A pot recognition method and device

Abstract

The present disclosure relates to a pot recognition method and device, and relates to a smart electric appliance, including: collecting a feature of a first target pot when a pot temperature corresponding to the first target pot is less than a preset temperature to obtain first cold-state feature data corresponding to the first target pot; performing a heating treatment on the first target pot and collecting a feature of the first target pot to obtain first hot-state feature data corresponding to the first target pot; extracting a feature of the first target pot based on the first cold-state feature data and the first hot-state feature data to obtain first pot feature data corresponding to the first target pot; and identifying target pot material information corresponding to the first target pot from a plurality of different preset pot material information based on the first pot feature data. The present disclosure can improve the accuracy of pot material identification of the first target pot.

Description

Technical Field

[0001] This disclosure relates to the field of smart electrical appliance technology, and in particular to a cookware identification method and device. Background Technology

[0002] Currently, in the field of smart kitchen appliances, especially in cooktops such as induction cookers and ceramic cooktops, the identification of cookware materials mainly relies on a single physical quantity threshold judgment method. This involves placing the cookware in the system and detecting changes in the resonant frequency of the coil or the magnitude of the load current, setting a fixed threshold range to determine whether the cookware is made of ferromagnetic material or stainless steel. However, this method has coarse accuracy and cannot distinguish between materials of the same material family. Specifically, it can only roughly distinguish between "with / without a pot" or "iron / non-iron," failing to accurately differentiate between cookware that are ferromagnetic but have significantly different thermophysical properties (such as thick-bottomed cast iron pots and thin-walled enamel pots). This leads to problems during actual heating, such as thin pots overheating and burning, or thick pots heating too slowly due to parameter mismatch. Therefore, the above method suffers from poor accuracy in identifying cookware materials. Summary of the Invention

[0003] In view of the above-mentioned technical problems, this disclosure proposes a cookware identification method and device.

[0004] According to one aspect of the embodiments of this disclosure, a cookware identification method is provided, the method comprising: When the temperature of the cookware corresponding to the first target cookware is lower than the preset temperature, feature acquisition is performed on the first target cookware to obtain the first cold-state feature data corresponding to the first target cookware. The first target cookware is heated and its features are collected to obtain the first thermal feature data corresponding to the first target cookware. Based on the first cold state feature data and the first hot state feature data, feature extraction is performed on the first target cookware to obtain the first cookware feature data corresponding to the first target cookware. Based on the first cookware feature data, the target cookware material information corresponding to the first target cookware is identified from a variety of different preset cookware material information.

[0005] Optionally, the first cold-state feature data includes a static temperature change curve and first inductance data, and the first hot-state feature data includes a heating temperature change curve, a cooling temperature change curve, and second inductance data; the step of extracting features from the first target cookware based on the first cold-state feature data and the first hot-state feature data to obtain the first cookware feature data corresponding to the first target cookware includes: Based on the static temperature change curve, the cold equilibrium rate data is determined; the cold equilibrium rate data characterizes the rate at which the first target cookware reaches thermal equilibrium under no heating conditions after being placed. Feature extraction is performed on the first inductance data to obtain cold-state inductance feature data; the cold-state inductance feature data characterizes the static electromagnetic properties of the material of the first target cookware under no-heating conditions; Based on the heating temperature change curve, the heating slope data is determined; the heating slope data characterizes the average slope of the linear rise range of the bottom temperature of the first target pot during the heating process. Based on the cooling temperature change curve, cooling decay rate data is determined; the cooling decay rate data characterizes the decay rate of the bottom temperature of the first target pot naturally decreasing after heating is stopped. Feature extraction is performed on the second inductance data to obtain thermal inductance feature data; the thermal inductance feature data characterizes the dynamic electromagnetic properties of the material of the first target cookware under heating conditions; The cold equilibrium rate data, the cold inductance characteristic data, the heating slope data, the cooling decay rate data, and the hot inductance characteristic data are used as the first cookware characteristic data.

[0006] Optionally, the method further includes: Obtain the first cookware identification information corresponding to the first target cookware and the first cooking parameter set corresponding to the first target cookware; The first cookware feature data, the first cooking parameter set, and the first cookware identification information are used as the target cookware configuration data corresponding to the first target cookware. The target cookware configuration data is stored in a preset memory.

[0007] Optionally, the method further includes: When the second target cookware is detected to be placed on the target stove, the features of the second target cookware are collected to obtain the second cold state feature data corresponding to the second target cookware. Based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, the second target cookware is identified to obtain the second cookware identification information corresponding to the second target cookware.

[0008] Optionally, the step of identifying the second target cookware based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, to obtain the second cookware identification information corresponding to the second target cookware, includes: The second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain the target matching result; When the target matching result indicates that there are multiple preset cookware feature data that match the second cold state feature data, the second target cookware is heated and its features are collected to obtain the second hot state feature data corresponding to the second target cookware. Based on the second hot state feature data and the second cold state feature data, feature extraction is performed on the second target cookware to obtain the second cookware feature data corresponding to the second target cookware. The second cookware feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain matched cookware feature data. The preset cookware identification information corresponding to the matched cookware feature data is used as the second cookware identification information.

[0009] Optionally, the method further includes: Based on the second cookware identification information, obtain the second cooking parameter set corresponding to the second target cookware; Upon receiving a cooking instruction for the second target cookware, the target cookware is controlled to perform the corresponding cooking operation based on the second cooking parameter set.

[0010] Optionally, the method further includes: If a modification instruction for a third cooking parameter set corresponding to a third target cookware is detected, the current cumulative modification frequency corresponding to the third target cookware is obtained; the third target cookware is any one of a plurality of preset cookwares; If the current cumulative modification frequency exceeds the preset modification frequency, a recalibration prompt message is generated; the recalibration prompt message is used to prompt the target object to update the third cookware feature data corresponding to the third target cookware.

[0011] Optionally, the method further includes: Upon detecting a modification instruction for the third cooking parameter set corresponding to the third target cookware, the third cooking parameter set corresponding to the third target cookware in the preset memory is updated to the modified cooking parameter set in the modification instruction.

[0012] Optionally, the method further includes: If a fourth target cookware is detected among multiple preset cookwares, the third cookware identification information corresponding to the fourth target cookware is retrieved from the preset memory; the fourth target cookware is a preset cookware among the multiple preset cookwares whose cumulative waiting time exceeds the preset waiting time. Based on the third cookware identification information, usage prompt information corresponding to the fourth target cookware is generated.

[0013] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the above-described cookware identification method.

[0014] According to another aspect of the present disclosure, a computer-readable storage medium is provided, which, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to perform the above-described cookware identification method.

[0015] According to another aspect of the present disclosure, a computer program product containing instructions is provided that, when run on a computer, causes the computer to perform the above-described cookware identification method.

[0016] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects: By collecting features from the first target cookware when its temperature is lower than a preset temperature, first cold-state feature data is obtained, enabling the acquisition of cold-state feature data for the first target cookware. Then, the first target cookware is heated, and features are collected again to obtain first hot-state feature data, enabling the acquisition of hot-state feature data for the first target cookware. Next, by combining the first cold-state and first hot-state feature data, features are extracted from the first target cookware, resulting in first cookware feature data, enabling accurate extraction of cookware features for the first target cookware. Finally, by combining the first cookware feature data, the target cookware material information is identified from various preset cookware material information, improving the accuracy of cookware material identification for the first target cookware.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0019] Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a cookware identification method according to an exemplary embodiment; Figure 3 This is a schematic diagram of the architecture of a target system according to an exemplary embodiment; Figure 4 This is a block diagram illustrating a cookware recognition device according to an exemplary embodiment; Figure 5 This is a block diagram illustrating an electronic device for material identification of a first target cookware by means of first cold-state feature data and first hot-state feature data, according to an exemplary embodiment. Figure 6 This is a block diagram illustrating another electronic device for material identification of a first target cookware using first cold-state feature data and first hot-state feature data acquired according to an exemplary embodiment. Detailed Implementation

[0020] Various exemplary embodiments, features, and aspects of this application will now be described in detail with reference to the accompanying drawings. The same reference numerals in the drawings denote elements that have the same or similar functions. Although various aspects of the embodiments are shown in the drawings, they are not necessarily drawn to scale unless specifically indicated otherwise.

[0021] The term “exemplary” as used herein means “serving as an example, embodiment, or illustration.” Any embodiment illustrated herein as “exemplary” is not necessarily to be construed as superior to or better than other embodiments.

[0022] Furthermore, to better illustrate this application, numerous specific details are provided in the following detailed embodiments. Those skilled in the art should understand that this application can be implemented without certain specific details. In some instances, methods, means, components, and circuits well-known to those skilled in the art have not been described in detail in order to highlight the main points of this application.

[0023] Please see Figure 1 , Figure 1 This is a schematic diagram of an application environment provided in an embodiment of this application. The application environment may include at least a terminal device 101 and a server 102.

[0024] The terminal device 101 and the server 102 are connected via a wireless or wired network. The terminal device 101 is used to collect features of the first target cookware when the cookware temperature is lower than a preset temperature, obtaining first cold-state feature data corresponding to the first target cookware; to heat the first target cookware and collect features of the first target cookware, obtaining first hot-state feature data corresponding to the first target cookware; and to send the first cold-state feature data and the first hot-state feature data to the server. The server 102 is used to extract features of the first target cookware based on the first cold-state feature data and the first hot-state feature data, obtaining first cookware feature data corresponding to the first target cookware; and to identify the target cookware material information corresponding to the first target cookware from multiple preset cookware material information based on the first cookware feature data, sending the target cookware material information to the terminal device 101, so that the terminal device 101 controls the target stove to perform cooking operations based on the target cookware material information.

[0025] Optionally, the terminal device 101 may be a smartphone, tablet computer, laptop computer, desktop computer, smart speaker, smartwatch, smart voice interaction device, smart home appliance, or in-vehicle terminal, but is not limited to these.

[0026] Optionally, the server 102 is an independent physical server, or a server cluster or distributed system composed of multiple physical servers. Optionally, it is a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0027] Those skilled in the art will understand that the terminal device 101 and server 102 described above are merely illustrative examples. Other existing or future terminal devices or servers that are applicable to this application should also be included within the scope of protection of this application, and are hereby incorporated by reference. For example, the steps performed by the server 102 described above can also be implemented on the terminal device 101.

[0028] It should be noted that this specification provides method operation steps as shown in the embodiments or flowcharts, but based on conventional or non-inventive labor, more or fewer operation steps may be included. The order of steps listed in the embodiments is merely one possible execution order among many steps and does not represent the only execution order.

[0029] Specifically, Figure 2 This is a flowchart illustrating a cookware identification method according to an exemplary embodiment. Figure 2As shown, this cookware identification method can be used in electronic devices such as terminals or servers, and specifically includes the following steps: S201: When the temperature of the cookware corresponding to the first target cookware is lower than the preset temperature, feature acquisition is performed on the first target cookware to obtain the first cold-state feature data corresponding to the first target cookware.

[0030] In one specific embodiment, the first target cookware may refer to the cookware whose material needs to be identified.

[0031] In one specific embodiment, the temperature of the cookware corresponding to the first target cookware can be the temperature of any point on the first target cookware. Specifically, the temperature of the cookware corresponding to the first target cookware can be the temperature of the bottom of the first target cookware.

[0032] In one specific embodiment, a preset temperature can be used as a criterion for determining whether the first target cookware is currently in an unheated state. The preset temperature can be set according to actual application needs. Specifically, the preset temperature can be determined based on the current room temperature.

[0033] In one specific embodiment, if the temperature of the cookware corresponding to the first target cookware is lower than the preset temperature, it can be determined that the first target cookware is currently in an unheated state.

[0034] In one specific embodiment, the first cold-state characteristic data may refer to the characteristic data of the first target cookware collected when the first target cookware is under unheated conditions. Specifically, the first cold-state characteristic data may include a static temperature change curve or first inductance data.

[0035] In one specific embodiment, a bottom temperature sensor for the cookware can be installed on the target stove. This bottom temperature sensor can be used to collect the bottom temperature of the cookware placed on the target stove.

[0036] In one specific embodiment, when a first target pot is detected to be placed on the target stove, the current pot temperature can be collected by a pot bottom temperature sensor; when the current pot temperature is detected to be lower than a preset temperature, the pot temperature can be collected for a first preset time by the pot bottom temperature sensor, and a static temperature change curve can be generated accordingly. Specifically, the first preset time can be set according to actual application needs, and this disclosure does not limit it. Optionally, the value range of the first preset time can be 15s to 30s. For example, the first preset time can be 20s.

[0037] In one specific embodiment, an inductance acquisition module can be installed on the target cooktop. This inductance acquisition module can be used to collect the inductance data of the cookware placed on the target cooktop.

[0038] In one specific embodiment, when a first target cookware is detected to be placed on the target stove, the inductance data of the first target cookware can be collected by the inductance acquisition module as the first inductance data.

[0039] S203: Heat the first target cookware and collect its features to obtain the first thermal characteristic data corresponding to the first target cookware.

[0040] In a specific embodiment, the first thermal characteristic data can refer to the characteristic data of the first target cookware collected under heating conditions and after heating is stopped. Specifically, the first thermal characteristic data may include a heating temperature change curve, a cooling temperature change curve, or second inductance data. The heating temperature change curve can refer to the temperature change curve collected during the heating process of the first target cookware. The cooling temperature change curve can refer to the temperature change curve collected during the cooling process of the first target cookware after heating is stopped. The second inductance data can refer to the inductance data of the first target cookware during the heating process and the cooling process after heating is stopped.

[0041] In one specific embodiment, the target cookware can be heated by controlling the target stove to perform a heating operation. Specifically, the target stove can be controlled to heat the first target cookware at a preset power for a second preset time, and then the heating can be immediately cut off to enter a hot static monitoring state, during which the bottom temperature of the pot is collected for a third preset time (i.e., the cooling process). Correspondingly, the bottom temperature and inductance data of the pot during the heating process and the static cooling process can be collected by a pot bottom temperature sensor, which can obtain the heating temperature change curve, the cooling temperature change curve, and the second inductance data.

[0042] S205: Based on the first cold state feature data and the first hot state feature data, perform feature extraction on the first target cookware to obtain the first cookware feature data corresponding to the first target cookware.

[0043] In one specific embodiment, the first cookware characteristic data can be used to characterize the cookware characteristics of the first target cookware in both cold and hot states. Specifically, the first cookware characteristic data may include cold-state equilibrium rate data, cold-state inductance characteristic data, heating slope data, cooling decay rate data, and hot-state inductance characteristic data.

[0044] In a specific embodiment, when the first cold-state feature data includes a static temperature change curve and first inductance data, and the first hot-state feature data includes a heating temperature change curve, a cooling temperature change curve, and second inductance data, the above-mentioned feature extraction of the first target cookware based on the first cold-state feature data and the first hot-state feature data to obtain the first cookware feature data corresponding to the first target cookware may include: Based on the static temperature change curve, determine the cold equilibrium rate data; Feature extraction is performed on the first inductance data to obtain the cold-state inductance feature data; Determine the heating slope data based on the heating temperature change curve; Based on the cooling temperature change curve, determine the cooling decay rate data; Feature extraction is performed on the second inductance data to obtain the hot inductance feature data; The cold equilibrium rate data, cold inductance characteristic data, heating slope data, cooling decay rate data, and hot inductance characteristic data are used as the first cookware characteristic data.

[0045] In one specific embodiment, the cold equilibrium rate data can characterize the rate at which the first target cookware reaches thermal equilibrium under no-heating conditions after being placed. It is understood that the cold equilibrium rate data reflects the natural heat exchange capacity between the cookware and the environment—thick-bottomed cookware has a large heat capacity and a small cold equilibrium rate (slowly approaching equilibrium); thin-bottomed cookware has a small heat capacity and a large cold equilibrium rate (rapidly approaching equilibrium).

[0046] In a specific embodiment, the cold equilibrium rate data can be obtained using the following formula: α= (1 / n)*ln[(T n T_env) / (T0 T_env)] Where α represents the cold equilibrium rate data; n represents the cold acquisition time length; T n T_env is the bottom temperature of the first target cookware collected at the nth second; T_env is the ambient temperature (such as the temperature of the target cookware panel); T0 is the initial temperature (i.e., the temperature when the first target cookware was first placed).

[0047] In a specific embodiment, taking a first preset duration of 20 seconds as an example, the temperature sequence T1, T2, ..., T of the pot bottom is recorded within 20 seconds of the cold state. 20 The initial temperature T0 (the temperature when the cookware was first placed on the stove). Temperature changes follow an exponential tendency: T(t) = T_env + (T0) T_env)·e^( α·t) Where T_env is the ambient temperature (cooktop panel temperature). The cold equilibrium rate data α can be obtained by performing a least-squares fit on the 20-second temperature sequence. Specifically, a simplified calculation using the two-point method yields the following formula for calculating the cold equilibrium rate data: α= (1 / 20)·ln[(T 20 T_env) / (T0 T_env)] In one specific embodiment, cold-state inductance characteristic data can characterize the static electromagnetic properties of the material of the first target cookware under no-heating conditions. Specifically, the cold-state inductance characteristic data can include maximum cold-state inductance data, minimum cold-state inductance data, and average cold-state inductance data. It is understood that the cold-state inductance characteristic data can reflect the "static" electromagnetic properties of the cookware material under conditions without heating interference—metal cookware generates eddy currents due to conductivity and magnetism, causing a significant change in equivalent inductance, while non-metal cookware shows a smaller change.

[0048] In one specific embodiment, the first inductance data may include inductance data corresponding to each of multiple cold-state acquisition times. Specifically, the largest inductance data among the multiple cold-state acquisition times can be taken as the maximum cold-state inductance data; the smallest inductance data among the multiple cold-state acquisition times can be taken as the minimum cold-state inductance data; and the average cold-state inductance data can be obtained by averaging the multiple cold-state acquisition times.

[0049] In one specific embodiment, the heating slope data can characterize the average slope of the linear temperature rise range of the bottom of the first target cookware during the heating process. It can be understood that the heating slope data can reflect the thermodynamic "sensitivity" of the cookware—thin-bottomed cookware heats up quickly (large heating slope data), while thick-bottomed cookware heats up slowly (small heating slope data).

[0050] In one specific embodiment, a straight line can be fitted to the line segment between the initial heating temperature and the preset heating temperature in the heating temperature change curve, and the slope obtained from the fitting can be used as the heating slope data.

[0051] In a specific embodiment, the heating slope data can be obtained using the following formula: β=(T_end T_start) / Δt Where β is the heating slope data; T_end is the preset heating temperature; T_start is the heating start temperature (usually the temperature at the end of the cold state); Δt is the heating time from the heating start temperature to the preset heating temperature.

[0052] In one specific embodiment, the cooling decay rate data can characterize the rate at which the bottom temperature of the first target cookware naturally decreases after heating is stopped. It is understood that the cooling decay rate data can be a key parameter for distinguishing between thick-bottomed heat-storing cookware (high thermal inertia, slow cooling, and low cooling decay rate data) and thin-bottomed heat-dissipating cookware (low thermal inertia, fast cooling, and high cooling decay rate data).

[0053] In one specific embodiment, the cooling decay rate data can be obtained using the following formula: γ= (1 / m)·ln[(T m T_env) / (T_max T_env)] Where γ represents the cooling decay rate data; T m T_env represents the temperature of the first target cookware collected at the m-th second during the cooling process; T_env represents the ambient temperature; and T_max represents the overshoot peak temperature during the cooling process.

[0054] In a specific embodiment, taking a third preset duration of 30 seconds as an example, the cooling temperature change curve is a temperature sequence recorded within 30 seconds after the heating is cut off, and the cooling process also follows exponential decay: T(t) = T_env + (T_max) T_env)·e^( γ·t) By performing least-squares fitting on the 30-second temperature sequence to obtain γ, the simplified calculation formula can be obtained as follows: γ= (1 / 30)·ln[(T 30 T_env) / (T_max T_env)] In one specific embodiment, the thermal inductance characteristic data can characterize the dynamic electromagnetic properties of the material of the first target cookware under heating conditions. The thermal inductance characteristic data can include maximum thermal inductance data, minimum thermal inductance data, average thermal inductance data, and inductance fluctuation data. Among these, the inductance fluctuation data can characterize the fluctuations in inductance value caused by the expansion and deformation of the cookware bottom and the temperature drift of the electromagnetic properties during heating. It can be understood that the inductance fluctuation data can indirectly reflect the flatness of the cookware bottom and the stability of its contact with the probe.

[0055] In one specific embodiment, approximately 600 inductance values ​​can be collected at a sampling rate of 10Hz throughout the entire hot-state process (heating and cooling stages) to obtain the second inductance data. Further, the average hot-state inductance data can be obtained by averaging multiple inductance values ​​in the second inductance data; the largest inductance value in the second inductance data can be taken as the maximum hot-state inductance data; and the smallest inductance value in the second inductance data can be taken as the minimum hot-state inductance data.

[0056] In a specific embodiment, the inductance fluctuation data can be obtained using the following formula: σ_hot=[√(Σ(L_hot i L_hot_avg)² / k)] / L_hot_avg Where σ_hot represents the inductance fluctuation data; L_hot i is the i-th inductance data in the second inductance data; k is the number of inductance data contained in the second inductance data; L_hot_avg is the average hot inductance data.

[0057] In the above embodiments, based on the static temperature change curve, the cold equilibrium rate data is determined, and feature extraction is performed on the first inductance data to obtain cold inductance feature data. Based on the heating temperature change curve, the heating slope data is determined, and based on the cooling temperature change curve, the cooling decay rate data is determined. Feature extraction is performed on the second inductance data to obtain hot inductance feature data. The cold equilibrium rate data, cold inductance feature data, heating slope data, cooling decay rate data, and hot inductance feature data are used as the first cookware feature data. This allows for feature fusion of the cold and hot feature data of the first target cookware, enabling accurate extraction of the cookware features of the first target cookware. This achieves multi-dimensional characterization of the first target cookware's features, thereby effectively improving the accuracy of material identification of the first target cookware.

[0058] S207: Based on the first cookware feature data, identify the target cookware material information corresponding to the first target cookware from a variety of different preset cookware material information.

[0059] In one specific embodiment, multiple preset cookware material information can correspond to different cookware materials. Specifically, the cookware materials corresponding to the multiple preset cookware material information can include at least two of the following materials: stainless steel, aluminum alloy, copper, iron, enamel cast iron, or titanium.

[0060] In one specific embodiment, the target cookware material information can characterize the cookware material of the first target cookware.

[0061] In one specific embodiment, the above method may further include: Obtain the first cookware identification information and the first cooking parameter set corresponding to the first target cookware; The first cookware feature data, the first cooking parameter set, and the first cookware identification information are used as the target cookware configuration data corresponding to the first target cookware; Store the target cookware configuration data to a preset memory.

[0062] In one specific embodiment, the first cookware identification information can be used as a unique identifier for the first target cookware. Specifically, the first cookware identification information may include the cookware name, for example, the first cookware identification information may be "thick-bottomed iron pot".

[0063] In one specific embodiment, the first cooking parameter set may refer to the set of parameters required for the cooking process using the first target cookware. For example, the first cooking parameter set may include maximum power limits, anti-dry-burning temperature thresholds, or recommended heating profiles, etc.

[0064] In one specific embodiment, the target object can perform an identification input operation through the object terminal so that the object terminal can obtain the first pot identification information corresponding to the first target pot.

[0065] In one specific embodiment, the target object can perform a cooking parameter input operation through the object terminal so that the object terminal can obtain the first cooking parameter set corresponding to the first target cookware.

[0066] In one specific embodiment, the first cookware feature data, the first cooking parameter set, and the first cookware identification information can be bound together and stored in a preset memory as the target cookware configuration data corresponding to the first target cookware.

[0067] In the above embodiments, by obtaining the first cookware identification information and the first cooking parameter set corresponding to the first target cookware, the first cookware feature data, the first cooking parameter set, and the first cookware identification information are used as the target cookware configuration data corresponding to the first target cookware. The target cookware configuration data is stored in a preset memory, which can realize the rapid storage of the first cookware feature data of the first target cookware. Thus, the first target cookware can be accurately identified through the first cookware feature data.

[0068] In one specific embodiment, the above method may further include: When the second target cookware is detected to be placed on the target stove, the features of the second target cookware are collected to obtain the second cold state feature data corresponding to the second target cookware. Based on the second cold state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, the second target cookware is identified to obtain the second cookware identification information corresponding to the second target cookware.

[0069] In one specific embodiment, the second target cookware can refer to the cookware that needs to be identified from a plurality of preset cookware for the target object. Specifically, the second target cookware can be one of the plurality of preset cookware. The plurality of preset cookware can refer to cookware that the target object can choose to use.

[0070] In one specific embodiment, the second cold-state feature data may refer to the feature data of the second target cookware collected when the second target cookware is under unheated conditions. The second cold-state feature data may include a static temperature change curve or third inductance data. Specifically, the feature acquisition process of the second cold-state feature data can refer to the feature acquisition process of the first cold-state feature data of the first target cookware described above, and will not be repeated in this disclosure.

[0071] In one specific embodiment, the second cold-state feature data and the preset cookware feature data corresponding to each preset cookware in the preset memory are matched to obtain a target matching result. The target matching result can be used to indicate whether there is preset cookware feature data among the preset cookware feature data corresponding to multiple preset cookwares that matches the second cold-state feature data.

[0072] In a specific embodiment, the cold balance rate data and cold inductance characteristic data in the second cold state feature data and the preset cookware feature data corresponding to any preset cookware can be matched to obtain the matching result corresponding to any preset cookware, and correspondingly, the target matching result can be obtained.

[0073] In one specific embodiment, feature similarity calculation can be performed on the cold-state equilibrium rate data and cold-state inductance feature data of the second cold-state feature data and the preset cookware feature data corresponding to any preset cookware to obtain feature similarity index data corresponding to the aforementioned preset cookware. If the feature similarity index data corresponding to any preset cookware is greater than the preset similarity index data, it can be determined that the second cold-state feature data corresponding to the second target cookware matches the preset cookware feature data corresponding to the aforementioned preset cookware. The feature similarity index data corresponding to any preset cookware can characterize the similarity between the cold-state equilibrium rate data and cold-state inductance feature data of the preset cookware feature data corresponding to the aforementioned preset cookware and the second cold-state feature data. Specifically, the preset similarity index data can be set according to actual application needs, and this disclosure does not limit it.

[0074] In a specific embodiment, when the target matching result indicates that there is a preset cookware feature data that matches the second cold state feature data, the preset cookware can be used as the matching cookware, and the preset cookware feature data corresponding to the matching cookware can be used as the matching cookware feature data; accordingly, the preset cookware identification information corresponding to the matching cookware feature data can be obtained from the preset memory as the second cookware identification information.

[0075] In the above embodiments, when the second target cookware is detected to be placed on the target stove, the features of the second target cookware are collected to obtain the second cold state feature data corresponding to the second target cookware. Based on the second cold state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, the second target cookware is identified to obtain the second cookware identification information corresponding to the second target cookware. This can realize the rapid identification of cookware in daily life and improve the efficiency of cookware identification.

[0076] In a specific embodiment, the above-mentioned process of identifying the second target cookware based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, to obtain the second cookware identification information corresponding to the second target cookware, may include: The second cold state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain the target matching result; If the target matching result indicates that there are multiple preset cookware feature data that match the second cold state feature data, the second target cookware is heated and its features are collected to obtain the second hot state feature data corresponding to the second target cookware. Based on the second hot state feature data and the second cold state feature data, feature extraction is performed on the second target cookware to obtain the second cookware feature data corresponding to the second target cookware. The second cookware feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain the matched cookware feature data. The preset cookware identification information corresponding to the matched cookware feature data is used as the second cookware identification information.

[0077] In a specific embodiment, the second thermal characteristic data may refer to the characteristic data of the second target cookware collected under heating conditions and after heating is stopped.

[0078] In a specific embodiment, the specific process of heating the second target cookware and acquiring the second thermal characteristic data can be referred to the aforementioned feature acquisition process of the first thermal characteristic data of the first target cookware, and will not be repeated here.

[0079] In a specific embodiment, when the target matching result indicates that there are multiple preset cookware feature data that match the second cold state feature data, that is, multiple preset cookwares will match the current second cold state feature data, the second cookware identification information of the second target cookware can be accurately identified from the multiple preset cookwares by heating and feature acquisition.

[0080] In one specific embodiment, the second cookware characteristic data can be used to characterize the cookware characteristics of the second target cookware in both cold and hot states. Specifically, the second cookware characteristic data may include cold-state equilibrium rate data, cold-state inductance characteristic data, heating slope data, cooling decay rate data, and hot-state inductance characteristic data.

[0081] In a specific embodiment, the feature extraction process for the second target cookware, which combines the second hot-state feature data and the second cold-state feature data, can refer to the feature extraction process for the first target cookware based on the first cold-state feature data and the first hot-state feature data described above, and will not be repeated here.

[0082] In one specific embodiment, the matched cookware feature data can refer to the preset cookware feature data that matches the second cookware feature data among the preset cookware feature data corresponding to each of the multiple preset cookwares. Specifically, the matched cookware feature data can be any one of the preset cookware feature data corresponding to each of the multiple preset cookwares.

[0083] In one specific embodiment, the matching process between the second cookware feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory can be performed by calculating the feature similarity between the second cookware feature data and the preset cookware feature data corresponding to each preset cookware in the preset memory, and determining the target matching result based on the feature similarity calculation result.

[0084] In the above embodiments, by matching the second cold-state feature data with the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, a target matching result is obtained. When the target matching result indicates that multiple preset cookware feature data match the second cold-state feature data, the second target cookware is heated, and features of the second target cookware are collected to obtain the second hot-state feature data corresponding to the second target cookware. Based on the second hot-state feature data and the second cold-state feature data, features of the second target cookware are extracted to obtain the second cookware feature data corresponding to the second target cookware. The second cookware feature data is then matched with the preset cookware feature data corresponding to multiple preset cookwares in the preset memory to obtain the matched cookware feature data. The preset cookware identification information corresponding to the matched cookware feature data is used as the second cookware identification information, which can achieve accurate identification of the second target cookware, thereby improving the accuracy of cooking operations and further enhancing the intelligence of smart kitchen appliances. Understandably, by using preset cookware feature data as the benchmark for cookware recognition, the system's ability to distinguish cookware of similar materials can be significantly improved. At the same time, it provides users with a seamless intelligent interactive experience with zero learning cost. That is, users only need to perform a learning operation once when using a new cookware for the first time (learning and storing it as preset cookware feature data). Different cookware can be bound to completely different sets of cooking parameters to achieve precise control of "one cookware, one strategy". Subsequent use is fully automated.

[0085] In one specific embodiment, the above method may further include: Based on the second cookware identification information, obtain the second cooking parameter set corresponding to the second target cookware; Upon receiving a cooking instruction for the second target cookware, the target cookware is controlled to perform the corresponding cooking operation based on the second cooking parameter set.

[0086] In one specific embodiment, the second cooking parameter set may refer to the cooking parameter set preset by the target object for the second target cookware.

[0087] In one specific embodiment, a preset cooking parameter set corresponding to the second cookware identification information can be obtained from a preset memory based on the second cookware identification information, and used as the second cooking parameter set.

[0088] In the above embodiments, when the second cookware identification information of the second target cookware is identified, precise cooking operations can be achieved for the second target cookware by using the obtained second cooking parameter set.

[0089] In one specific embodiment, the above method may further include: If a modification instruction for the third cooking parameter set corresponding to the third target cookware is detected, the current cumulative modification frequency corresponding to the third target cookware is obtained; If the current cumulative modification frequency exceeds the preset modification frequency, a recalibration prompt message will be generated.

[0090] In one specific embodiment, the third target cookware can be any one of a plurality of preset cookware. The third cooking parameter set corresponding to the third target cookware can refer to the preset cooking parameter set corresponding to the third target cookware stored in a preset memory.

[0091] In one specific embodiment, the modification instruction can be used to instruct modifications to a third set of cooking parameters. Specifically, the modification instruction may include modifying the cooking parameter set, or modification instruction information for the third set of cooking parameters. The modified cooking parameter set can refer to a modified set of cooking parameters. The modification instruction information can be used to indicate the direction and amount of modification to the third set of cooking parameters.

[0092] In a specific embodiment, the current cumulative modification frequency can refer to the cumulative number of times the cooking parameter set has been modified since the third target cookware began storing the preset cooking parameter set in the preset memory until the current time. Specifically, each time the preset cooking parameter set corresponding to the third target cookware is modified, the current cumulative modification frequency is recorded and updated accordingly. For example, after one modification, the current cumulative modification frequency is incremented by 1. Accordingly, the current cumulative modification frequency corresponding to the third target cookware can be stored in the preset memory; subsequently, the current cumulative modification frequency corresponding to the third target cookware can be retrieved from the preset memory.

[0093] In one specific embodiment, the recalibration prompt can be used to prompt the target object to update the third cookware feature data corresponding to the third target cookware.

[0094] In one specific embodiment, the preset modification frequency can be set according to actual application needs, and this disclosure does not limit it.

[0095] In one specific embodiment, if the current cumulative modification frequency exceeds the preset modification frequency, a recalibration prompt message can be sent to the terminal and displayed to prompt the target object to update the third cookware feature data corresponding to the third target cookware.

[0096] In one specific embodiment, the target object can trigger a feature update operation for a third target cookware by performing a feature update operation on the terminal corresponding to the target stove. This triggers the terminal to recalibrate the preset cookware feature data of the third target cookware. Specifically, the target object is prompted to place the third target cookware on the target stove. Upon detecting that the third target cookware is placed on the target stove, the third target cookware is designated as the first target cookware. Then, if the temperature of the cookware corresponding to the first target cookware is lower than a preset temperature, the target object performs feature acquisition on the first target cookware to obtain first cold-state feature data. Based on the first cold-state feature data and the first hot-state feature data, the target object performs feature extraction on the first target cookware to obtain cookware feature data corresponding to the first target cookware. The newly obtained first cookware feature data is then updated in the preset memory as the calibrated cookware feature data to achieve recalibration.

[0097] In the above embodiments, upon detecting a modification instruction for the third cooking parameter set corresponding to the third target cookware, the system obtains the current cumulative modification frequency for the third target cookware. If the current cumulative modification frequency exceeds a preset modification frequency, a recalibration prompt is generated. Through the target object's interaction with the modification of the third cooking parameter set, the system can effectively and promptly perceive changes in the cookware's state, thereby enabling timely updates to the third cookware's feature data. It is understood that if the target object frequently performs significant parameter corrections during a successfully matched cooking process, the system can indirectly perceive the drift in the cookware's physical characteristics caused by aging, carbon buildup, etc., and can prompt the user to consider recalibrating.

[0098] In one specific embodiment, the above method may further include: If a modification instruction for the third cooking parameter set corresponding to the third target cookware is detected, the third cooking parameter set corresponding to the third target cookware in the preset memory is updated to the modified cooking parameter set in the modification instruction.

[0099] In the above embodiments, by updating the third cooking parameter set corresponding to the third target cookware in the preset memory to the modified cooking parameter set in the modification instruction when a modification instruction is detected for the third cooking parameter set corresponding to the third target cookware, the corresponding cooking parameter set stored in the preset memory can be synchronously updated when the target object modifies the cooking parameter set. The user's manual correction behavior is recorded and accumulated, and the system becomes more and more in line with the user's habits the more it is used.

[0100] In one specific embodiment, the above method may further include: If a fourth target cookware is detected among multiple preset cookwares, the third cookware identification information corresponding to the fourth target cookware is retrieved from the preset memory; Based on the third cookware identification information, generate usage prompts for the fourth target cookware.

[0101] In one specific embodiment, the fourth target cookware can be one of a plurality of preset cookwares whose cumulative waiting time exceeds a preset waiting time. The cumulative waiting time refers to the time interval between the current moment of the fourth target cookware and its most recent successful match. Specifically, the fourth target cookware can be one or more of a plurality of preset cookwares. It is understood that when the cumulative waiting time corresponding to the fourth target cookware exceeds the preset waiting time, it can be determined that the feature data of the preset cookware corresponding to the fourth target cookware is in a state of not being matched for a long time. Furthermore, it can be determined that the fourth target cookware may have been unused for a long time, or that its state changes due to use, causing the original preset cookware feature data to need recalibration and updating.

[0102] In one specific embodiment, the preset matching time can be set according to the actual application needs, and this disclosure does not limit it.

[0103] In one specific embodiment, the cumulative matching time corresponding to each preset cookware can be determined; by comparing the cumulative matching time corresponding to each preset cookware with the preset matching time, the fourth target cookware can be determined.

[0104] In one specific embodiment, a prompt message can be used to alert the target object that the aforementioned fourth target cookware may have been unused for an extended period. The prompt message may also carry the aforementioned third cookware identification information.

[0105] In one specific embodiment, when displaying usage prompts for any preset cookware, the system can proactively remind the user whether to retain the data. The user can control the data via the terminal to choose to retain, delete, or relearn it, thereby achieving effective management of storage space. The forgetting reminder mechanism prevents abandoned cookware from occupying limited storage space for a long time, maintaining the timeliness and effectiveness of the feature database.

[0106] In the above embodiments, by detecting the presence of a fourth target cookware among multiple preset cookware, the system retrieves the third cookware identification information corresponding to the fourth target cookware from the preset memory, and generates usage prompt information corresponding to the fourth target cookware based on the third cookware identification information. This improves the automation and intelligence level of cookware lifecycle management, enhances human-computer interaction experience, and improves system usability. It is understood that users do not need to actively inform the system "I've changed my cookware"; the system automatically infers and reminds users based on long-term matching failures, avoiding cooking failures caused by forgetting to switch modes. By covering the entire process of cookware status tracking and adaptation services from first use, long-term service, aging drift to final replacement, the automation and intelligence level of cookware lifecycle management can be improved.

[0107] In the above embodiments, by collecting features from the first target cookware when its temperature is lower than a preset temperature, first cold-state feature data of the first target cookware can be obtained. Then, the first target cookware is heated, and features are collected again to obtain first hot-state feature data of the first target cookware. Next, the first cold-state and first hot-state feature data are combined to extract features from the first target cookware, resulting in first cookware feature data. This allows for accurate extraction of the cookware features of the first target cookware. Finally, by combining the first cookware feature data, the target cookware material information corresponding to the first target cookware can be identified from various preset cookware material information, improving the accuracy of cookware material identification for the first target cookware.

[0108] Figure 3 This is a schematic diagram of the architecture of a target system according to an exemplary embodiment. The target system can be used to implement the above-described cookware recognition method. Specifically, as... Figure 3 As shown, the target system may include a controller, a target cooktop, a pot bottom temperature sensor, and an inductive acquisition module. The controller can be used to implement the aforementioned cooktop identification method. The target cooktop can be used to place the cooktop and for heating. The pot bottom temperature sensor can be used to collect the bottom temperature of the cooktop placed on the target cooktop. The pot bottom temperature sensor can be installed on the target cooktop. The aforementioned inductive acquisition module can be used to collect the inductance data of the cooktop placed on the target cooktop. The inductive acquisition module can be installed on the target cooktop.

[0109] Figure 4 This is a block diagram illustrating a cookware recognition device according to an exemplary embodiment. Specifically, as shown... Figure 4 As shown, the device may include: The first feature acquisition module 410 is used to acquire features of the first target cookware when the temperature of the cookware corresponding to the first target cookware is lower than a preset temperature, and obtain the first cold state feature data corresponding to the first target cookware. The second feature acquisition module 420 is used to heat the first target cookware and acquire features of the first target cookware to obtain the first thermal feature data corresponding to the first target cookware. The first feature extraction module 430 is used to extract features from the first target cookware based on the first cold state feature data and the first hot state feature data to obtain the first cookware feature data corresponding to the first target cookware. The material recognition module 440 is used to identify the target cookware material information corresponding to the first target cookware from a variety of different preset cookware material information based on the first cookware feature data.

[0110] In one specific embodiment, the first cold-state feature data includes a static temperature change curve and first inductance data; the first hot-state feature data includes a heating temperature change curve, a cooling temperature change curve, and second inductance data; the first feature extraction module 430 includes: The equilibrium rate determination module is used to determine the cold equilibrium rate data based on the static temperature change curve; the cold equilibrium rate data characterizes the rate at which the first target cookware reaches thermal equilibrium under no heating conditions after being placed. The cold-state inductance feature determination module is used to extract features from the first inductance data to obtain cold-state inductance feature data; the cold-state inductance feature data characterizes the static electromagnetic properties of the material of the first target cookware under no-heating conditions; The heating slope determination module is used to determine the heating slope data based on the heating temperature change curve; the heating slope data represents the average slope of the linear rise range of the bottom temperature of the first target pot during the heating process. The decay rate determination module is used to determine the cooling decay rate data based on the cooling temperature change curve; the cooling decay rate data characterizes the decay rate of the bottom temperature of the first target pot naturally decreasing after heating is stopped. A hot-state inductance feature determination module is used to extract features from the second inductance data to obtain hot-state inductance feature data; the hot-state inductance feature data characterizes the dynamic electromagnetic properties of the material of the first target cookware under heating conditions; The cookware feature generation module is used to take the cold equilibrium rate data, the cold inductance feature data, the heating slope data, the cooling decay rate data, and the hot inductance feature data as the first cookware feature data.

[0111] In one specific embodiment, the device further includes: The information acquisition module is used to acquire the first cookware identification information corresponding to the first target cookware and the first cooking parameter set corresponding to the first target cookware; The cookware configuration generation module is used to take the first cookware feature data, the first cooking parameter set and the first cookware identification information as the target cookware configuration data corresponding to the first target cookware; The storage module is used to store the target cookware configuration data into a preset memory.

[0112] In one specific embodiment, the device further includes: The third feature acquisition module is used to acquire features of the second target cookware when the second target cookware is detected to be placed on the target stove, and to obtain the second cold-state feature data corresponding to the second target cookware. The cookware identification module is used to identify the second target cookware based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, and obtain the second cookware identification information corresponding to the second target cookware.

[0113] In one specific embodiment, the cookware identification module includes: The first matching processing module is used to match the second cold state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory to obtain the target matching result; The fourth feature acquisition module is used to heat the second target cookware and acquire features of the second target cookware when the target matching result indicates that there are multiple preset cookware feature data that match the second cold state feature data, thereby obtaining the second hot state feature data corresponding to the second target cookware. The second feature extraction module is used to extract features from the second target cookware based on the second hot-state feature data and the second cold-state feature data, so as to obtain the second cookware feature data corresponding to the second target cookware. The second matching processing module is used to match the second cookware feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory to obtain matched cookware feature data. The cookware identification module is used to use the preset cookware identification information corresponding to the matched cookware feature data as the second cookware identification information.

[0114] In one specific embodiment, the device further includes: The parameter set acquisition module is used to acquire the second cooking parameter set corresponding to the second target cookware based on the second cookware identification information; The execution module is used to control the target cooker to perform the corresponding cooking operation based on the second cooking parameter set when a cooking instruction for the second target cooker is received.

[0115] In one specific embodiment, the device further includes: The current frequency acquisition module is used to acquire the current cumulative modification frequency corresponding to the third target cookware when a modification instruction for the third cooking parameter set corresponding to the third target cookware is detected; the third target cookware is any one of a plurality of preset cookwares; The first prompt generation module is used to generate a recalibration prompt message when the current cumulative modification frequency exceeds the preset modification frequency; the recalibration prompt message is used to prompt the target object to update the third cookware feature data corresponding to the third target cookware.

[0116] In one specific embodiment, the device further includes: The parameter set update module is used to update the third cooking parameter set corresponding to the third target cookware in the preset memory to the modified cooking parameter set in the modification instruction when a modification instruction for the third cooking parameter set corresponding to the third target cookware is detected.

[0117] In one specific embodiment, the device further includes: The cookware identifier acquisition module is used to acquire the third cookware identifier information corresponding to the fourth target cookware from the preset memory when a fourth target cookware is detected among multiple preset cookwares; the fourth target cookware is a preset cookware among the multiple preset cookwares whose cumulative waiting time exceeds the preset waiting time. The second prompt generation module is used to generate usage prompt information corresponding to the fourth target cookware based on the third cookware identification information.

[0118] Regarding the apparatus in the above embodiments, the specific manner in which each module and unit performs its operations has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0119] Figure 5 This is a block diagram illustrating an electronic device for material identification of a first target cookware using first cold-state feature data and first hot-state feature data, according to an exemplary embodiment. The electronic device may be a server, and its internal structure diagram may be as follows: Figure 5As shown, the electronic device includes a processor, memory, and a network interface connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a cookware identification method.

[0120] Figure 6 This is a block diagram illustrating another electronic device for material identification of a first target cookware using first cold-state feature data and first hot-state feature data, according to an exemplary embodiment. The electronic device may be a terminal, and its internal structure diagram may be as follows: Figure 6 As shown, the electronic device includes a processor, memory, network interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface is used to communicate with external terminals via a network connection. When the computer program is executed by the processor, it implements a cookware recognition method. The display screen can be a liquid crystal display (LCD) or an e-ink display. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad mounted on the device's casing, or an external keyboard, touchpad, or mouse.

[0121] Those skilled in the art will understand that Figure 5 or Figure 6 The structure shown is merely a block diagram of a portion of the structure related to the present disclosure and does not constitute a limitation on the electronic device to which the present disclosure is applied. A specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0122] In an exemplary embodiment, an electronic device is also provided, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to execute the instructions to implement the cookware identification method as described in the embodiments of this disclosure.

[0123] In an exemplary embodiment, a computer-readable storage medium is also provided, wherein when the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to perform the cookware identification method of the present disclosure embodiments.

[0124] In an exemplary embodiment, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the cookware identification method of the present disclosure embodiments.

[0125] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0126] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0127] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for identifying cookware, characterized in that, The method includes: When the temperature of the cookware corresponding to the first target cookware is lower than the preset temperature, feature acquisition is performed on the first target cookware to obtain the first cold-state feature data corresponding to the first target cookware. The first target cookware is heated and its features are collected to obtain the first thermal feature data corresponding to the first target cookware. Based on the first cold state feature data and the first hot state feature data, feature extraction is performed on the first target cookware to obtain the first cookware feature data corresponding to the first target cookware. Based on the first cookware feature data, the target cookware material information corresponding to the first target cookware is identified from a variety of different preset cookware material information.

2. The method according to claim 1, characterized in that, The first cold-state feature data includes a static temperature change curve and first inductance data; the first hot-state feature data includes a heating temperature change curve, a cooling temperature change curve, and second inductance data; the step of extracting features from the first target cookware based on the first cold-state feature data and the first hot-state feature data to obtain the first cookware feature data corresponding to the first target cookware includes: Based on the static temperature change curve, the cold equilibrium rate data is determined; the cold equilibrium rate data characterizes the rate at which the first target cookware reaches thermal equilibrium under no heating conditions after being placed. Feature extraction is performed on the first inductance data to obtain cold-state inductance feature data; the cold-state inductance feature data characterizes the static electromagnetic properties of the material of the first target cookware under no-heating conditions; Based on the heating temperature change curve, the heating slope data is determined; the heating slope data characterizes the average slope of the linear rise range of the bottom temperature of the first target pot during the heating process. Based on the cooling temperature change curve, cooling decay rate data is determined; the cooling decay rate data characterizes the decay rate of the bottom temperature of the first target pot naturally decreasing after heating is stopped. Feature extraction is performed on the second inductance data to obtain thermal inductance feature data; the thermal inductance feature data characterizes the dynamic electromagnetic properties of the material of the first target cookware under heating conditions; The cold equilibrium rate data, the cold inductance characteristic data, the heating slope data, the cooling decay rate data, and the hot inductance characteristic data are used as the first cookware characteristic data.

3. The method according to claim 1, characterized in that, The method further includes: Obtain the first cookware identification information corresponding to the first target cookware and the first cooking parameter set corresponding to the first target cookware; The first cookware feature data, the first cooking parameter set, and the first cookware identification information are used as the target cookware configuration data corresponding to the first target cookware. The target cookware configuration data is stored in a preset memory.

4. The method according to claim 3, characterized in that, The method further includes: When the second target cookware is detected to be placed on the target stove, the features of the second target cookware are collected to obtain the second cold-state feature data corresponding to the second target cookware. Based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, the second target cookware is identified to obtain the second cookware identification information corresponding to the second target cookware.

5. The method according to claim 4, characterized in that, The step of identifying the second target cookware based on the second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory, and obtaining the second cookware identification information corresponding to the second target cookware, includes: The second cold-state feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain the target matching result; When the target matching result indicates that there are multiple preset cookware feature data that match the second cold state feature data, the second target cookware is heated and its features are collected to obtain the second hot state feature data corresponding to the second target cookware. Based on the second hot-state feature data and the second cold-state feature data, feature extraction is performed on the second target cookware to obtain the second cookware feature data corresponding to the second target cookware. The second cookware feature data and the preset cookware feature data corresponding to multiple preset cookwares in the preset memory are matched to obtain matched cookware feature data. The preset cookware identification information corresponding to the matched cookware feature data is used as the second cookware identification information.

6. The method according to claim 4 or 5, characterized in that, The method further includes: Based on the second cookware identification information, obtain the second cooking parameter set corresponding to the second target cookware; Upon receiving a cooking instruction for the second target cookware, the target cookware is controlled to perform the corresponding cooking operation based on the second cooking parameter set.

7. The method according to claim 3, characterized in that, The method further includes: If a modification instruction for a third cooking parameter set corresponding to a third target cookware is detected, the current cumulative modification frequency corresponding to the third target cookware is obtained; the third target cookware is any one of a plurality of preset cookwares; If the current cumulative modification frequency exceeds the preset modification frequency, a recalibration prompt message is generated; the recalibration prompt message is used to prompt the target object to update the third cookware feature data corresponding to the third target cookware.

8. The method according to claim 3, characterized in that, The method further includes: Upon detecting a modification instruction for the third cooking parameter set corresponding to the third target cookware, the third cooking parameter set corresponding to the third target cookware in the preset memory is updated to the modified cooking parameter set in the modification instruction.

9. The method according to claim 3, characterized in that, The method further includes: If a fourth target cookware is detected among multiple preset cookwares, the third cookware identification information corresponding to the fourth target cookware is retrieved from the preset memory; the fourth target cookware is a preset cookware among the multiple preset cookwares whose cumulative waiting time exceeds the preset waiting time. Based on the third cookware identification information, usage prompt information corresponding to the fourth target cookware is generated.

10. A cookware identification device, characterized in that, The device includes: The first feature acquisition module is used to acquire features of the first target cookware when the temperature of the cookware corresponding to the first target cookware is lower than a preset temperature, and obtain the first cold-state feature data corresponding to the first target cookware. The second feature acquisition module is used to heat the first target cookware and acquire features of the first target cookware to obtain the first thermal feature data corresponding to the first target cookware. The first feature extraction module is used to extract features from the first target cookware based on the first cold-state feature data and the first hot-state feature data, so as to obtain the first cookware feature data corresponding to the first target cookware. The material recognition module is used to identify the target cookware material information corresponding to the first target cookware from a variety of different preset cookware material information based on the first cookware feature data.

Images