A multifunctional electric steamer intelligent control system and method

Abstract

This invention discloses a multifunctional electric steamer intelligent control system and method, including a steam generating unit with a fractal guide plate and a gradient porosity metal foam layer distributed on its surface, the porosity of which continuously and gradually changes along the steam flow direction; an asymmetric pulse control unit with a solenoid valve driven by a pulse signal with an adjustable duty cycle, used to form a high-low pressure alternating steam flow with a preset alternating cycle from the steam flow guided by the fractal guide plate; a temperature field monitoring unit including a temperature sensor array distributed on the inner wall of the cooking cavity, forming a spatial temperature field feedback network to monitor the temperature inside the cooking cavity and perform CFD simulation; and a dynamic injection adjustment unit using a rotary steam nozzle, used to adjust the nozzle's injection angle in real time according to the CFD simulation results to inject high-low pressure alternating steam flow. This invention achieves uniform steam flow distribution within the electric steamer, thereby avoiding the problem of localized overcooking or undercooking of food, and improving cooking efficiency and quality.

Description

Technical Field

[0001] This invention relates to the field of intelligent control technology for electric steamers, and in particular to an intelligent control system and method for a multifunctional electric steamer. Background Technology

[0002] Electrode steam boilers utilize electrode heating to generate steam that meets specific requirements for user consumption. Traditional electric steamers have low steam generation efficiency and require segmented heating with different power levels, which often results in uneven steam distribution, failing to ensure even heating of food during cooking. Consequently, they cannot meet the complex requirements of different foods for varying steam cooking environments, significantly limiting cooking results and adaptability to different food types. Summary of the Invention

[0003] To address at least one of the aforementioned technical problems, this invention provides a multifunctional electric steamer intelligent control system and method.

[0004] In a first aspect, the present invention provides a multifunctional electric steamer intelligent control system, the system comprising:

[0005] The steam generating unit is equipped with a fractal guide plate, and the surface of the fractal guide plate is distributed with a gradient porosity metal foam layer, the porosity of which changes continuously and gradually along the steam flow direction.

[0006] The asymmetric pulse control unit is equipped with a solenoid valve, which is driven by a pulse signal with an adjustable duty cycle and is used to form a high-low pressure alternating steam flow with a preset alternating cycle from the steam flow guided by the fractal guide plate.

[0007] The temperature field monitoring unit includes an array of temperature sensors distributed on the inner wall of the cooking cavity, forming a spatial temperature field feedback network for monitoring the temperature inside the cooking cavity and performing CFD simulation.

[0008] The dynamic injection adjustment unit uses a rotary steam nozzle to adjust the injection angle of the nozzle in real time according to the CFD simulation results, so as to inject the high and low pressure alternating steam flow.

[0009] Preferably, the fractal guide plate adopts a Hilbert curve fractal configuration, and the branch spacing satisfies:

[0010] Δd=0.8 n ×D

[0011] In the formula, Δd represents the branch spacing, n represents the number of fractal iterations (n≥3), and D is the initial spacing.

[0012] Preferably, the porosity gradually changes from 50% to 80% along the steam flow direction, and the porosity gradient distribution of the metal foam layer satisfies the following condition: the porosity at the inlet end is:

[0013]

[0014] In the formula, μ in The value represents the porosity at the inlet end, x represents the axial position, and L represents the total length of the channel.

[0015] Preferably, the preset alternation period is 2-5 seconds.

[0016] Preferably, the rotary steam distributor has a rotation angle of 30°-150°.

[0017] Preferably, the temperature sensor array is divided into three layers from closest to farthest from the bottom of the electric steamer: a first layer, a second layer, and a third layer, with the number of sensors decreasing in each layer.

[0018] Preferably, the system further includes:

[0019] The scale removal unit integrates quantum dot fluorescent probes to identify water hardness through characteristic emission spectra. The water hardness is then input into a pre-trained LSTM model to predict scale trends, and an automatic citric acid cleaning program is triggered based on the prediction results.

[0020] In a second aspect, the present invention also provides a smart control method for a multi-functional electric steamer, applied to the smart control system of the multi-functional electric steamer as described in any one of the first aspects, the method comprising:

[0021] Temperature field data in three dimensions inside the electric steamer are collected by an array of temperature sensors distributed on the inner wall of the cooking cavity.

[0022] Determine the simulation parameters, including steam flow parameters and fractal guide plate structure parameters, and use the nozzle injection angle range as the boundary condition. Input the simulation parameters and boundary conditions into the CFD model for simulation.

[0023] The initial flow field is inverted based on temperature field data, and the steam flow control equation is solved using a transient turbulence model to calculate the non-uniformity index of the flow field.

[0024] The system determines whether the non-uniformity index exceeds a preset threshold. When it does, it calculates the nozzle angle correction amount to control steam injection and triggers the solenoid valve to dynamically adjust the duration ratio of alternating high and low pressure steam flow according to the flow field uniformity until the non-uniformity index is within the preset threshold, thus forming a closed-loop control of the steam flow inside the electric steamer.

[0025] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0026] The intelligent control system of this multifunctional electric steamer provides a method to drive a solenoid valve with an adjustable duty cycle pulse signal to generate alternating high and low pressure steam flows. This enhances the adaptability of ingredients and ensures different steam supplies at different stages. By collecting temperature data and performing CFD simulation, the dynamic injection adjustment unit uses a rotary steam nozzle. Based on the CFD simulation results, it can adjust the nozzle's injection angle in real time, ensuring that the alternating high and low pressure steam flows are accurately injected into all areas of the cooking chamber. This allows the ingredients to be heated evenly in a more suitable steam environment, significantly improving the cooking effect. Therefore, this invention, through the coordinated operation of the steam generation unit, asymmetric pulse control unit, temperature field monitoring unit, and dynamic injection adjustment unit, effectively solves the problems of unreasonable steam generation and distribution, inaccurate steam control, incomplete temperature monitoring, and lack of flexibility in steam injection found in existing technologies. It achieves efficient steam generation and uniform distribution, can accurately adjust steam pressure and flow to match the cooking needs of different ingredients, comprehensively and in real time monitors and precisely controls the temperature field within the cooking chamber, and flexibly adjusts the steam injection angle to ensure even heating of ingredients, greatly improving the intelligence level and cooking effect of the electric steamer.

[0027] 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

[0028] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the accompanying drawings used in the embodiments of the present invention or the background art will be described below.

[0029] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the specification, serve to illustrate the technical solutions of this disclosure.

[0030] Figure 1 This is a schematic diagram of the structure of a multifunctional electric steamer intelligent control system provided in an embodiment of the present invention;

[0031] Figure 2 This is a schematic diagram of the structure of a multifunctional electric steamer intelligent control system provided in another embodiment of the present invention;

[0032] Figure 3 This is a flowchart illustrating a smart control method for a multifunctional electric steamer provided in an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0035] Current electric steamers suffer from uneven steam distribution during use, leading to localized overheating or underheating, resulting in overcooked or undercooked food and severely impacting cooking outcomes. To address this, this invention provides a multifunctional intelligent control system and method for an electric steamer. Through the coordinated operation of a steam generation unit, an asymmetric pulse control unit, a temperature field monitoring unit, and a dynamic jet adjustment unit, it effectively solves problems in existing technologies such as unreasonable steam generation and distribution, inaccurate steam control, incomplete temperature monitoring, and lack of flexibility in steam jetting.

[0036] Please see Figure 1 , Figure 1 This is a schematic diagram of the structure of a multifunctional electric steamer intelligent control system provided in an embodiment of the present invention. Figure 1 As shown, the intelligent control system of the multi-functional electric steamer includes:

[0037] The steam generating unit 100 is equipped with a fractal guide plate, and the surface of the fractal guide plate is distributed with a gradient porosity metal foam layer, the porosity of which changes continuously and gradually along the steam flow direction.

[0038] The asymmetric pulse control unit 200 is equipped with a solenoid valve, which is driven by a pulse signal with an adjustable duty cycle and is used to form a high-low pressure alternating steam flow with a preset alternating cycle from the steam flow guided by the fractal guide plate.

[0039] The temperature field monitoring unit 300 includes an array of temperature sensors distributed on the inner wall of the cooking cavity, forming a spatial temperature field feedback network for monitoring the temperature inside the cooking cavity and performing CFD simulation.

[0040] The dynamic injection adjustment unit 400 uses a rotary steam nozzle to adjust the injection angle of the nozzle in real time according to the CFD simulation results, so as to inject the high and low pressure alternating steam flow.

[0041] To facilitate understanding, the following terms will be explained first:

[0042] Fractal baffle: A fractal is a geometric shape with self-similar properties. Fractal baffles utilize this property in their design, creating a self-similar branching structure in the steam flow path. This effectively increases the contact area between the steam and the baffle, improves steam flow efficiency, and optimizes the distribution of steam within the cooking cavity.

[0043] Gradient porosity metal foam layer: Metal foam is a metallic material with a large number of pores inside. Gradient porosity means that the porosity gradually changes from the steam inlet to the outlet. This structure allows steam to flow rapidly in the large pores when passing through the metal foam layer. As the pores become smaller, the steam is gradually dispersed and stabilized, reducing turbulence and energy loss during steam flow, while also filtering impurities.

[0044] Adjustable duty cycle pulse signal: A pulse signal is a periodic signal. The duty cycle is the ratio of the time the signal is at a high level to the total time of the cycle. An adjustable duty cycle means that this ratio can be changed through a control circuit or program. In this system, the opening and closing time of the solenoid valve is controlled by adjusting the duty cycle, thereby creating an alternating high and low pressure steam flow.

[0045] CFD simulation: CFD, or Computational Fluid Dynamics, analyzes systems involving fluid flow and heat conduction through computer numerical calculations and graphical displays. In this system, CFD simulation technology is used to simulate the flow and temperature field distribution of steam within the cooking cavity based on data collected by temperature sensors, providing a basis for precisely controlling steam parameters and injection angles.

[0046] In this embodiment, the cooperative relationship between the various units is as follows: The steam generating unit 100 employs a fractal guide plate and a gradient metal foam layer. Using a topology optimization algorithm, after the steam generating unit operates, the generated steam flows along the pores of the gradient metal foam layer. The asymmetric pulse control unit 200 is equipped with a pulse signal generator and a solenoid valve. When steam flows, the pulse signal generator responds, adjusting the pulse signal period through the duty cycle adjustment knob to generate a control signal, thereby controlling the size of the solenoid valve and achieving alternating control of high-pressure and low-pressure steam flows. Simultaneously, the system monitors the temperature field within the cooking cavity of the electric steamer through the temperature field monitoring unit 300. Combining CFD simulation technology, it determines whether the non-uniformity index of the flow field is within a preset threshold. If it exceeds the threshold, it indicates non-uniform distribution. At this time, the dynamic injection adjustment unit 400 uses a rotary steam nozzle to adjust the nozzle's injection angle in real time according to the CFD simulation results, injecting alternating high and low-pressure steam flows into the cooking cavity until the non-uniformity index of the flow field meets the standard, thereby achieving closed-loop steam flow and temperature field control to ensure cooking quality.

[0047] The fractal guide plate utilizes high-precision 3D printing technology and is made of food-grade stainless steel. Before printing, the complex shape of the guide plate is precisely designed based on fractal principles using professional modeling software, ensuring that the steam flow path on its surface exhibits a highly self-similar branching structure. During the printing process, various parameters are strictly controlled to ensure that the dimensional accuracy of the guide plate is within ±0.1mm, thereby achieving efficient steam guidance. The gradient porosity metal foam layer is constructed using chemical vapor deposition (CVD) technology, with the fractal guide plate placed inside the deposition equipment. By precisely controlling parameters such as deposition time, reactive gas flow rate, and deposition temperature—for example, setting a longer time and a larger gas flow rate in the initial stage of deposition—the porosity of the metal foam layer at the steam inlet reaches 40%-50%. As the deposition process progresses, the time and gas flow rate are gradually reduced, allowing the porosity at the outlet to drop to 20%-30%, thus achieving a continuous gradual change in porosity along the steam flow direction.

[0048] For asymmetric pulse control units, stable microcontrollers such as the STM32 series can be used to generate pulse signals. A program to generate pulse signals with adjustable duty cycles is written using specialized programming software. Simultaneously, a touch-screen interface is installed on the control panel of the electric steamer, or a corresponding mobile app is developed. Users can input different cooking modes (such as steaming fish, steaming buns, steaming vegetables, etc.) through the interface or app. The system automatically converts the cooking mode into a corresponding duty cycle value based on a preset algorithm, thereby controlling the opening and closing time ratio of the solenoid valve. The solenoid valve can be a pilot-operated solenoid valve with a high temperature resistance up to 150℃ and a response time of less than 5ms. The solenoid valve is installed near the outlet of the fractal guide plate in the steam pipe to ensure a rapid response to the pulse signal, accurately switching the steam flow to a preset alternating high and low pressure steam flow.

[0049] The temperature sensor array preferably uses thermistor temperature sensors with an accuracy of ±0.5℃, evenly distributed on the inner wall of the cooking cavity according to its shape and size. For common 30L-50L cooking cavities, the sensor spacing is set to 6-8 cm, and they are fixed with dedicated sensor mounting brackets to ensure secure and accurate sensing of the cavity temperature. All sensors are connected to the data acquisition module via high-temperature shielded cables. The data collected by the temperature sensors is transmitted to a computer in real time through the data acquisition module. The software is used to build a precise 3D model of the cooking cavity with millimeter-level accuracy. Parameters such as the physical properties of steam and flow boundary conditions are set. The software simulates the temperature field distribution inside the cavity based on the input data and presents it in the form of an intuitive temperature cloud map. Based on the simulation results, the system adjusts the relevant parameters of the steam generation unit and the dynamic injection adjustment unit through a control algorithm. The rotary steam nozzle can be a rotary steam nozzle driven by a stepper motor. The nozzle material is selected from high-temperature resistant and steam corrosion resistant high-performance ceramics. The stepper motor is connected to a microcontroller. The microcontroller accurately calculates the required rotation angle and time of the nozzle based on the temperature field data obtained from CFD simulation, and sends control pulse signals to the stepper motor to achieve real-time control of the nozzle injection angle. The nozzle is installed at the top of the cooking chamber to ensure that steam evenly covers the food inside. Furthermore, a specialized control algorithm can be developed to enable the microcontroller to quickly and accurately adjust the nozzle angle based on CFD simulation results. The algorithm considers factors such as the dynamic characteristics of steam flow, the rate of temperature change, and the thermal conductivity of the food, ensuring that alternating high and low pressure steam flows are precisely injected into areas with lower temperatures or densely distributed food.

[0050] In the above embodiments, the unique self-similar branching structure of the fractal structure guide plate significantly increases the contact area between steam and the guide plate. Compared with traditional flat guide plates, the steam guiding efficiency is greatly improved, enabling the steam to be evenly guided to all parts of the cooking cavity, reducing steam accumulation and local overheating, and ensuring uniform heating of the food. The gradient porosity metal foam layer effectively stabilizes the steam flow, reduces turbulence, and minimizes energy loss during steam flow. At the same time, the porous structure can filter out tiny impurities in the steam, ensuring steam purity and improving the cooking quality of the food. Precise control of the solenoid valve via a pulse signal with adjustable duty cycle allows for fine adjustment of steam pressure, with multiple high and low pressure alternation modes to meet the specific steam pressure requirements of different foods. A temperature sensor array fully covers the cooking cavity, and combined with high-precision CFD simulation, it can monitor the temperature field distribution within the cavity in real time and accurately, with a temperature monitoring accuracy of ±1℃. Compared with traditional single-point or few-point temperature monitoring, it can promptly detect abnormal temperature areas within the cavity, preventing localized overheating or undercooking of the food. By precisely adjusting the steam jet angle, the cooking time for ingredients can be shortened, while avoiding problems such as undercooked or overcooked ingredients due to uneven steam distribution, thus significantly improving the cooking quality of ingredients.

[0051] In one embodiment, the fractal guide plate adopts a Hilbert curve fractal configuration, and the branch spacing satisfies:

[0052] Δd=0.8 n ×D

[0053] In the formula, Δd represents the branch spacing, n represents the number of fractal iterations (n≥3), and D is the initial spacing.

[0054] The Hilbert curve, through recursive plane segmentation, forms a continuous path without intersections. The progressively decreasing spacing breaks up large-scale vortices in the steam flow, resulting in a more gradual flattening of the pressure difference distribution between adjacent levels. 0.8 n The value of 0.8 is close to the reciprocal of the golden ratio (0.618), which takes into account hydrodynamic efficiency.

[0055] In one embodiment, the porosity gradually changes from 50% to 80% along the steam flow direction, and the porosity gradient distribution of the metal foam layer satisfies the following condition: the porosity at the inlet end is:

[0056]

[0057] In the formula, μ in The value represents the porosity at the inlet end, x represents the axial position, and L represents the total length of the channel.

[0058] In the formula, 0.5 is the basic porosity, which exists regardless of the position of x. That is the change in porosity. The calculation calculates the proportion of the current position x within the total channel length L, squares it, and multiplies it by 0.3 to obtain the porosity increment based on the position change. When x is 0, that is, at the channel inlet... When μ is 0, μ in The value is 0.5, which aligns with the initial inlet porosity of 50%. As x increases, Get bigger It also increases, and the porosity increment also increases until x = L, that is, at the channel outlet, μ in =0.8, achieving an outlet porosity of 80%. This formula allows for precise control of the metal foam layer's porosity from inlet to outlet, maintaining a continuous and gradual change from 50% to 80%, optimizing steam flow, stabilizing steam, reducing energy loss, and filtering impurities.

[0059] In one embodiment, the preset alternation cycle is 2-5 seconds. In practice, the cycle length of the duty cycle adjustable pulse signal is precisely controlled through microcontroller programming. For example, when the user selects the steaming fish mode, the preset alternation cycle can be set to 3 seconds. Within these 3 seconds, the solenoid valve opens and closes with a specific duty cycle according to the pulse signal, forming alternating high and low pressure steam flows. Assuming the duty cycle is set to 60%, then within these 3 seconds, the solenoid valve opens for 1.8 seconds and closes for 1.2 seconds, with the high-pressure steam flow lasting 1.8 seconds and the low-pressure steam flow lasting 1.2 seconds. From the perspective of the impact on steam flow, a shorter preset alternation cycle (e.g., 2 seconds) allows for more frequent switching between high and low pressure steam flows, resulting in more vigorous steam agitation within the cooking chamber, accelerating heat transfer. This is suitable for smaller, easily cooked ingredients, quickly steaming them while maintaining their tender texture. A longer preset alternating cycle (e.g., 5 seconds) results in a slower switching between high and low pressure steam flows, leading to a gentler and more sustained steam effect. This is suitable for larger, harder-to-cook ingredients, ensuring that heat penetrates deep into the food while preventing localized overheating. In terms of cooking results, taking steaming different ingredients as an example, when steaming shrimp, a 2-second preset alternating cycle ensures the shrimp is heated evenly in a short time, resulting in tender and elastic shrimp meat. This precise preset alternating cycle setting greatly enhances the electric steamer's adaptability to different ingredients, significantly optimizing cooking results.

[0060] In one embodiment, the rotary steam distributor has a rotation angle of 30°-150°. Because the steam can be precisely sprayed onto areas of lower temperature or with more food distribution within the cooking chamber, the food is heated more evenly. Taking steaming a whole chicken as an example, when using a fixed-angle steam nozzle, the difference in doneness between the breast and leg parts can reach 15%-20%, while using a 30°-150° rotatable steam distributor can control the difference in doneness to within 8%. This results in more consistent texture and more uniform tenderness, significantly improving the overall cooking quality.

[0061] In one embodiment, the temperature sensor array is divided into three layers from closest to farthest from the bottom of the electric steamer: a first layer, a second layer, and a third layer, with the number of sensors decreasing in each layer. Specifically, the sensors can be arranged as follows: 6-8 sensors at the bottom layer (20mm from the bottom surface), 4-6 sensors at the middle layer (80mm from the bottom surface), and 2-4 sensors at the top layer (140mm from the bottom surface) to ensure accurate temperature detection.

[0062] See Figure 2 In one embodiment, the system further includes:

[0063] The scale removal unit 500 integrates a quantum dot fluorescent probe to identify water hardness through characteristic emission spectra. The water hardness is then input into a pre-trained LSTM model to predict scale trends, triggering an automatic citric acid cleaning program based on the prediction results.

[0064] In this embodiment, the quantum dot fluorescent probe can be a quantum dot fluorescent probe with high sensitivity and specificity to key ions affecting water hardness, such as calcium and magnesium ions. These quantum dot fluorescent probes emit characteristic emission spectra related to ion concentration when excited by light of a specific wavelength. For example, a quantum dot fluorescent probe based on a CdSe / ZnS core-shell structure can achieve a detection limit for calcium ions at the nanomolar level. The quantum dot fluorescent probe is fixed to the surface of a specially designed sensor chip, which is encapsulated in a waterproof and corrosion-resistant shell and installed in the water inlet pipe or bottom of the water tank of an electric steamer, ensuring full contact with water. Microfluidic technology allows water to flow through the probe area, ensuring sufficient reaction between ions in the water and the probe.

[0065] Furthermore, a small fluorescence spectrometer is built into the scale removal unit 500 to excite the quantum dot fluorescent probe and detect its emission spectrum. The spectrometer emits light of a specific wavelength, such as 365nm ultraviolet light, which illuminates the quantum dot fluorescent probe, and then collects the fluorescence spectrum emitted by the probe. The spectrometer transmits the collected spectral data to the main control chip of the electric steamer via a data cable. The main control chip performs preliminary data processing to extract characteristic parameters of the spectrum, such as peak wavelength and fluorescence intensity, which are closely related to water hardness.

[0066] After detecting water hardness, it's necessary to further predict scale formation trends, which can be achieved using an LSTM model. Training the model requires collecting a large amount of water sample data with different hardness levels, including corresponding spectral feature parameters and actual measured hardness values. This data is preprocessed, such as through normalization, to ensure it's within a uniform scale, facilitating model training. The preprocessed data is then divided into training and testing sets. The training set is used to train the model, adjusting its parameters to accurately predict water hardness based on spectral feature parameters. After multiple rounds of training and optimization, the model achieves a prediction accuracy of over 90% on the testing set. The trained LSTM model is then deployed to the main control chip of the electric steamer. The main control chip uses the spectral data collected by the quantum dot fluorescent probe to predict water hardness through the LSTM model and further predict scale formation trends. For example, based on historical data and current water hardness, it can predict the potential scale accumulation over the next week. The automatic citric acid cleaning program is triggered based on the scale formation trend. A scale accumulation threshold is set in the electric steamer's control system. When the scale accumulation predicted by the LSTM model exceeds this threshold, the automatic citric acid cleaning program is automatically triggered. For example, if the system predicts that scale accumulation will reach a level affecting the steamer's performance within the next week, the cleaning program will begin. When the cleaning program is triggered, an automatic injection device injects citric acid solution into the water in the steam generating unit according to a preset ratio. Then, the steamer starts its steam generation program, causing the citric acid-containing steam to circulate within the cooking chamber, dissolving the scale through a chemical reaction. After cleaning, an automatic drainage device discharges the cleaned water from the steamer.

[0067] Thus, by using quantum dot fluorescent probes and spectral detection technology, water hardness can be identified quickly and accurately. By using a pre-trained LSTM model to predict scale trends, the accumulation of scale can be anticipated in advance, and an automatic citric acid cleaning program can be triggered promptly based on the prediction results. This cleans the scale before it accumulates in large quantities, effectively reducing the impact of scale on the performance of the electric steamer.

[0068] See Figure 3 In one embodiment, the present invention also provides a smart control method for a multifunctional electric steamer, applied to the smart control system of the multifunctional electric steamer as described in any of the above embodiments, the method comprising:

[0069] S10. Collect temperature field data in the three-dimensional space inside the electric steamer by an array of temperature sensors distributed on the inner wall of the cooking cavity;

[0070] S20. Determine the simulation parameters, including steam flow parameters and fractal guide plate structure parameters. Use the nozzle injection angle range as the boundary condition and input the simulation parameters and boundary conditions into the CFD model for simulation.

[0071] S30. Based on the temperature field data, the initial flow field is inverted, and the transient turbulence model is used to solve the steam flow control equations in order to calculate the non-uniformity index of the flow field.

[0072] S40. Determine whether the non-uniformity index exceeds the preset threshold. When it exceeds the preset threshold, calculate the nozzle angle correction amount to control the steam injection and trigger the solenoid valve to dynamically adjust the duration ratio of the high and low pressure alternating steam flow according to the flow field uniformity until the non-uniformity index is within the preset threshold, thus forming a closed-loop control of the steam flow inside the electric steamer.

[0073] To facilitate understanding, the control process will be explained in detail below:

[0074] 1) Three-dimensional spatial temperature field data {T(x,y,z,t)} is collected by an array of 12-14 temperature sensors distributed on the inner wall of the cooking cavity with a sampling period of 0.5-2 seconds;

[0075] 2) Construct a real-time computational fluid dynamics (CFD) simulation model. Input parameters include:

[0076] Steam flow parameters: pulse high pressure stage velocity 3-5m / s, low pressure stage velocity 1-2m / s, period T = 2-5 seconds;

[0077] Structural parameters: Hilbert curve of fractal guide plate, fractal order n≥3, porosity distribution function of metal foam.

[0078]

[0079] Dynamic boundary conditions: Nozzle angle θ(t)∈[30°,150°]

[0080] 3) Based on the temperature field data {T(x,y,z,t)}, the initial flow field is inverted, and the transient SST k-ω turbulence model is used to solve the steam flow control equations:

[0081]

[0082] In the formula, ρ is the steam density, with units of kg / m³. 3 ui is the velocity vector component, i = x, y, z, used to describe the three-dimensional velocity distribution of the flow field and determine the convection intensity; p represents static pressure, μ represents dynamic viscosity, μt is turbulent viscosity, Sporous represents the porous medium source term, K represents permeability, and β represents the inertial drag coefficient.

[0083] 4) Determine the flow field non-uniformity index:

[0084]

[0085] In the formula, η(t) is the dimensionless non-uniformity, V represents the effective volume of the cooking cavity, uˉ(t) is the instantaneous spatial average velocity, and u(x,t) is the component of the velocity vector on the x-axis. When η(t)>0.08, it indicates the existence of a local low-speed zone (which easily leads to undercooked food) or a high-speed concentrated flow (which leads to overcooking), and the nozzle adjustment needs to be triggered.

[0086] The nozzle angle correction is calculated using the adjoint optimization algorithm.

[0087]

[0088] In the formula, J is the multi-objective loss function, δ is the regularization coefficient, and Δθ is the standard deviation. k This represents the angle correction amount for the k-th nozzle;

[0089] 5) Determine the updated nozzle angle θ based on the angle correction amount. k (t+Δt), generating vector steam injection:

[0090] θ k (t+Δt)=θ k (t)+Δθ k

[0091] 6) Trigger the asymmetric pulse control module to dynamically adjust the high-low pressure duration ratio based on the flow field uniformity:

[0092]

[0093] In the formula, t high t low The durations of the high-pressure and low-pressure steam flows are respectively, and sigmoid is the sigmoid function. The ratio of the high-pressure and low-pressure durations is adjusted in this way to form a closed-loop control until η(t)≤0.08.

[0094] In summary, the intelligent control method provided in this embodiment collects temperature data and performs CFD simulation. The dynamic injection adjustment unit adopts a rotary steam nozzle, which can adjust the injection angle of the nozzle in real time according to the CFD simulation results. This ensures that the alternating high and low pressure steam flow is accurately injected into each area of ​​the cooking chamber, so that the food is heated evenly in a more suitable steam environment, significantly improving the cooking effect.

[0095] In one embodiment, after cooking, an integrated quantum dot fluorescent probe may be included to identify water hardness through characteristic emission spectra. The water hardness is then input into a pre-trained LSTM model to predict limescale trends, triggering an automatic citric acid cleaning program based on the prediction results. The specific water hardness detection and limescale trend prediction processes can be found in the aforementioned embodiments. Thus, water hardness can be quickly and accurately identified using quantum dot fluorescent probes and spectral detection technology. By using a pre-trained LSTM model to predict limescale trends, the accumulation of limescale can be anticipated in advance, and the automatic citric acid cleaning program can be triggered promptly based on the prediction results, cleaning before a large amount of limescale accumulates, effectively reducing the impact of limescale on the performance of the electric steamer.

[0096] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0097] Those skilled in the art will readily understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. Those skilled in the art will also readily understand that the various embodiments of the present invention have different focuses, and for the sake of convenience and brevity, the same or similar parts may not be repeated in different embodiments. Therefore, parts not described or not described in detail in one embodiment can be referred to in other embodiments.

Claims

1. A multifunctional cooking electric steamer intelligent control system, characterized in that, The system includes: The steam generating unit is equipped with a fractal guide plate, which adopts a Hilbert curve fractal configuration and has a gradient porosity metal foam layer distributed on its surface. The porosity gradually changes from 50% to 80% along the steam flow direction. The porosity gradient distribution of the metal foam layer satisfies the following condition: the porosity at the inlet end is: ； wherein represents the inlet end porosity, is the axial position, is the total length of the channel; The branch spacing of the fractal guide plate satisfies: ； wherein represents the branching pitch, represents the number of fractal iterations, , is the initial pitch; The asymmetric pulse control unit is equipped with a solenoid valve, which is driven by a pulse signal with an adjustable duty cycle and is used to form a high-low pressure alternating steam flow with a preset alternating cycle from the steam flow guided by the fractal guide plate. The temperature field monitoring unit includes an array of temperature sensors distributed on the inner wall of the cooking cavity, forming a spatial temperature field feedback network for monitoring the temperature inside the cooking cavity and performing CFD simulation. The dynamic injection adjustment unit uses a rotary steam nozzle to adjust the injection angle of the nozzle in real time according to the CFD simulation results, so as to inject the high and low pressure alternating steam flow. Control unit, the control unit being configured to: Temperature field data in three dimensions inside the electric steamer are collected by an array of temperature sensors distributed on the inner wall of the cooking cavity. Determine the simulation parameters, including steam flow parameters and fractal guide plate structure parameters, and use the nozzle injection angle range as the boundary condition. Input the simulation parameters and boundary conditions into the CFD model for simulation. The initial flow field is inverted based on temperature field data, and the steam flow control equation is solved using a transient turbulence model to calculate the non-uniformity index of the flow field. The system determines whether the non-uniformity index exceeds a preset threshold. When it does, it calculates the nozzle angle correction amount to control steam injection and triggers the solenoid valve to dynamically adjust the duration ratio of alternating high and low pressure steam flow according to the flow field uniformity until the non-uniformity index is within the preset threshold, thus forming a closed-loop control of the steam flow inside the electric steamer.

2. The multi-functional cooking electric steamer intelligent control system according to claim 1, wherein, The preset alternation period is 2-5 seconds.

3. The multi-functional cooking electric steamer intelligent control system according to claim 1, wherein, The rotary steam distributor has a rotation angle of 30°-150°.

4. The multi-functional cooking electric steamer intelligent control system according to claim 1, wherein, The temperature sensor array is divided into three layers from closest to farthest from the bottom of the electric steamer: the first layer, the second layer, and the third layer, with the number of sensors decreasing in each layer.

5. The multi-functional cooking electric steamer intelligent control system according to claim 1, wherein, The system also includes: The scale removal unit integrates quantum dot fluorescent probes to identify water hardness through characteristic emission spectra. The water hardness is then input into a pre-trained LSTM model to predict scale trends, and an automatic citric acid cleaning program is triggered based on the prediction results.

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