region. The coordinates of the temperature data within the high-temperature region are given. The temperature data, For the temperature and, Area weighting factor This is the area weighting coefficient. For the sum of areas, The base area.

[0027] In one embodiment, obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature region in the temperature matrix includes:

[0028] Summing all temperature data corresponding to the high-temperature region in the temperature matrix yields the sum of temperatures.

[0029] The temperature detection result is determined based on the quotient of the temperature and the area of ​​the high-temperature region.

[0030] In one embodiment, extracting the connected components from the binary matrix to obtain the high-temperature region includes:

[0031] The binary matrix is ​​opened to obtain a first matrix; the opening operation is used to retain the temperature data representing high temperature in the filter matrix.

[0032] Perform a closing operation on the first matrix to obtain a new binary matrix;

[0033] Based on the new binary matrix, connected components are extracted to obtain the high-temperature region.

[0034] In one embodiment, the step of preprocessing the temperature matrix to obtain a filter matrix includes:

[0035] The temperature data in the temperature matrix is ​​filtered by a preset kernel size to obtain a filter matrix;

[0036] Alternatively, the first temperature data in the temperature matrix can be weighted and averaged according to at least one of the domain weight and the numerical weight to obtain filtered data; wherein the first temperature data is any temperature data in the temperature matrix.

[0037] The second technical problem mentioned above is solved by the following technical solution:

[0038] A temperature detection device, comprising:

[0039] The acquisition module is used to acquire multiple temperature data of the cooking area to be detected and form a temperature matrix;

[0040] The filtering module is used to preprocess the temperature matrix to obtain a filtering matrix, and to binarize the temperature data in the filtering matrix to obtain a binary matrix.

[0041] The extraction module is used to extract connected components from the binary matrix to obtain the high-temperature region;

[0042] The detection module is used to obtain the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix.

[0043] Compared with the prior art, the temperature detection method described in this application has the following advantages: it acquires temperature data from multiple temperature regions of the cooking area to be detected to obtain a temperature matrix; then it performs binarization processing on the temperature data to form a binary matrix, and extracts the high-temperature region through connected component extraction; thereby realizing dynamic tracking of the high-temperature region that best reflects the cooking state of the cooking area to be detected, and then obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature region in the temperature matrix, which alleviates the problem of low detection accuracy caused by the invariance of the temperature detection area in related technologies; and is conducive to improving the accuracy of temperature detection of the range hood.

[0044] The third technical problem mentioned above is solved by the following technical solution:

[0045] A range hood includes a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the temperature detection method described above through the computer program.

[0046] Compared with the prior art, the temperature detection method described in this application has the following advantages: by acquiring temperature data from multiple temperature regions of the cooking area to be detected, a temperature matrix is ​​obtained; then, the temperature data is binarized to form a binary matrix, and the high-temperature region is obtained through connected component extraction; thereby, the high-temperature region that best reflects the cooking state of the cooking area to be detected is dynamically tracked, and the temperature detection result of the cooking area to be detected is obtained based on the temperature data corresponding to the high-temperature region in the temperature matrix, which alleviates the problem of low detection accuracy caused by the invariance of the temperature detection region in related technologies; and is conducive to improving the accuracy of temperature detection of the range hood.

[0047] The fourth technical problem mentioned above is solved by the following technical solution:

[0048] A computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the temperature detection method described above.

[0049] Compared with the prior art, the temperature detection method of this application has the following advantages: by acquiring temperature data from multiple temperature regions of the cooking area to be detected, a temperature matrix is ​​obtained; then, the temperature data is binarized to form a binary matrix, and the high-temperature region is obtained through connected component extraction; thereby, the high-temperature region that best reflects the cooking state of the cooking area to be detected is dynamically tracked, and the temperature detection result of the cooking area to be detected is obtained based on the temperature data corresponding to the high-temperature region in the temperature matrix, which alleviates the problem of low detection accuracy caused by the invariance of the temperature detection region in related technologies; therefore, the embodiments of this application are beneficial to improving the accuracy of temperature detection of range hoods. Attached Figure Description

[0050] The accompanying drawings, which form part of this application, are used to provide a further understanding of this application. The illustrative embodiments and descriptions of this application are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0051] Figure 1 A schematic diagram illustrating an application scenario of a temperature detection method provided in an embodiment of this application is shown.

[0052] Figure 2 A schematic flowchart of a temperature detection method provided in an embodiment of this application is shown;

[0053] Figure 3 A schematic flowchart of another temperature detection method provided according to an embodiment of this application is shown;

[0054] Figure 4 A schematic flowchart of the opening operation provided according to an embodiment of this application is shown;

[0055] Figure 5 A schematic flowchart of the closing operation provided according to an embodiment of this application is shown;

[0056] Figure 6 A schematic diagram of a temperature detection device provided in an embodiment of this application is shown. Detailed Implementation

[0057] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0058] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0059] 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 for the embodiments of this application 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 apparatus 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 apparatus.

[0060] Due to variations in the installation location, height, and spacing between cooktops, the infrared array temperature measurement covers inconsistent temperature detection areas, affecting the accuracy of temperature detection in the temperature-controlled cooktop-cooktop linkage system and making it difficult to accurately identify the cooktop's operating status. This application's technology initializes a large infrared temperature detection area and divides it into multiple smaller areas for distributed temperature acquisition. It analyzes the distribution characteristics of temperature values ​​within each smaller area in real time. When certain smaller areas show significantly high temperatures while other areas are lower, the system determines that the high-temperature concentration area is the cooktop burner area, and the low-temperature area is a non-working area. Subsequently, it automatically and dynamically shrinks the overall temperature detection area towards the high-temperature concentration area, achieving adaptive adjustment of the detection range and accurately focusing on the actual heat source location. This technology effectively improves the accuracy and stability of infrared temperature measurement under different installation environments and cooktop layouts. It can adaptively identify and lock onto the actual heating area of ​​the cooktop burner, avoiding misjudgments or response delays caused by the temperature detection area deviating from the heat source, significantly improving the intelligence level and user experience of the cooktop-cooktop linkage system.

[0061] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0062] The methods and embodiments provided in this application can be executed in a range hood, a computer terminal associated with the range hood, or a similar computing device. Taking operation on a range hood as an example, Figure 1 This is a hardware structure block diagram of a range hood using a temperature detection method according to an embodiment of the present invention. Figure 1 As shown, a range hood may include one or more ( Figure 1 Only one is shown in the image. A processor 102 (which may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.) and a memory 104 for storing data are also shown. The range hood may further include a transmission device 106 for communication functions and an input / output device 108. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the range hood described above. For example, the range hood may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0063] The memory 104 can be used to store computer programs, such as application software programs and modules, like the computer program corresponding to the temperature detection method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the computer program stored in the memory 104, thereby implementing the above-described method. The memory 104 may include high-speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the range hood via a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The transmission device 106 is used to receive or send data via a network. Specific examples of the aforementioned networks may include wireless networks provided by the range hood's communication provider. In one example, the transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0064] This embodiment provides a temperature detection method that runs on a range hood, a computer terminal associated with the range hood, or a similar computing device. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0065] It should be noted that the information collected in this application is information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, storage, use, processing, transmission, provision, disclosure, and application of this data all comply with the relevant laws, regulations, and standards of the relevant countries and regions, and necessary confidentiality measures have been taken. This process does not violate public order and good morals, and corresponding access points are provided for users to choose whether to authorize or refuse. The automated decision-making involved in this application provides users with corresponding access points to choose whether to agree to or refuse the automated decision-making results; if the user chooses to refuse, the process proceeds to the expert decision-making stage.

[0066] Figure 2 This is a schematic flowchart of a temperature detection method according to an embodiment of this application. The temperature detection method includes:

[0067] Step S100: Acquire multiple temperature data of the cooking area to be detected and form a temperature matrix;

[0068] Step S200: Perform data preprocessing on the temperature matrix to obtain a filter matrix, and binarize the temperature data in the filter matrix to obtain a binary matrix;

[0069] Step S300: Extract the connected components from the binary matrix to obtain the high-temperature region;

[0070] Step S400: Based on the temperature data corresponding to the high-temperature region in the temperature matrix, obtain the temperature detection result of the cooking area to be detected.

[0071] Understandably, in related technologies, the high-temperature point (usually the burner) is typically determined before the use of the range hood. During subsequent use, the range hood's status is adjusted by monitoring the temperature of this high-temperature point. However, this approach cannot dynamically adjust the high-temperature point based on the cooktop's operating environment. In contrast, this application first detects the cooking area to be detected, obtaining multiple temperature data points. The cooking area to be detected can be the area of ​​the cooktop surface corresponding to the range hood. Of course, those skilled in the art can adjust the range of the cooking area to be detected according to actual needs. The temperature matrix is ​​preprocessed to remove points with large temperature variations and smooth the temperature data to obtain a filtering matrix. The specific preprocessing method can be selected as needed; for example, it can be a moving average method, median filtering, or low-pass filtering. This application does not limit the specific method of data preprocessing. Then, this application binarizes the filtered data to facilitate subsequent high-temperature area extraction and temperature determination. Binarization can be achieved by numerically transforming each temperature data point relative to a preset temperature threshold. Connectivity analysis is performed on the binary matrix to extract the connected components, thus obtaining the high-temperature regions. In some embodiments, the connected components are related to the burners on the stove surface. The connected components are used to characterize the area of ​​the stove surface; the number of connected components corresponds to the number of burners on the stove surface, meaning the number of high-temperature regions obtained is the same as the number of burners. In this application, the temperature data of the high-temperature regions is detected and analyzed to obtain the temperature detection result of the cooking area to be detected. This application can adaptively process the temperature of the stove surface, alleviating the problem of stove surface temperature detection not considering the environment in related technologies, and improving the accuracy of stove surface temperature detection.

[0072] Optionally, based on the temperature data corresponding to the high-temperature region in the temperature matrix, the temperature detection result of the cooking area to be detected is obtained, including:

[0073] Summing all temperature data corresponding to the highest temperature region with the largest area in the temperature matrix yields the sum of temperatures.

[0074] The sum of the areas corresponding to all high-temperature regions in the temperature matrix is ​​obtained.

[0075] The average temperature is determined based on the quotient of the sum of the temperatures and the sum of the areas.

[0076] The temperature detection result is determined by the product of the average temperature and the area weighting factor.

[0077] This application synthesizes the temperatures within a high-temperature region to obtain the temperature detection result of the cooking area to be detected. In some embodiments, this application sums the temperature data of the highest-temperature region by summing the areas of the highest-temperature regions, and then divides the sum of temperatures by the area of ​​all high-temperature regions to obtain the average temperature of the high-temperature regions. In some embodiments, area weighting is added to improve the accuracy of temperature detection. It can be understood that the area of ​​the current high-temperature region is normalized based on a reference area; then, an area weighting factor is used as a coefficient to linearly amplify this normalized area. In this application, the area weighting factor is a number greater than 1. Using the area weighting factor as a gain term, the area weighting factor is positively correlated with the area of ​​the high-temperature region; that is, the larger the area, the higher the characteristic temperature. For large pots with a large cross-sectional dimension, estimating the temperature detection result based on the average temperature would underestimate the heat load, causing deviations in the temperature detection result. Therefore, this application improves the detection accuracy of the range hood's temperature detection through an area weighting factor.

[0078] Optionally, before determining the temperature detection result based on the temperature mean and area weighting factor, the method further includes:

[0079] The area ratio is determined by the quotient of the area of ​​the high-temperature zone and the reference area; where the reference area is related to the heating area of ​​the stove.

[0080] The area weighting factor is determined by the product of the area ratio and the area weighting coefficient; wherein the area weighting coefficient is related to one or more of the following: stove power, stove size, stove shape, and stove material.

[0081] The reference area in this application can be the area of ​​the standard heating area of ​​the burner in the cooktop design, or it can be the heating area corresponding to the burner measured before testing. It is understood that the burner in this application refers to the burner or burner unit of the cooktop. In some embodiments, the area coefficient is related to one or more of the cooktop power, cooktop size, cooktop shape, and cooktop material. The cooktop power, cooktop size, cooktop shape, and cooktop material can be stored in the range hood by the user through data input, or the above parameters can be detected by a detection device installed on the range hood to determine the area weight, and thus determine the area weighting factor. This application improves the accuracy of temperature feature synthesis for cooktop temperature detection through the area weighting factor.

[0082] Optionally, based on the temperature data corresponding to the high-temperature region in the temperature matrix, the temperature detection result of the cooking area to be detected is obtained, including:

[0083] ;

[0084] in, For temperature detection results, This is a high-temperature area. The coordinates for temperature data within the high-temperature region. For temperature data, For temperature and, Area weighting factor This is the area weighting coefficient. For the sum of areas, The base area.

[0085] This application uses the above formula to perform feature calculations on the temperature data of the high-temperature region of the temperature matrix to obtain the temperature of the high-temperature region, i.e., the temperature of the cooking region.

[0086] Optionally, based on the temperature data corresponding to the high-temperature region in the temperature matrix, the temperature detection result of the cooking area to be detected is obtained, including:

[0087] Summing all temperature data corresponding to the high-temperature region in the temperature matrix yields the sum of temperatures.

[0088] The temperature detection result is determined by the ratio of temperature to the area of ​​the high-temperature region.

[0089] In some embodiments, this application may use the average temperature of the high-temperature zone of the cooking area as the temperature detection result.

[0090] Optionally, connected components can be extracted from the binary matrix to obtain the high-temperature region, including:

[0091] The binary matrix is ​​opened to obtain the first matrix; the opening operation is used to retain the temperature data representing high temperature in the filter matrix.

[0092] Perform a closing operation on the first matrix to obtain a new binary matrix;

[0093] Based on the new binary matrix, connected components are extracted to obtain the high-temperature region.

[0094] Understandably, the opening operation is used to remove scattered areas and retain the temperature data representing high temperature in the filter matrix, while the closing operation is used to connect adjacent high temperature areas to achieve the initial extraction of the high temperature area range. This application uses the opening and closing operations to process the temperature area, providing a prerequisite for the temperature calculation of the cooking area to be detected.

[0095] Optionally, the temperature matrix is ​​preprocessed to obtain a filtering matrix, including:

[0096] The temperature data in the temperature matrix is ​​filtered by a preset kernel size to obtain the filtering matrix;

[0097] Alternatively, the first temperature data in the temperature matrix can be weighted and averaged according to at least one of the domain weight and the numerical weight to obtain the filtered data; wherein the first temperature data is any temperature data in the temperature matrix.

[0098] This application can perform median filtering using a preset kernel size. The preset kernel size can be determined based on the size of the temperature data region; in some embodiments, the preset kernel size can be 3. 3, or it could be 5 5. This application does not limit the specific range of the preset kernel size. In other embodiments, each temperature data in the temperature matrix is ​​weighted and averaged using neighborhood weights and numerical weights. Exemplarily, the neighborhood weights provide weights for temperature data other than the current temperature data, and the neighborhood weights are proportional to the distance between the other temperature data and the current temperature data. Numerical weights can be provided based on other temperature data besides the current temperature data. Of course, those skilled in the art can design weight values ​​based on other features. This application preprocesses the data in the temperature matrix through filtering to eliminate the influence of isolated temperature points on the detected temperature results.

[0099] Optionally, the high-temperature region is obtained based on the connected components, including:

[0100] The connected regions are sorted in descending order of area, and a predetermined number of connected regions at the top of the first sort are selected as high-temperature regions; wherein, the predetermined number is equal to the number of burners in the cooking area to be detected.

[0101] When extracting high-temperature regions, this application determines the number of high-temperature regions based on the number of burners in the cooking area to be detected. In some embodiments, high-temperature regions are filtered according to their area. In other embodiments, high-temperature regions can be filtered according to their temperature. In still other embodiments, connected regions are sorted based on at least one of their area and temperature, and high-temperature regions are obtained from the sorted connected regions. Of course, those skilled in the art can also sort and filter connected regions using other parameters, and this application does not impose specific limitations.

[0102] Optionally, the temperature data in the filter matrix is ​​binarized to obtain a binary matrix, including:

[0103] If the temperature data is greater than a preset temperature threshold, the temperature data is converted into a first marker value;

[0104] If the temperature data is less than or equal to a preset temperature threshold, the temperature data is converted into a second label value; wherein, the preset temperature threshold is related to the largest first temperature in the temperature matrix;

[0105] The method provided in this application also includes the following method, which determines a preset temperature threshold through the following steps:

[0106] Determine the preset proportional coefficient based on one or more of the following: stove power, stove material, stove size, and ambient temperature;

[0107] A preset temperature threshold is determined based on the first temperature and a preset proportional coefficient.

[0108] In some embodiments, the first marker value in this application can be 1, and the second marker value can be 0, then the high-temperature region is the region marked as 1. The preset temperature threshold is related to the first temperature. After determining the preset temperature threshold, this application determines the preset temperature threshold based on the product of the first temperature and a preset proportionality coefficient.

[0109] Optionally, in this application, a connected component is extracted from the binary matrix to obtain a high-temperature region, including:

[0110] A first pass is performed on the binary matrix to establish a temporary label for the first data in the binary matrix. Based on the temporary labels of the neighborhood data of the first data, a label equivalence relation is established for the first data. Herein, the first data is any data in the binary matrix.

[0111] Based on the label equivalence relation, determine the equivalence set and assign target labels to the label equivalence relation;

[0112] A second scan is performed on the binary matrix, and the temporary label of the first data is replaced with the corresponding target label to obtain the labeled connected component. Based on the connected component, the high-temperature region is obtained.

[0113] This application uses a connected component labeling algorithm to extract connected components from a binary matrix.

[0114] Optionally, the temperature matrix includes multiple second temperature data in addition to the first temperature data. Before performing a weighted average on the first temperature data in the temperature matrix according to at least one of neighborhood weight and numerical weight to obtain the filtered data, the method further includes:

[0115] Based on the distance between the first temperature data and the second temperature data, a neighborhood weight for the second temperature data is determined; wherein, the neighborhood weight is negatively correlated with the distance.

[0116] The numerical weight of the second temperature data is determined based on the numerical difference between the first temperature data and the second temperature data; wherein the numerical difference is greater than zero, and the numerical weight is negatively correlated with the numerical difference.

[0117] To achieve the above objectives, according to another aspect of this application, a temperature detection device is provided, such as... Figure 6 As shown, it includes:

[0118] The acquisition module 610 is used to acquire multiple temperature data of the cooking area to be detected and form a temperature matrix;

[0119] The filtering module 620 is used to preprocess the temperature matrix to obtain a filtering matrix, and to binarize the temperature data in the filtering matrix to obtain a binary matrix.

[0120] Extraction module 630 is used to extract connected components from a binary matrix to obtain the high-temperature region;

[0121] The detection module 640 is used to obtain the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix.

[0122] According to another aspect of this application, a range hood is provided, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to execute the temperature detection method described above through the computer program.

[0123] According to another aspect of this application, a computer-readable storage medium is provided, including a stored program, wherein, when the program is executed, it controls the device where the computer-readable storage medium is located to perform the above-described temperature detection method.

[0124] According to another aspect of this application, a computer program product is provided, including computer instructions that, when executed by a processor, implement the steps of the temperature detection method described above.

[0125] Compared with the prior art, the temperature detection method of this application has the following advantages: This application acquires temperature data from multiple temperature regions of the cooking area to be detected to obtain a temperature matrix; then, the temperature data is binarized to form a binary matrix, and the high-temperature region is obtained through connected component extraction; thereby, the high-temperature region that best reflects the cooking state of the cooking area to be detected is dynamically tracked, and the temperature detection result of the cooking area to be detected is obtained based on the temperature data corresponding to the high-temperature region in the temperature matrix, which alleviates the problem of low detection accuracy caused by the invariance of the temperature detection region in related technologies; therefore, the embodiments of this application are beneficial to improving the accuracy of temperature detection of range hoods.

[0126] To enable those skilled in the art to better understand the technical solution of this application, the implementation process of the temperature detection method of this application will be described in detail below with reference to specific embodiments.

[0127] When pots and pans are placed on the stovetop, uneven heating can occur, making it inaccurate to calculate the temperature using the average temperature of a given area. Therefore, the following methods can be used for temperature calculation during cooking: Figure 3 As shown.

[0128] Step 1: Data preprocessing (median filtering);

[0129] The original temperature matrix is ​​subjected to 3×3 median filtering to eliminate isolated noise points.

[0130] ;

[0131] in: : The temperature value in the i-th row and j-th column of the original temperature matrix; Offset, with a value range of -1, 0, and 1, representing the 3×3 neighborhood around the current point; Temperature values ​​of the current point and its 8 neighboring points (9 points in total); {...}: Take the median (not the average) of these 9 temperature values; Temperature value after median filtering.

[0132] Step 2: Extraction in a high-temperature zone;

[0133] Calculate the maximum value in the entire temperature matrix: ;

[0134] Set high temperature threshold ,in α This is the scaling factor (recommended 0.6). (0.8), which can be dynamically adjusted according to the power of the stove.

[0135] Generate a binary matrix : That is, if the temperature at this point is greater than the high temperature threshold, it is marked as 1 (high temperature zone); otherwise, it is marked as 0 (non-high temperature zone).

[0136] Step 3: Morphological processing and connected component analysis;

[0137] like Figure 4 As shown, for Perform opening operations (corrosion followed by dilation, see...) Figure 4 The last two steps (in the process) remove small, scattered areas: ○B=( B)⊕B;

[0138] like Figure 5 As shown, a closing operation is then performed (corrosion after expansion, see...). Figure 5 (The last two steps in the process), connecting adjacent high-temperature zones: ●B=( ⊕B) B;

[0139] Use a connected component labeling algorithm (such as the Two-pass algorithm) to find all connected components and calculate the area of ​​each connected component. Sk .

[0140] Step 4: Characteristic temperature synthesis;

[0141] The average temperature of a high-temperature region represents the heating intensity, but the area also affects the total heat generated. Therefore, a characteristic temperature is defined as follows:

[0142] ;

[0143] in It is the sum of the areas of all high-temperature regions. It is a reference area (such as the standard heating area of ​​the stove burner). This is the area weighting coefficient (recommended value: 0.2~0.5). This represents the sum of temperatures in the highest-temperature region with the largest area in the temperature matrix. This formula appropriately increases the characteristic temperature as the area of ​​the high-temperature region increases, better reflecting the actual heat load. Through the area weighting provided in this application, the large boiler area automatically amplifies the temperature, ensuring that the temperature detection results truly reflect the required flue gas volume and improving the accuracy of temperature detection.

[0144] For simplicity, the average temperature of all high-temperature areas can also be used directly:

[0145] ;

[0146] This technology is applicable to various smart range hood and cooktop linkage products, and can effectively improve the reliability of temperature detection in different kitchen installation environments, reduce the risk of misoperation, and enhance the user's cooking experience.

[0147] It should be noted that the above are merely illustrative examples and do not specifically limit the implementation logic.

[0148] It is obvious to those skilled in the art that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0149] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0151] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0152] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0153] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0154] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0155] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0156] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0157] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0158] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. 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 temperature detection method, characterized in that, The temperature detection method includes: Acquire multiple temperature data points of the cooking area to be detected and form a temperature matrix; The temperature matrix is ​​preprocessed to obtain a filtering matrix, and the temperature data in the filtering matrix is ​​binarized to obtain a binary matrix. The high-temperature region is obtained by extracting the connected components from the binary matrix. Based on the temperature data corresponding to the high-temperature region in the temperature matrix, the temperature detection result of the cooking area to be detected is obtained.

2. The temperature detection method according to claim 1, characterized in that, The step of obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix includes: Summing all temperature data corresponding to the highest temperature region with the largest area in the temperature matrix yields the sum of temperatures. The sum of the areas corresponding to all high-temperature regions in the temperature matrix is ​​obtained. The average temperature is determined based on the quotient of the sum of the temperatures and the sum of the areas. The temperature detection result is determined based on the product of the mean temperature and the area weighting factor.

3. The temperature detection method according to claim 2, characterized in that, Before determining the temperature detection result based on the mean temperature and the area weighting factor, the method further includes: The area ratio is determined by the quotient of the area of ​​the high-temperature zone and the reference area; wherein the reference area is related to the heating area of ​​the stove. The area weighting factor is determined based on the product of the area ratio and the area weighting coefficient; wherein the area weighting coefficient is related to one or more of the following: stove power, stove size, stove shape, and stove material.

4. The temperature detection method according to claim 3, characterized in that, The step of obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix includes: ； in, The temperature detection result is... This refers to the high-temperature region. The coordinates of the temperature data within the high-temperature region are given. The temperature data, For the temperature and, Area weighting factor This is the area weighting coefficient. For the sum of the areas, The base area.

5. The temperature detection method according to claim 1, characterized in that, The step of obtaining the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix includes: Summing all temperature data corresponding to the high-temperature region in the temperature matrix yields the sum of temperatures. The temperature detection result is determined based on the quotient of the temperature and the area of ​​the high-temperature region.

6. The temperature detection method according to claim 1, characterized in that, The step of extracting connected components from the binary matrix to obtain the high-temperature region includes: An opening operation is performed on the binary matrix to obtain a first matrix; wherein the opening operation is used to retain the temperature data representing high temperature in the filter matrix; Perform a closing operation on the first matrix to obtain a new binary matrix; Based on the new binary matrix, connected components are extracted to obtain the high-temperature region.

7. The temperature detection method according to claim 6, characterized in that, The step of preprocessing the temperature matrix to obtain a filtering matrix includes: The temperature data in the temperature matrix is ​​filtered by a preset kernel size to obtain a filter matrix; Alternatively, the first temperature data in the temperature matrix can be weighted and averaged according to at least one of the domain weight and the numerical weight to obtain filtered data; wherein the first temperature data is any temperature data in the temperature matrix.

8. A temperature detection device, characterized in that, The temperature detection device includes: The acquisition module is used to acquire multiple temperature data of the cooking area to be detected and form a temperature matrix; The filtering module is used to preprocess the temperature matrix to obtain a filtering matrix, and to binarize the temperature data in the filtering matrix to obtain a binary matrix. The extraction module is used to extract connected components from the binary matrix to obtain the high-temperature region; The detection module is used to obtain the temperature detection result of the cooking area to be detected based on the temperature data corresponding to the high-temperature area in the temperature matrix.

9. A range hood, characterized in that, The range hood includes: A memory and a processor, wherein the memory stores a computer program, and the processor is configured to execute the temperature detection method according to any one of claims 1 to 7 via the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the temperature detection method according to any one of claims 1 to 7.

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