Oil temperature state evaluation method, intelligent range hood, computer equipment and storage medium

Abstract

The invention relates to an oil temperature state evaluation method, an intelligent range hood, computer equipment and a storage medium, and the oil temperature state evaluation method comprises the steps: carrying out the infrared thermal imaging of a target region above the oil surface in a cooking utensil, so as to obtain a real-time temperature matrix corresponding to the target region; the real-time temperature matrix comprises a plurality of temperature values, and each temperature value corresponds to a corresponding position in the target area; based on the real-time temperature matrix, determining a corresponding temperature field information entropy and a time change rate of the temperature field information entropy; determining the characteristic oil temperature in the cooking utensil based on the real-time temperature matrix; and determining the oil temperature level in the cooking utensil based on the characteristic oil temperature and the time change rate of the temperature field information entropy. According to the method and the device, the problem that the oil temperature state cannot be accurately evaluated during cooking is solved, the oil temperature state can be accurately evaluated in the cooking process, meanwhile, non-contact evaluation is adopted, the detection convenience and safety are improved, and the requirement of healthy cooking is better met.

Description

Technical Field

[0001] This application relates to the field of smart home appliances, and in particular to oil temperature status assessment methods, smart range hoods, computer equipment, and storage media. Background Technology

[0002] In daily cooking, precise control of oil temperature is crucial for both cooking results and dietary health. Commonly used cooking oils have a fixed smoke point critical temperature. When the temperature of the cooking oil exceeds this smoke point, the oil will undergo a thermal degradation reaction, which not only destroys the nutritional components of the oil itself, but also produces fumes containing carcinogens, harming human health.

[0003] However, in actual cooking operations, there is a lack of effective means to assess the oil temperature. Users cannot accurately perceive and judge the oil temperature. They can only rely on experience to roughly estimate the oil temperature by observing the state of the oil surface and the amount of smoke produced, which easily leads to the oil temperature being too high.

[0004] There is currently no effective solution to the problem of inaccurate oil temperature assessment during cooking in related technologies. Summary of the Invention

[0005] This embodiment provides a method for assessing oil temperature, a smart range hood, a computer device, and a storage medium to address the problem in related technologies where oil temperature cannot be accurately assessed during cooking.

[0006] Firstly, this embodiment provides a method for assessing oil temperature status, including:

[0007] Infrared thermal imaging is performed on a target area above the oil surface inside a cooking appliance to obtain a real-time temperature matrix corresponding to the target area; the real-time temperature matrix includes multiple temperature values, each temperature value corresponding to a corresponding position in the target area;

[0008] Based on the real-time temperature matrix, the corresponding temperature field information entropy and the time change rate of the temperature field information entropy are determined.

[0009] Based on the real-time temperature matrix, the characteristic oil temperature inside the cooking appliance is determined;

[0010] The oil temperature level within the cooking appliance is determined based on the characteristic oil temperature and the time change rate of the temperature field information entropy.

[0011] In some embodiments, performing infrared thermal imaging on a target area above the oil surface inside the cooking appliance to obtain a real-time temperature matrix corresponding to the target area includes:

[0012] By using an infrared sensor with a preset pixel array, the target area above the oil surface inside the cooking appliance is sampled to obtain the output voltage corresponding to each pixel position in the preset pixel array;

[0013] Based on preset calibration coefficients, the output voltage corresponding to each pixel position is linearized and calibrated to generate the corresponding real-time temperature matrix.

[0014] In some embodiments, determining the corresponding temperature field information entropy based on the real-time temperature matrix includes:

[0015] Based on each temperature value in the real-time temperature matrix, determine the normalized temperature distribution probability corresponding to each temperature value;

[0016] According to the Shannon entropy formula, the normalized temperature distribution probability corresponding to each temperature value is calculated to obtain the temperature field information entropy.

[0017] In some embodiments, determining the characteristic oil temperature within the cooking appliance based on the real-time temperature matrix includes:

[0018] The temperature values ​​in the real-time temperature matrix are sorted to determine the maximum temperature value among them.

[0019] The maximum temperature value is used as the characteristic oil temperature within the cooking appliance.

[0020] In some embodiments, determining the oil temperature level within the cooking appliance based on the characteristic oil temperature and the time-varying rate of change of the temperature field information entropy includes:

[0021] When the characteristic oil temperature is detected to be greater than a first preset threshold, and the time change rate of the temperature field information entropy is greater than a preset change rate threshold, the oil temperature level in the cooking appliance is determined to be a dangerous level.

[0022] In some embodiments, the method further includes:

[0023] When the characteristic oil temperature is detected to be greater than the second preset threshold, the stove power of the cooking appliance is controlled to be reduced to the first preset level, and the fan speed of the smart range hood used by the cooking appliance is dynamically increased; the second preset threshold is greater than the first preset threshold.

[0024] In some embodiments, the method further includes:

[0025] When the characteristic oil temperature is detected to be continuously greater than a third preset threshold and less than the first preset threshold within a preset time period, the heat of the stove used by the cooking appliance is controlled to be reduced to a second preset level.

[0026] Secondly, this embodiment provides an intelligent range hood, which includes an infrared sensor and a controller;

[0027] The infrared sensor is used to perform infrared thermal imaging on a target area above the oil surface inside the cooking appliance to obtain a real-time temperature matrix corresponding to the target area; the real-time temperature matrix includes multiple temperature values, each of which corresponds to a corresponding position in the target area;

[0028] The controller is used to determine the corresponding temperature field information entropy and the time change rate of the temperature field information entropy based on the real-time temperature matrix.

[0029] The controller is also used to determine the characteristic oil temperature inside the cooking appliance based on the real-time temperature matrix;

[0030] The controller is also used to determine the oil temperature level in the cooking appliance based on the characteristic oil temperature and the time change rate of the temperature field information entropy.

[0031] Thirdly, this embodiment provides a computer device including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the oil temperature status assessment method described in the first aspect above.

[0032] Fourthly, this embodiment provides a storage medium storing a computer program that, when executed by a processor, implements the oil temperature status assessment method described in the first aspect above.

[0033] Compared with related technologies, the oil temperature assessment method, intelligent range hood, computer equipment, and storage medium provided in this embodiment obtain a real-time temperature matrix corresponding to the target area by performing infrared thermal imaging on the target area above the oil surface inside the cooking appliance. The real-time temperature matrix includes multiple temperature values, each corresponding to a specific location in the target area. Based on the real-time temperature matrix, the corresponding temperature field entropy and the time change rate of the temperature field entropy are determined. Based on the real-time temperature matrix, the characteristic oil temperature inside the cooking appliance is determined. Based on the characteristic oil temperature and the time change rate of the temperature field entropy, the oil temperature level inside the cooking appliance is determined. This solves the problem of inaccurate oil temperature assessment during cooking, enabling accurate assessment of oil temperature during the cooking process. Furthermore, the non-contact assessment method improves the convenience and safety of detection and better meets the needs of healthy cooking.

[0034] Details of one or more embodiments of this application are set forth in the following drawings and description to make other features, objects and advantages of this application more readily apparent. Attached Figure Description

[0035] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0036] Figure 1 This is a structural block diagram of an intelligent range hood provided in one embodiment of this application;

[0037] Figure 2 This is a flowchart of an oil temperature condition assessment method provided in an embodiment of this application;

[0038] Figure 3 This is a flowchart of a method for obtaining a real-time temperature matrix according to an embodiment of this application;

[0039] Figure 4 This is a flowchart of an oil temperature condition assessment method provided in an embodiment of this application;

[0040] Figure 5 This is a flowchart of a characteristic oil temperature determination method provided in an embodiment of this application;

[0041] Figure 6 This is a flowchart of an oil temperature rating assessment method provided in an embodiment of this application.

[0042] In the diagram: 100, Smart Range Hood; 101, Controller; 102, Infrared Sensor; 103, Memory; 104, Fan Drive Module; 105, Light Module; 106, Switch Module; 107, Communication Module. Detailed Implementation

[0043] To better understand the purpose, technical solution, and advantages of this application, the application is described and explained below in conjunction with the accompanying drawings and embodiments.

[0044] Unless otherwise defined, the technical or scientific terms used in this application shall have the general meaning understood by one of ordinary skill in the art to which this application pertains. Words such as “a,” “an,” “an,” “the,” “the,” and “these” used in this application do not indicate quantitative limitation and may be singular or plural. The terms “comprising,” “including,” “having,” and any variations thereof used in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or modules (units) is not limited to the listed steps or modules (units) but may include steps or modules (units) not listed, or may include other steps or modules (units) inherent to these processes, methods, products, or devices. Words such as “connected,” “linked,” and “coupled” used in this application are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. “Multiple” used in this application refers to two or more. “And / or” describes the relationship between related objects, indicating that three relationships may exist; for example, “A and / or B” can represent: A alone, A and B simultaneously, and B alone. Normally, the character " / " indicates that the objects before and after it are in an "or" relationship. The terms "first," "second," "third," etc., used in this application are merely to distinguish similar objects and do not represent a specific order of objects.

[0045] The method embodiment provided in this example can be executed by the intelligent range hood 100. Figure 1 This is a structural block diagram of the intelligent range hood 100 in this embodiment, as shown below. Figure 1 As shown, the intelligent range hood 100 includes a controller 101, an infrared sensor 102, a memory 103, a fan drive module 104, a light module 105, a switch module 106, and a communication module 107. The controller 101 can be a microprocessor (MCU) or a field-programmable gate array (FPGA) device, etc. 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 smart range hood 100 described above. For example, the smart range hood 100 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 are illustrated.

[0046] Infrared sensor 102 can be installed at the bottom of the smoke collection hood or the bottom of the smoke baffle of the smart range hood 100, usually facing the center of the cooking appliance, to perform infrared thermal imaging of the target area above the cooking appliance to obtain the real-time temperature matrix corresponding to the target area. Specifically, for each cooking appliance, infrared sensor 102 has sufficient pixel coverage, such as using a 16×16 pixel array; the field of view (FOV) of infrared sensor 102 at least covers the placement area of ​​the cooking appliance (including single-burner area, double-burner area, etc.), for example, a FOV of 110° to cover the double-burner area, and the installation position is about 30~60 cm away from the cooking appliance; the wavelength range of infrared sensor 102 matches the wavelength characteristics of the thermal radiation signal emitted by the cooking appliance (e.g., 8~14). The temperature resolution of the infrared sensor 102 meets the requirements for detecting minute changes in the thermal field (e.g., 0.1℃).

[0047] The memory 103 is used to store computer programs, such as the computer program corresponding to the oil temperature state assessment method in this embodiment. The controller 101 executes various functional applications and data processing by running the computer program stored in the memory 103, thereby realizing the above-described method. The memory 103 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.

[0048] The fan drive module 104 receives control commands from the controller 101 and drives the fan assembly to operate at corresponding speeds, achieving smoke extraction functions at different levels. The lighting module 105 provides illumination for the cooking area, typically using LED light sources. This module receives control signals from the controller 101 and can turn the lights on and off, as well as adjust their brightness to suit different ambient light intensities and cooking needs. The switch module 106, as the core component for human-machine interaction, receives manual operation commands from the user (such as power on / off, speed switching, and lighting control) and converts these commands into electrical signals, transmitting them to the controller 101.

[0049] The communication module 107 is used to realize information interaction between the smart range hood 100 and external devices or networks, and supports intelligent functions such as remote control and data uploading. It can support one or more communication protocols such as Wi-Fi, Bluetooth, and ZigBee.

[0050] This embodiment provides a method for assessing oil temperature. Figure 2 This is a flowchart of the oil temperature condition assessment method in this embodiment, as shown below. Figure 2 As shown, the process includes the following steps:

[0051] Step S210: Perform infrared thermal imaging on the target area above the oil surface inside the cooking appliance to obtain the real-time temperature matrix corresponding to the target area; the real-time temperature matrix includes multiple temperature values, each temperature value corresponding to a corresponding position in the target area;

[0052] Step S220: Based on the real-time temperature matrix, determine the corresponding temperature field information entropy and the time change rate of the temperature field information entropy.

[0053] Step S230: Determine the characteristic oil temperature inside the cooking appliance based on the real-time temperature matrix;

[0054] Step S240: Determine the oil temperature level in the cooking appliance based on the time change rate of the characteristic oil temperature and the information entropy of the temperature field.

[0055] In this embodiment, the temperature distribution of a target area above the cooking appliance is monitored in real time. The target area is the steam plume formed above the cooking appliance. Specifically, an infrared sensor or infrared camera with a preset pixel array is used to collect signals from the target area above the cooking appliance, obtaining the output voltage corresponding to each pixel position in the preset pixel array. Based on a preset calibration coefficient, the output voltage corresponding to each pixel position is linearized and calibrated to generate a corresponding real-time temperature matrix.

[0056] The system automatically acquires signals at preset time intervals (e.g., 0.5 seconds), outputting a real-time temperature matrix corresponding to the pixel resolution for each acquisition to continuously and dynamically reflect the temperature changes in the target area. This real-time temperature matrix includes multiple temperature values, each corresponding to a specific location within the target area.

[0057] Entropy is calculated for each temperature value in the real-time temperature matrix to obtain the temperature field entropy H at the current moment. The temperature field entropy reflects the uniformity (i.e., irregularity) of the thermal field in the target area. The higher the value of the temperature field entropy, the more uneven the temperature distribution in the target area.

[0058] Furthermore, based on the temperature values ​​in the real-time temperature matrix, a characteristic oil temperature is determined to characterize the oil temperature level inside the cooking appliance. This characteristic oil temperature can be determined in various ways. For example, the temperature values ​​in the real-time temperature matrix can be sorted to determine the maximum temperature value, which can then be used as the characteristic oil temperature inside the cooking appliance; or, the median of all temperature values ​​in the real-time temperature matrix can be selected as the characteristic oil temperature to effectively filter out extreme values ​​caused by local water droplet splashes.

[0059] Subsequently, the time-varying rate of change of the temperature field entropy, dH / dt, is calculated. This time-varying rate reflects the dynamic change rate of the thermal field distribution. Based on the characteristic oil temperature and the time-varying rate of change of the temperature field entropy, and according to preset judgment rules, the current oil temperature level in the cooking appliance is determined. The judgment rules define the characteristic oil temperature threshold and entropy change rate conditions corresponding to different oil temperature levels.

[0060] For example, the oil temperature level can be determined by the following logic: if the characteristic oil temperature remains above 180℃ for a preset period of time, the oil temperature level in the current cooking appliance is determined to be Level 1; if the characteristic oil temperature is above 200℃ and the time change rate of the temperature field information entropy is above 0.5 / s, the oil temperature level in the current cooking appliance is determined to be Level 2, which is a dangerous level; if the characteristic oil temperature is above 220℃, the oil temperature level in the current cooking appliance is determined to be Level 3. It should be understood that the specific values ​​of the above temperature threshold and change rate threshold are only examples, and can be calibrated and adjusted according to different oils, cookware, or cooking needs in actual applications.

[0061] Precise control of oil temperature is crucial for cooking results and dietary health. However, in actual cooking, there is a lack of effective means to assess oil temperature. Users cannot accurately perceive and judge the oil temperature and usually can only rely on experience to roughly estimate the oil temperature by observing the state of the oil surface and the amount of smoke produced, which easily leads to the oil temperature being too high.

[0062] Compared to existing technologies, this application uses infrared thermal imaging to obtain a real-time temperature matrix for a target area above the oil surface in a cooking appliance. The real-time temperature matrix includes multiple temperature values, each corresponding to a specific location within the target area. Based on the real-time temperature matrix, the corresponding temperature field entropy and its time-varying rate of change are determined. The characteristic oil temperature within the cooking appliance is then determined based on the real-time temperature matrix. Finally, the oil temperature level within the cooking appliance is determined based on the characteristic oil temperature and the time-varying rate of change of the temperature field entropy. By acquiring a real-time temperature matrix of the oil surface area through infrared thermal imaging and simultaneously extracting the characteristic oil temperature, temperature field entropy, and their time-varying rate from this matrix, a multi-parameter fusion oil temperature state assessment model is constructed. This achieves accurate grading of the oil temperature state, solving the problem of inaccurate oil temperature assessment during cooking. Furthermore, the non-contact assessment method enhances the convenience and safety of detection and better aligns with the needs of healthy cooking.

[0063] In some of these embodiments, such as Figure 3 As shown, step S210, which involves performing infrared thermal imaging on the target area above the oil surface inside the cooking appliance to obtain the real-time temperature matrix corresponding to the target area, includes the following steps:

[0064] Step S211: By using an infrared sensor with a preset pixel array, the target area above the oil surface in the cooking appliance is sampled to obtain the output voltage corresponding to each pixel position in the preset pixel array.

[0065] Step S212: Based on preset calibration coefficients, the output voltage corresponding to each pixel position is linearized and calibrated to generate the corresponding real-time temperature matrix.

[0066] In this embodiment, an infrared sensor is installed at the bottom of the smoke collection hood or the bottom of the smoke baffle of the smart range hood, directly facing the center of the cooking appliance. This allows the infrared sensor to monitor the temperature distribution in a target area above the cooking appliance in real time. The target area is the plume of steam formed by boiling inside the cooking appliance.

[0067] Specifically, an infrared sensor with a preset pixel array is used to collect signals from the target area above the cooking appliance, obtaining the output voltage corresponding to each pixel position in the preset pixel array. Based on preset calibration coefficients, the output voltage corresponding to each pixel position is linearized and calibrated to generate a real-time temperature matrix. The specific expression for linearization calibration is as follows:

[0068] (1)

[0069] In equation (1), represents the temperature value in the i-th row and j-th column of the real-time temperature matrix, in °C; k and b are preset calibration coefficients. This represents the output voltage corresponding to the pixel position.

[0070] For example, when the infrared sensor uses a 16×16 pixel array, the corresponding real-time temperature matrix is ​​a 16×16 temperature matrix, the specific expression of which is as follows:

[0071] (2)

[0072] In equation (2), This is a real-time temperature matrix; This represents the temperature value in the i-th row and j-th column of the real-time temperature matrix, in °C.

[0073] This embodiment utilizes an infrared sensor to achieve real-time measurement of the temperature field in the cooking area, providing a data foundation for subsequent analysis and assessment of oil temperature conditions.

[0074] In some of these embodiments, such as Figure 4 As shown, step S220, which determines the corresponding temperature field information entropy based on the real-time temperature matrix, includes the following steps:

[0075] Step S221: Based on each temperature value in the real-time temperature matrix, determine the normalized temperature distribution probability corresponding to each temperature value;

[0076] Step S222: Calculate the normalized temperature distribution probability corresponding to each temperature value according to the Shannon entropy formula to obtain the temperature field information entropy.

[0077] Specifically, based on each temperature value in the real-time temperature matrix, the normalized temperature distribution probability corresponding to each temperature value is calculated, and the calculation formula is as follows:

[0078] (3)

[0079] In equation (3), This represents the normalized temperature distribution probability corresponding to each temperature value; This represents the temperature value in the i-th row and j-th column of the real-time temperature matrix. This represents the minimum temperature value in the real-time temperature matrix.

[0080] Furthermore, the normalized temperature distribution probability corresponding to each temperature value is calculated using the Shannon entropy formula to obtain the temperature field information entropy. Taking an infrared sensor with a 16×16 pixel array as an example, the formula for calculating the temperature field information entropy is as follows:

[0081] (4)

[0082] In equation (4), Represents the entropy of the temperature field; This represents the normalized temperature distribution probability corresponding to each temperature value.

[0083] This embodiment calculates the temperature field information entropy corresponding to the real-time temperature matrix to accurately reflect the uniformity of the thermal field above the oil surface.

[0084] In some of these embodiments, such as Figure 5 As shown, step S230, which determines the characteristic oil temperature within the cooking appliance based on the real-time temperature matrix, includes the following steps:

[0085] Step S231: Sort the temperature values ​​in the real-time temperature matrix to determine the maximum temperature value among them.

[0086] Step S232: The maximum temperature value is used as the characteristic oil temperature inside the cooking appliance.

[0087] Specifically, the real-time temperature matrix is ​​treated as a two-dimensional data set. By traversing and comparing or calling the built-in sorting function, the maximum temperature value among all temperature values ​​is determined to identify the peak temperature point reached by the oil surface at the current moment.

[0088] Furthermore, since the highest temperature point on the oil surface is often the primary area that causes risks such as oil fumes and fires, and is also the upper limit of the temperature at which a violent thermal reaction occurs when food comes into contact with it, the maximum temperature value is used as the characteristic oil temperature at the current moment to most directly reflect the thermal state of the oil surface.

[0089] This embodiment efficiently and stably extracts temperature feature values ​​with safety indication significance from the real-time temperature matrix that reflects the overall heat distribution, ensuring that the obtained characteristic oil temperature always represents the real-time upper limit of the oil surface temperature, thus providing a reliable and intuitive core parameter for subsequent oil temperature level determination.

[0090] In some of these embodiments, such as Figure 6 As shown, step S240, which determines the oil temperature level within the cooking appliance based on the time change rate of characteristic oil temperature and temperature field information entropy, includes the following steps:

[0091] Step S241: When the characteristic oil temperature is detected to be greater than the first preset threshold and the time change rate of the temperature field information entropy is greater than the preset change rate threshold, the oil temperature level in the cooking appliance is determined to be dangerous.

[0092] In this embodiment, a dual criterion of characteristic oil temperature and the rate of change of temperature field entropy is established to identify dangerous oil surface conditions. Specifically, the characteristic oil temperature is compared with a first preset threshold, and the time change rate of temperature field entropy is compared with a preset rate of change threshold. When the characteristic oil temperature is detected to be greater than the first preset threshold, and the time change rate of temperature field entropy is greater than the preset rate of change threshold, the oil temperature level inside the cooking appliance is determined to be dangerous. At this time, an oil temperature danger warning can be triggered, such as controlling the indicator light to flash red rapidly to issue an alarm, and simultaneously activating corresponding voice prompts or buzzer prompts.

[0093] Understandably, if the characteristic oil temperature exceeds a first preset threshold, it indicates that the local or overall temperature of the oil surface has risen to a critical range that may trigger oil fumes or thermal runaway. Furthermore, if the time change rate of the temperature field information entropy exceeds a preset change rate threshold, it reflects that the oil surface temperature distribution is undergoing rapid, non-uniform, and drastic changes. When both conditions are met simultaneously, a clear danger warning condition is established.

[0094] This embodiment, by coupling characteristic oil temperature with dynamic changes in the temperature field, can not only identify states that have reached dangerous temperature thresholds, but also sensitively capture transient processes of instability in the thermal field of the oil surface, so as to provide early warning before a large amount of oil fumes are generated, oil surface splashes, or the risk of fire increases significantly.

[0095] In some embodiments, the above-described oil temperature condition assessment method further includes the following steps:

[0096] When the detected characteristic oil temperature is greater than the second preset threshold, the firepower of the stove used by the cooking appliance is reduced to the first preset level and the fan speed of the smart range hood used by the cooking appliance is dynamically increased; the second preset threshold is greater than the first preset threshold.

[0097] Specifically, when the characteristic oil temperature exceeds the second preset threshold, it indicates that the oil temperature has entered a high-risk zone requiring immediate intervention, at which point multi-dimensional control is implemented. On the one hand, the firepower of the stove used for cooking is reduced to the first preset level, such as reducing the stove firepower by 30%, aiming to quickly suppress the continuous rise in oil temperature from the heat source and reduce the risk of thermal runaway. On the other hand, the fan speed of the intelligent range hood is dynamically increased, such as adjusting it to the maximum fan speed, to enhance the extraction efficiency of oil fumes and heat and alleviate the accumulation of local high temperatures.

[0098] The target setting for reducing firepower (i.e., the first preset setting) is pre-set, enabling rapid and stable power attenuation without sudden flameout. Furthermore, the fan speed can be adaptively adjusted based on the extent to which the real-time oil temperature exceeds the threshold or by considering the changing trend of temperature field entropy, thereby achieving a precise match between exhaust intensity and risk level.

[0099] This embodiment, by setting a high-level temperature threshold and supporting cross-device collaborative control, ensures that after a high-risk state is detected, the system can complete the entire process from risk identification to device response in a very short time. This significantly reduces the possibility of excessive oil fume generation, continuous rise in oil temperature, and even fire, greatly improving the safety level of the cooking process and helping to solve the health risks of high-temperature frying.

[0100] In some embodiments, the above-described oil temperature condition assessment method further includes the following steps:

[0101] When the characteristic oil temperature is detected to be continuously greater than the third preset threshold and less than the first preset threshold within a preset time period, the firepower of the stove used by the cooking appliance is controlled to be reduced to the second preset level.

[0102] Specifically, the third preset threshold and the first preset threshold together define the working range below the danger threshold but significantly above the ideal cooking temperature. When the characteristic oil temperature is detected to be continuously greater than the third preset threshold but less than the first preset threshold within a preset time period, it is determined that the oil temperature shows a steady-state high trend, and an oil temperature warning is triggered, such as controlling the indicator light to flash yellow slowly as an alarm.

[0103] Accordingly, when the aforementioned continuous judgment conditions are met, the system generates and issues a control command to the stove, adjusting the stove's firepower output to the second preset level. The power level of the second preset level is lower than the current operating level but higher than the first preset level set to address high risks. This adjustment employs a steady-state power reduction method, aiming to gently suppress the rising inertia of oil temperature without interrupting cooking with a sudden power drop.

[0104] This embodiment allows for preventative fire control adjustments to be made in the early stages when the oil temperature is consistently high but has not yet reached a dangerous level, significantly reducing the probability of triggering higher-level alarms or mandatory interventions.

[0105] The present embodiment will be described and explained below through specific examples.

[0106] The system monitors the temperature distribution in a target area above the cooking appliance, specifically the steam plume formed above the appliance. Specifically, an infrared sensor with a preset pixel array collects signals from the target area, obtaining the output voltage corresponding to each pixel position. Based on a preset calibration coefficient, the output voltage at each pixel position is linearized and calibrated to generate a real-time temperature matrix. This matrix includes multiple temperature values, each corresponding to a specific location within the target area.

[0107] Furthermore, entropy is calculated for each temperature value in the real-time temperature matrix to obtain the temperature field entropy at the current moment. The temperature field entropy reflects the uniformity (i.e., irregularity) of the thermal field in the target area. The higher the value of the temperature field entropy, the more uneven the temperature distribution in the target area.

[0108] Subsequently, the temperature values ​​in the real-time temperature matrix are sorted to determine the maximum temperature value, which is then used as the characteristic oil temperature within the cooking appliance. The time change rate of the temperature field information entropy is calculated, and based on the characteristic oil temperature and the time change rate of the temperature field information entropy, the current oil temperature level within the cooking appliance is determined.

[0109] Specifically, if the characteristic oil temperature remains above 180℃ for 60 seconds, the current oil temperature level in the cooking appliance is determined to be Level 1, and the control indicator light will flash yellow slowly as an alarm. If the characteristic oil temperature is above 200℃ and the time change rate of the temperature field information entropy is greater than 0.5 / s, the current oil temperature level in the cooking appliance is determined to be Level 2, and the control indicator light will flash red quickly as an alarm, while simultaneously activating a voice prompt indicating oil temperature danger. If the characteristic oil temperature is above 220℃, the current oil temperature level in the cooking appliance is determined to be Level 3, the stove's firepower will be reduced by 30%, and the smart range hood will be adjusted to its maximum fan speed.

[0110] It should be noted that the steps shown in the above process or in the flowchart of the accompanying figures can be executed in a computer system such as a set of computer-executable instructions, and 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.

[0111] This embodiment also provides a computer device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0112] Optionally, the computer device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0113] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0114] S1, perform infrared thermal imaging on the target area above the oil surface inside the cooking appliance to obtain the real-time temperature matrix corresponding to the target area; the real-time temperature matrix includes multiple temperature values, each temperature value corresponding to a corresponding position in the target area;

[0115] S2, based on the real-time temperature matrix, determines the corresponding temperature field information entropy and the time change rate of the temperature field information entropy;

[0116] S3, based on the real-time temperature matrix, determines the characteristic oil temperature inside the cooking appliance;

[0117] S4. Based on the time change rate of characteristic oil temperature and temperature field information entropy, determine the oil temperature level in the cooking appliance.

[0118] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated in this embodiment.

[0119] Furthermore, in conjunction with the oil temperature status assessment method provided in the above embodiments, this embodiment can also provide a storage medium for implementation. This storage medium stores a computer program; when executed by a processor, the computer program implements any of the oil temperature status assessment methods described in the above embodiments.

[0120] It should be understood that the specific embodiments described herein are merely illustrative of the application and not intended to limit it. All other embodiments derived by those skilled in the art based on the embodiments provided in this application without inventive effort are within the scope of protection of this application.

[0121] Obviously, the accompanying drawings are merely some examples or embodiments of this application. Those skilled in the art can apply this application to other similar situations based on these drawings without any creative effort. Furthermore, it is understood that although the work done in this development process may be complex and lengthy, for those skilled in the art, certain design, manufacturing, or production modifications made based on the technical content disclosed in this application are merely conventional technical means and should not be considered as insufficient disclosure of this application.

[0122] The term "embodiment" in this application refers to a specific feature, structure, or characteristic described in connection with an embodiment that may be included in at least one embodiment of this application. The appearance of this phrase in various places in the specification does not necessarily imply the same embodiment, nor does it imply that it is mutually exclusive with or independent of other embodiments. It will be clearly or implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0123] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of patent protection. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the appended claims.

Claims

1. A method for assessing oil temperature status, characterized in that, include: Infrared thermal imaging is performed on the target area above the oil surface inside the cooking appliance to obtain the real-time temperature matrix corresponding to the target area. The real-time temperature matrix includes multiple temperature values, each of which corresponds to a specific location in the target area; Based on the real-time temperature matrix, the corresponding temperature field information entropy and the time change rate of the temperature field information entropy are determined. Based on the real-time temperature matrix, the characteristic oil temperature inside the cooking appliance is determined; The oil temperature level within the cooking appliance is determined based on the characteristic oil temperature and the time change rate of the temperature field information entropy.

2. The oil temperature condition assessment method according to claim 1, characterized in that, The step of performing infrared thermal imaging on the target area above the oil surface inside the cooking appliance to obtain the real-time temperature matrix corresponding to the target area includes: By using an infrared sensor with a preset pixel array, the target area above the oil surface inside the cooking appliance is sampled to obtain the output voltage corresponding to each pixel position in the preset pixel array; Based on preset calibration coefficients, the output voltage corresponding to each pixel position is linearized and calibrated to generate the corresponding real-time temperature matrix.

3. The oil temperature condition assessment method according to claim 1, characterized in that, The step of determining the corresponding temperature field information entropy based on the real-time temperature matrix includes: Based on each temperature value in the real-time temperature matrix, determine the normalized temperature distribution probability corresponding to each temperature value; According to the Shannon entropy formula, the normalized temperature distribution probability corresponding to each temperature value is calculated to obtain the temperature field information entropy.

4. The oil temperature condition assessment method according to claim 1, characterized in that, Determining the characteristic oil temperature within the cooking appliance based on the real-time temperature matrix includes: The temperature values ​​in the real-time temperature matrix are sorted to determine the maximum temperature value among them. The maximum temperature value is used as the characteristic oil temperature within the cooking appliance.

5. The oil temperature condition assessment method according to claim 1, characterized in that, Determining the oil temperature level within the cooking appliance based on the characteristic oil temperature and the time change rate of the temperature field information entropy includes: When the characteristic oil temperature is detected to be greater than a first preset threshold, and the time change rate of the temperature field information entropy is greater than a preset change rate threshold, the oil temperature level in the cooking appliance is determined to be a dangerous level.

6. The oil temperature condition assessment method according to claim 5, characterized in that, The method further includes: When the characteristic oil temperature is detected to be greater than the second preset threshold, the stove power of the cooking appliance is controlled to be reduced to the first preset level, and the fan speed of the smart range hood used by the cooking appliance is dynamically increased; the second preset threshold is greater than the first preset threshold.

7. The oil temperature condition assessment method according to claim 5, characterized in that, The method further includes: When the characteristic oil temperature is detected to be continuously greater than a third preset threshold and less than the first preset threshold within a preset time period, the heat of the stove used by the cooking appliance is controlled to be reduced to a second preset level.

8. A smart range hood, characterized in that, The intelligent range hood includes an infrared sensor and a controller; The infrared sensor is used to perform infrared thermal imaging on a target area above the oil surface inside the cooking appliance to obtain a real-time temperature matrix corresponding to the target area; the real-time temperature matrix includes multiple temperature values, each of which corresponds to a corresponding position in the target area; The controller is used to determine the corresponding temperature field information entropy and the time change rate of the temperature field information entropy based on the real-time temperature matrix. The controller is also used to determine the characteristic oil temperature inside the cooking appliance based on the real-time temperature matrix; The controller is also used to determine the oil temperature level in the cooking appliance based on the characteristic oil temperature and the time change rate of the temperature field information entropy.

9. A computer device, comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to run the computer program to perform the steps of the oil temperature condition assessment method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the oil temperature condition assessment method according to any one of claims 1 to 7.

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