A stir-fry control system and method

Abstract

The application discloses a kind of stir-frying control system and method, it is related to automatic control field, to reduce the problem caused by single temperature or time of existing automation equipment only judges, wherein product stir-frying system includes infrared temperature measurement probe, sound probe, controller, NIR spectrum probe, light instrument, the initial surface temperature of controller is calculated output temperature according to stage one beginning, according to the output power of heater is adjusted according to output temperature calculation result;The energy proportion of preset frequency band is calculated, when the real-time surface temperature of material reaches preset value, the energy proportion of preset frequency band is less than preset value, and the absolute value of energy proportion of preset frequency band change rate is less than or equal to 0.01 per second, enter stage two;Dynamic peak temperature is calculated, with dynamic peak temperature as control target, adjust the power output of heater;Predicted color value is calculated, when predicted color value reaches or exceeds preset target color threshold, determine that stir-frying is completed, and stir-frying is terminated.

Description

Technical Field

[0001] This invention relates to the field of automatic control, and more particularly to a stir-frying control system and method. Background Technology

[0002] The process of stir-frying ingredients like nuts and chili peppers into chili oil is a crucial step in food processing. Its core lies in precise heat treatment to induce Maillard and caramelization reactions, resulting in a unique color, aroma, and crispy texture. Traditionally, chili oil is stir-fried manually, relying on the operator's personal experience. This involves subjective judgment of heat and timing based on visual observation of the color, aroma, and the sound of the stir-frying process. However, this method has several drawbacks: product quality is extremely inconsistent, with poor uniformity between batches and even within the same batch, making standardized production impossible; secondly, production efficiency is low, hindering large-scale production; thirdly, there are significant food safety and hygiene risks; and finally, the training period for skilled workers is long, resulting in high labor costs.

[0003] To address the problems associated with manual stir-frying, some automated or semi-automated stir-frying equipment has emerged. These devices typically possess basic temperature control and timed stirring functions. However, they suffer from the following issues: most existing stir-frying equipment relies on a single pot temperature or time-based program control, which can easily lead to situations where the internal state of the material (such as moisture and color) is decoupled from the pot temperature. This results in situations where the temperature reaches the preset value but the material is undercooked (not fully cooked), or the temperature does not exceed the set value but the material is overcooked (burnt). Furthermore, this results in insufficient accuracy in stage switching (such as switching from the dehydration stage to the flavor generation stage), making it difficult to guarantee the stability of the final product quality. Summary of the Invention

[0004] Therefore, in order to overcome the above-mentioned shortcomings, the present invention provides a stir-frying control system and method to replace the subjective judgment of human smelling and listening, reduce the problem of undercooking or overcooking caused by existing automated equipment relying solely on temperature or time judgment, and improve the quality consistency under large-scale production.

[0005] On one hand, the present invention provides a stir-frying control system, comprising:

[0006] An infrared temperature probe is provided, and multiple infrared temperature probes are provided to form an infrared temperature probe array, which is used to collect the real-time surface temperature of the material and the initial surface temperature at the beginning of the stage.

[0007] A sound probe is used to collect sound information during the stir-frying process;

[0008] NIR spectral probe, which collects optical signals through NIR spectral probe;

[0009] A spectrometer, which is connected to an NIR spectral probe, is used to acquire light signals and establish an NIR spectral model based on the spectral information.

[0010] The controller acquires the initial surface temperature at the start of stage one, calculates the output temperature based on this initial surface temperature, and adjusts the heater's output power in real time using a first PID control algorithm based on the deviation between the calculated output temperature and the real-time surface temperature of the material. It also acquires sound information, performs a Fourier transform on the sound information, and calculates the energy percentage of a preset frequency band. When the real-time surface temperature of the material reaches a preset value, the energy percentage of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy percentage of the preset frequency band is less than or equal to 0.01 seconds, stage two begins. Finally, the controller acquires spectral information and substitutes it into a pre-defined... An established NIR spectral model determines the real-time moisture content and real-time color value of the material. The controller calculates the dynamic peak temperature based on the material's moisture content at the beginning of stage two and at the beginning of stage one. Using the dynamic peak temperature as the control target, the power output of the heater is adjusted through a second PID control algorithm based on the deviation between the dynamic peak temperature and the material's real-time surface temperature. The predicted color value is calculated based on the material's real-time color value, real-time moisture content, and real-time surface temperature. The frying process is terminated based on the predicted color value. When the predicted color value reaches or exceeds a preset target color threshold, the frying process is considered complete and terminated.

[0011] Furthermore, the specific method for calculating the output temperature based on the initial surface temperature at the beginning of the stage is as follows:

[0012] ;

[0013] in, T lt for t It continuously outputs the temperature in degrees Celsius. T 0 The initial surface temperature of the material at the start of the stage, in degrees Celsius; R The heating rate is expressed in degrees Celsius per second. t The cooking time is in seconds.

[0014] Furthermore, the specific method for calculating the energy proportion of the preset frequency band is as follows:

[0015] ;

[0016] in, S t for t At any given time, the energy percentage of the preset frequency band; aThe lowest frequency of the preset frequency band, in Hertz; b The highest frequency of the preset frequency band, in Hertz; c The highest frequency in sound information, measured in Hertz; PSD(f) The power spectral density of the signal; df This refers to the frequency resolution.

[0017] Furthermore, the specific method for calculating the dynamic peak temperature based on the material moisture content at the beginning of stage two and the material moisture content at the beginning of stage one is as follows:

[0018] ;

[0019] in, T max This represents the peak temperature of Phase Two, expressed in degrees Celsius. T 1 represents the preset peak temperature for different types of nuts, in degrees Celsius; K mc This is the moisture compensation coefficient, expressed as a percentage of water content per degree Celsius. M 1 represents the moisture content of the material at the start of Phase Two; M 0 represents the moisture content of the material at the beginning of the stage.

[0020] Furthermore, the specific method for calculating and predicting the color value based on the material's real-time color value, real-time moisture content, and real-time surface temperature is as follows:

[0021] ;

[0022] in, b 1 represents the predicted color value; b 0 represents the real-time color value of the material; The rate of change of color values, in seconds; ∆t The time step is predicted in seconds.

[0023] Furthermore, the rate of change of the color value is calculated as follows:

[0024] ;

[0025] in, A The exponential factor is expressed in seconds. Ea The apparent activation energy of the Maillard reaction, expressed in joules per mole; r The ideal gas coefficient is expressed in joules per mole per Kelvin. M t for t Real-time moisture content of the material; T t fort Real-time surface temperature of the material, in Kelvin; n denoted as the reaction order.

[0026] On the other hand, the present invention also provides a control method for the above-mentioned product roasting system, comprising:

[0027] After the material is put into the oil pot, it enters the first stage. At this time, the controller acquires the initial surface temperature at the beginning of the first stage, the real-time surface temperature of the material during the frying process, and the sound information during the frying process.

[0028] The output temperature is calculated based on the initial surface temperature at the beginning of the stage, and the output temperature calculation result is obtained.

[0029] Based on the deviation between the calculated output temperature and the real-time surface temperature of the material, the output power of the heater is adjusted in real time using the first PID control algorithm.

[0030] The power spectral density is obtained by performing a Fourier transform on the sound information, and the energy proportion of the preset frequency band is calculated.

[0031] When the real-time surface temperature of the material reaches the preset value, the energy proportion of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy proportion of the preset frequency band is less than or equal to 0.01 seconds, the process enters stage two.

[0032] Acquire spectral information, substitute the spectral information into a pre-established NIR spectral model, and determine the real-time moisture content and real-time color value of the material.

[0033] Dynamic peak temperature is calculated based on the moisture content of the material at the beginning of stage two and the moisture content of the material at the beginning of stage one.

[0034] Using the dynamic peak temperature as the control target, the power output of the heater is adjusted according to the deviation between the dynamic peak temperature and the real-time surface temperature of the material through a second PID control algorithm.

[0035] The predicted color value is calculated based on the real-time color value, the real-time moisture content, and the real-time surface temperature.

[0036] The frying process is terminated based on the predicted color value. When the predicted color value reaches or exceeds the preset target color threshold, the frying process is considered complete and terminated.

[0037] The present invention has the following advantages:

[0038] This invention uses an infrared temperature probe array to collect the surface temperature of the material in real time, uses a first PID control algorithm to dynamically adjust the heater power, uses a sound probe to collect sound signals, and uses Fourier transform to analyze the changes in high-frequency noise (representing the sound of water vapor bursting) as an auxiliary criterion for the end of a stage. Combining the real-time surface temperature of the material and the spectral characteristics of the sound signal as dual core criteria, it replaces the subjective judgment of human smelling and listening, reduces the problems of undercooked or overcooked materials caused by existing automated equipment relying solely on temperature or time judgment, and improves the quality consistency under large-scale production. This embodiment integrates an NIR spectral probe onto the upper part of the stirrer, enabling online acquisition of material and real-time inversion of moisture content and color values ​​to quantify the degree of browning and reaction progress, achieving real-time monitoring of the Maillard reaction and caramelization reaction. Based on the initial moisture content of the material, the moisture content at the start of stage two, and the type of material, the peak temperature of stage two is dynamically calculated, ensuring that the material temperature is maintained within the optimal reaction range. This maximizes the generation of nut aroma and color, and reduces the generation of harmful byproducts such as acrylamide. By using real-time color values, moisture, and temperature to form a multi-dimensional basis for predicting the color value at future time points, the roasting process is terminated when the predicted color value reaches the preset optimal flavor threshold range. This can improve the problem of insufficient flavor due to premature termination or scorching due to delayed termination. Attached Figure Description

[0039] Figure 1 This is a logic diagram of the stir-frying control system;

[0040] Figure 2 This is a schematic diagram of the stir-frying equipment described in Example 3;

[0041] Figure 3 yes Figure 2 A schematic diagram of the wok module in the stir-frying equipment shown;

[0042] Figure 4 yes Figure 3 A cross-sectional view of the wok module shown;

[0043] Figure 5 yes Figure 2 A schematic diagram of the lifting and stirring mechanism in the frying system shown.

[0044] Figure 6 yes Figure 5 A schematic diagram of the agitator in the lifting and stirring mechanism shown;

[0045] Figure 7 yes Figure 5 The diagram shows the structure of the pot lid in the lifting and stirring mechanism.

[0046] In the picture:

[0047] 100. Wok module; 110. Oil pan; 111. Inner layer; 112. Outer layer; 120. Frame; 130. Handwheel; 140. Heater; 150. Worm gear transmission mechanism;

[0048] 200. Lifting and stirring mechanism; 210. Frame; 220. First power unit; 230. Slide seat; 240. Second power unit; 250. Pot lid; 260. Stirrer;

[0049] 300, NIR spectral probe;

[0050] 400. Infrared temperature probe;

[0051] 500. Sound probe;

[0052] 600. Infrared temperature probe array;

[0053] 700, Controller. Detailed Implementation

[0054] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0055] In this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0056] As described in the background section, most existing frying equipment is based on a single pot temperature or time for program control. This can easily lead to situations where the internal state of the material (such as moisture and color) is decoupled from the pot temperature, resulting in insufficient frying (uncooked) even when the temperature reaches the preset value, or over-frying (burnt) even when the temperature does not exceed the set value. This results in insufficient accuracy in stage switching (such as switching from the dehydration stage to the flavor generation stage), making it difficult to guarantee the stability of the final product quality.

[0057] Example 1:

[0058] Therefore, in order to solve the above-mentioned technical problems existing in the prior art, this embodiment provides a stir-frying control system, such as... Figure 1As shown, it includes:

[0059] Infrared temperature probe 400, wherein multiple infrared temperature probes are provided and arranged to form an infrared temperature probe array 600, for collecting the real-time surface temperature of the material and the initial surface temperature at the beginning of the stage.

[0060] Sound probe 500 is used to collect sound information during the stir-frying process;

[0061] NIR spectral probe 300, which collects optical signals through an NIR spectral probe;

[0062] The spectrometer 800 is connected to an NIR spectral probe to acquire light signals and generate spectral information based on the light signals.

[0063] Controller 700 is used to acquire the initial surface temperature at the beginning of stage one, calculate the output temperature based on the initial surface temperature at the beginning of stage one, obtain the output temperature calculation result, and adjust the output power of the heater in real time according to the deviation between the output temperature calculation result and the real-time surface temperature of the material through the first PID control algorithm; acquire sound information, perform Fourier transform on the sound information, calculate the energy ratio of the preset frequency band, and when the real-time surface temperature of the material reaches the preset value, the energy ratio of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy ratio of the preset frequency band is less than or equal to 0.01 seconds, enter stage two; the controller acquires spectral information and substitutes the spectral information into the preset... The established NIR spectral model determines the real-time moisture content and real-time color value of the material. The controller calculates the dynamic peak temperature based on the moisture content of the material at the beginning of stage two and the beginning of stage one. Using the dynamic peak temperature as the control target, the power output of the heater is adjusted through a second PID control algorithm based on the deviation between the dynamic peak temperature and the real-time surface temperature of the material. The predicted color value is calculated based on the real-time color value, real-time moisture content, and real-time surface temperature of the material. The frying termination is determined based on the predicted color value. When the predicted color value reaches or exceeds the preset target color threshold, the frying is determined to be complete and the frying is terminated.

[0064] After the materials are poured into the oil pan, an infrared temperature sensor array collects the initial surface temperature of the materials in real time and transmits the data to the controller. The controller calculates the output temperature based on the initial surface temperature of the materials. Based on the output temperature and the real-time surface temperature of the materials, the controller uses a first PID control algorithm to control the power output of the heater, causing the material temperature to rise until the preset temperature is reached. During the frying process, a sound sensor simultaneously collects the sound information and transmits the signal to the controller. The controller performs a Fourier transform on the sound information, calculates the energy percentage of a preset frequency band (corresponding to high-frequency water vapor popping sounds), and monitors the water evaporation intensity in real time. The controller simultaneously compares three conditions; when all three are met, it automatically transitions from stage one to stage two.

[0065] Temperature conditions: The real-time surface temperature of the material reaches the preset value;

[0066] Sound energy conditions: The energy proportion of the preset frequency band is less than the preset value (high-frequency crackling sounds are significantly reduced);

[0067] Energy change rate condition: The absolute value of the energy percentage change rate of the preset frequency band is ≤0.01 seconds (the sound signal tends to be stable).

[0068] Upon entering Phase Two, the NIR spectral probe continuously collects the light signals from the materials in the oil pan and transmits them to the spectrometer. The spectrometer analyzes and processes the light signals to generate corresponding spectral information, which is then fed back to the controller in real time. The controller inputs the received spectral information into a pre-established NIR spectral model and uses model inversion calculations to obtain the real-time moisture content and color value of the materials. Based on the real-time moisture content data, the controller calculates the dynamic peak temperature of Phase Two as the core temperature control target to ensure that the materials are within the optimal temperature range for the Maillard reaction and caramelization reaction. Using the dynamic peak temperature as the target value, the controller compares the real-time surface temperature of the materials collected by the infrared temperature probe array and calculates the deviation between the two. Through a second PID control algorithm, the power output of the heater is dynamically adjusted to keep the real-time surface temperature of the materials as close as possible to the dynamic peak temperature, thereby improving the formation of flavor compounds and reducing the generation of harmful byproducts.

[0069] Based on real-time collected parameters, the controller calculates a predicted color value and compares it with a preset target color threshold. When the predicted color value reaches or exceeds the threshold, the controller immediately determines that the cooking is complete and triggers a termination command.

[0070] The controller sends a shutdown signal to the heater to stop heat output;

[0071] If the system is equipped with an automatic stirring mechanism, the stirring action will stop synchronously.

[0072] The operator or linked equipment is prompted to perform the unloading operation to complete the stir-frying process.

[0073] This embodiment uses an infrared temperature probe array to collect the surface temperature of the material in real time, uses a first PID control algorithm to dynamically adjust the heater power, uses a sound probe to collect sound signals, and uses Fourier transform to analyze the changes in high-frequency noise (representing the sound of water vapor bursting) as an auxiliary criterion for the end of a stage. Combining the real-time surface temperature of the material and the spectral characteristics of the sound signal as dual core criteria, it replaces the subjective judgment of human smelling and listening, reduces the problems of undercooked or overcooked materials caused by existing automated equipment relying solely on temperature or time judgment, and improves the quality consistency under large-scale production. Moisture content is a core factor affecting the roasting process (such as dehydration rate and Maillard reaction intensity), while color is a direct reflection of product flavor (caramelization and Maillard reaction products). This embodiment uses an NIR spectral probe to collect material data online and retrieve moisture content and color values ​​in real time, quantifying the degree of browning and reaction progress, and achieving real-time monitoring of Maillard and caramelization reactions. Based on the initial moisture content of the material, the moisture content at the start of stage two, and the type of material, this embodiment dynamically calculates the peak temperature of stage two, maintaining the material temperature within the optimal reaction range, maximizing the generation of nut aroma and color, and reducing the generation of harmful byproducts such as acrylamide. The color value change rate calculation correlates temperature, moisture content, and the activation energy of the Maillard reaction, allowing the system to predict the reaction progress based on the real-time state of the material, avoiding uncontrolled reaction rates due to temperature / moisture fluctuations. By using real-time color values, moisture content, and temperature to predict future color values, roasting is terminated when the predicted color value reaches the preset optimal flavor threshold range, improving the problem of insufficient flavor due to premature termination or scorching due to delayed termination.

[0074] For example, the specific method for calculating the output temperature based on the initial surface temperature at the beginning of the stage is as follows:

[0075] ;

[0076] in, T lt for t It continuously outputs the temperature in degrees Celsius. T 0 The initial surface temperature of the material at the start of the stage, in degrees Celsius; R The heating rate is expressed in degrees Celsius per second. t The cooking time is in seconds.

[0077] Heating the oil pan using a gradient heating method can reduce the problems of materials "exploding" and losing nutrients due to excessively rapid heating, or materials not dehydrating sufficiently and failing to generate enough flavor due to excessively slow heating.

[0078] For example, the specific method for calculating the energy proportion of the preset frequency band is as follows:

[0079] ;

[0080] in, S t for t At any given time, the energy percentage of the preset frequency band; a The lowest frequency of the preset frequency band, in Hertz; b The highest frequency of the preset frequency band, in Hertz; c The highest frequency in sound information, measured in Hertz; PSD(f) The power spectral density of the signal; df This refers to the frequency resolution.

[0081] For example, the specific method for calculating the dynamic peak temperature based on the material moisture content at the beginning of stage two and the material moisture content at the beginning of stage one is as follows:

[0082] ;

[0083] in, T max This represents the peak temperature of Phase Two, expressed in degrees Celsius. T 1 represents the preset peak temperature for different types of nuts, in degrees Celsius; K mc This is the moisture compensation coefficient, expressed as a percentage of water content per degree Celsius. M 1 represents the moisture content of the material at the start of Phase Two; M 0 represents the moisture content of the material at the beginning of the stage.

[0084] For example, the specific method for calculating and predicting the color value based on the material's real-time color value, real-time moisture content, and real-time surface temperature is as follows:

[0085] ;

[0086] in, b 1 represents the predicted color value; b 0 represents the real-time color value of the material; The rate of change of color values, in seconds; ∆t The time step is predicted in seconds.

[0087] For example, the rate of change of the color value is calculated as follows:

[0088] ;

[0089] in, AThe exponential factor is expressed in seconds. Ea The apparent activation energy of the Maillard reaction, expressed in joules per mole; r The ideal gas coefficient is expressed in joules per mole per Kelvin. M t for t Real-time moisture content of the material; T t for t Real-time surface temperature of the material, in Kelvin; n The reaction order is given. The pre-exponential factor, activation energy, and reaction order are obtained through calibration and fitting using historical roasting data of the material.

[0090] Example 2:

[0091] This embodiment provides a control method for the product roasting system described in Embodiment 1, including:

[0092] S100: After the material is put into the oil pot, it enters the first stage. At this time, the controller acquires the initial surface temperature at the beginning of the first stage, the real-time surface temperature of the material during the frying process, and the sound information during the frying process.

[0093] Specifically, before the ingredients are added to the oil pan, a preset amount of cooking oil is poured into the inner layer of the pan. The controller sends a start command to the heater, which heats the oil through the bottom of the jacket until it reaches the preset preheating temperature. Then, the prepared ingredients are poured into the inner layer of the pan, at which point the frying process enters its first stage. The controller then lowers and closes the lid to prevent excessive heat loss and splashing. The second power unit is then activated, driving the stirrer to agitate the ingredients in the pan. After the ingredients are poured into the pan, an infrared temperature sensor array collects the initial surface temperature of the ingredients in real time and transmits the data to the controller.

[0094] S200: Calculate the output temperature based on the initial surface temperature at the beginning of the stage, and obtain the output temperature calculation result;

[0095] Specifically, the controller acquires the initial surface temperature of the material, calculates the output temperature based on the initial surface temperature of the material, and calculates the output temperature according to the real-time surface temperature of the material. The method of calculating the output temperature can be referred to the specific method of output temperature calculation described in Example 1.

[0096] S300: Based on the deviation between the output temperature calculation result and the real-time surface temperature of the material, the output power of the heater is adjusted in real time through the first PID control algorithm;

[0097] Specifically, the first PID control algorithm is a commonly used process control algorithm, and its core principle is based on proportional (PID) control.P ),integral( I） ,differential( D Three steps are used to coordinately correct system deviations:

[0098] Proportional link ( P It provides an immediate response to the current deviation, generating a control effect proportional to the magnitude of the deviation, and is used to quickly reduce the deviation.

[0099] Points system ( I The historical deviations are accumulated to eliminate the steady-state error of the system and achieve error-free tracking of the set value.

[0100] Differential element ( D Adjusting ahead of the deviation based on its changing trend helps to suppress system overshoot and improve response speed and stability.

[0101] This algorithm dynamically adjusts the parameters of the above three stages ( K p , K i , K d The optimal control quantity (i.e. heater power) is calculated by comprehensively analyzing the data, thereby achieving rapid and stable automatic control of the material temperature.

[0102] S400: Perform a Fourier transform on the sound information to obtain its power spectral density, and calculate the energy proportion of the preset frequency band;

[0103] Specifically, during the frying process, the sound probe synchronously collects sound signals from inside the oil pan (including acoustic characteristics such as boiling, frying, and bubble bursting) and transmits the sound signals to the controller. The controller first preprocesses the collected sound signals (time-domain signals) (e.g., filtering and noise reduction), and then converts them into frequency-domain signals through a Fast Fourier Transform (FFT) to obtain the power spectral density (PSD), which represents the energy distribution of different frequency components. Then, it calculates the energy proportion of a preset frequency band to quantify the frying state: a high proportion indicates vigorous boiling, and a low proportion indicates reduced moisture or near completion of frying. In this embodiment, the calculation method of the energy proportion of the preset frequency band can refer to the specific method for calculating the energy proportion of the preset frequency band described in Embodiment 1.

[0104] S500: When the real-time surface temperature of the material reaches the preset value, the energy ratio of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy ratio of the preset frequency band is less than or equal to 0.01 seconds, enter stage two.

[0105] Specifically, during the stir-frying process, the controller will simultaneously determine whether to enter the second stage of control based on three conditions:

[0106] Real-time surface temperature reaches preset value: For example, when the material surface temperature reaches 180°C, it indicates that heating is complete.

[0107] The energy percentage of the preset frequency band is less than the preset value: for example, if the sound energy percentage is less than 5%, it means that the boiling sound is weakening and the moisture content of the material is beginning to decrease.

[0108] The absolute value of the rate of change of energy percentage is less than or equal to 0.01 seconds: Calculate the rate of change of energy percentage over time to ensure stable state (slow change) and avoid false triggering due to instantaneous fluctuations.

[0109] The controller switches to phase two only when all conditions are met, thus improving the reliability of phase switching.

[0110] S600: Acquire spectral information, substitute the spectral information into a pre-established NIR spectral model, and determine the real-time moisture content and real-time color value of the material.

[0111] Specifically, in phase two, the controller uses an NIR spectral probe to illuminate the material and receives the reflected or transmitted light signals, converting them into electrical signals that are transmitted to the spectrometer. The spectrometer then uses these electrical signals to generate spectral information. NIR spectroscopy is sensitive to moisture and pigments. After preprocessing (such as baseline correction and normalization), the acquired spectral data is fed into a pre-trained NIR spectral model. This model maps spectral features to moisture content and color values.

[0112] S700: Calculate the dynamic peak temperature based on the material moisture content at the beginning of stage two and the material moisture content at the beginning of stage one.

[0113] Specifically, the dynamic peak temperature is dynamically adjusted based on changes in moisture content. The controller uses the moisture content at the start of Phase Two obtained by S600 and the initial moisture content of the material when it is added, recorded by S100, to calculate an optimal peak temperature. For details on how the dynamic peak temperature is calculated, please refer to the specific method for calculating dynamic peak temperature.

[0114] S800: Taking the dynamic peak temperature as the control target, the power output of the heater is adjusted by the second PID control algorithm according to the deviation between the dynamic peak temperature and the real-time surface temperature of the material;

[0115] Specifically, the controller uses the dynamic peak temperature calculated by the S700 as the new target and adjusts the heater power using a second PID control algorithm. The second PID algorithm has different parameters than the first PID algorithm to meet the fine-tuning temperature control requirements of stage two. The algorithm compares the real-time surface temperature (from the infrared sensor) with the dynamic peak temperature, calculates the deviation, and outputs a power adjustment signal. For example, if the temperature is below the peak, the PID will slowly increase the power; if the temperature is close to the peak, the PID will maintain a stable power to avoid fluctuations.

[0116] S900: The predicted color value is calculated based on the real-time color value, the real-time moisture content, and the real-time surface temperature;

[0117] Specifically, even when the temperature is stable, the color and moisture content of the material continue to change. The controller uses real-time data as input and calculates the color value at future time points using a predictive model. The predicted value is used to determine the cooking endpoint in advance and avoid overcooking. In this embodiment, the method for calculating the predicted color value can refer to the specific method for calculating the predicted color value described in Embodiment 1.

[0118] S1000: The stir-frying process is terminated based on the predicted color value. When the predicted color value reaches or exceeds the preset target color threshold, the stir-frying process is determined to be complete and terminated.

[0119] Specifically, the controller continuously monitors the predicted color value calculated by the S900 and compares it with a preset target color threshold. When the predicted value reaches or exceeds this threshold, the controller determines that the cooking is complete and immediately stops heating (e.g., by turning off the heater or issuing an alarm).

[0120] Example 3:

[0121] This embodiment provides a stir-frying device based on Embodiment 1, such as... Figure 2 As shown, the frying equipment includes:

[0122] 100 wok modules, such as Figure 3 , Figure 4 As shown, the wok module includes an oil pan 110, which has an inner layer 111 and an outer layer 112. The outer layer wraps around the outer side of the inner layer to form a sandwich layer, and a heater 140 is provided at the bottom of the sandwich layer.

[0123] Lifting and stirring mechanism 200, such as Figure 5As shown, the lifting and stirring mechanism includes a first power unit 220, a second power unit 240, a pot lid 250, and a stirrer 260. The pot lid is set on the top of the oil pot and is driven to move vertically up and down by the first power unit. The second power unit is installed on the upper surface of the pot lid. The stirrer is rotatably installed on the lower surface of the pot lid and is connected to the second power unit. The stirrer is driven to rotate around its own circumference by the second power unit.

[0124] In this embodiment, as Figure 7 As shown, multiple infrared temperature probes are arranged at predetermined positions inside the pot lid, forming an infrared temperature probe array. The sound probe is located inside the pot lid, as shown below. Figure 6 As shown, the NIR spectral probe is positioned at the top of the stirrer.

[0125] Specifically, the wok module may further include a frame 120, which is fixed to the ground. The wok is mounted on the frame and can rotate relative to the frame. A power mechanism may also be provided on the frame to drive the wok to rotate. The power mechanism may be selected from various options. Figure 2 The handwheel 130 shown can also be replaced by a power device such as a motor, rotary cylinder, or rotary hydraulic cylinder that can provide power for the oil pan to tilt. The power device can be connected to the tilting shaft of the oil pan through a worm gear transmission mechanism 150. In addition, the lifting and stirring mechanism can also include a stand 210, which is fixed on the ground. A slide block 230 is slidably installed on the stand. The slide block is driven to move vertically by a first power device. A second power device is installed on the slide block. The first power device can be a motor and can be connected to the slide block through a lead screw, sprocket transmission mechanism, or belt pulley transmission mechanism to achieve linear movement of the slide block. The first power device can also be a cylinder, electric cylinder, or hydraulic cylinder that directly drives the linear movement of the slide block. The second power device can be a motor.

[0126] In this embodiment, the stirrer may include a hollow stirring shaft. The NIR spectral probe is fixedly mounted in the internal cavity of the hollow stirring shaft via a high-temperature resistant, shock-absorbing bushing. An optical through-hole is formed on the side wall or bottom of the hollow stirring shaft, directly opposite the measurement window of the NIR spectral probe. A sapphire glass lens is sealed and embedded in the optical through-hole by high-temperature brazing or a sealing ring, forming the measurement window of the NIR spectral probe. A multi-channel rotary joint is provided at the top of the hollow stirring shaft. The static side of the multi-channel rotary joint is connected to an external pipeline, while the rotating side communicates with the interior of the hollow stirring shaft.

[0127] When using the product frying system described in this embodiment, the first power device is activated, causing the lid to rise vertically and expose the opening of the oil pan. After pouring a preset amount of cooking oil into the inner layer of the oil pan, the first power device is activated again, causing the lid to fall to the top of the oil pan and close, reducing heat loss. The controller sends a start command to the heater, which heats the cooking oil through the bottom of the jacket until the cooking oil reaches the preset preheating temperature. The first power device is activated again, causing the lid to rise again. After pouring the prepared materials to be fried into the inner layer of the oil pan, the lid is immediately controlled to fall and close to prevent excessive heat loss and material splashing. Then, the second power device is activated, causing the stirrer to rotate and agitate the materials in the oil pan.

[0128] Once stage two is complete, the controller sends a stop command to the heater and simultaneously stops the second power unit, causing the stirrer to stop rotating. The first power unit is then activated, causing the lid to rise vertically. Through the power mechanism of the wok module (such as a handwheel or motor), the wok rotates around the tilting shaft, pouring the cooked material (chili oil) into a pre-set collection container. After the material is poured out, the wok is tilted back to its original position, ready for the next batch of cooking.

[0129] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A stir-frying control system, characterized in that, include: An infrared temperature probe is provided, and multiple infrared temperature probes are provided to form an infrared temperature probe array, which is used to collect the real-time surface temperature of the material and the initial surface temperature at the beginning of the stage. A sound probe is used to collect sound information during the stir-frying process; NIR spectral probe, which collects light signals through NIR spectral probe; A spectrometer, which is connected to an NIR spectral probe to acquire light signals and establish an NIR spectral model based on the spectral information; After the material is put into the oil pot, the controller enters the first stage. At this time, the controller obtains the initial surface temperature at the beginning of the first stage, calculates the output temperature based on the initial surface temperature at the beginning of the first stage, obtains the output temperature calculation result, and adjusts the output power of the heater in real time through the first PID control algorithm based on the deviation between the output temperature calculation result and the real-time surface temperature of the material. Acquire sound information, perform Fourier transform on the sound information, calculate the energy ratio of a preset frequency band. When the real-time surface temperature of the material reaches a preset value, the energy ratio of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy ratio of the preset frequency band is less than or equal to 0.01 seconds, enter stage two. The controller acquires spectral information, substitutes the spectral information into a pre-established NIR spectral model to determine the real-time moisture content and real-time color value of the material. The controller calculates the dynamic peak temperature based on the moisture content of the material at the beginning of stage two and the moisture content of the material at the beginning of stage one. Using the dynamic peak temperature as the control target, the power output of the heater is adjusted through a second PID control algorithm based on the deviation between the dynamic peak temperature and the real-time surface temperature of the material. The predicted color value is calculated based on the real-time color value, real-time moisture content, and real-time surface temperature of the material. The frying termination judgment is made based on the predicted color value. When the predicted color value reaches or exceeds the preset target color threshold, the frying is determined to be complete and the frying is terminated. The specific method for calculating the dynamic peak temperature based on the material moisture content at the beginning of stage two and the material moisture content at the beginning of stage one is as follows: ； in, T max This represents the peak temperature of Phase Two, expressed in degrees Celsius. T 1 represents the preset peak temperature for different types of nuts, in degrees Celsius; K mc This is the moisture compensation coefficient, expressed as a percentage of water content per degree Celsius. M 1 represents the moisture content of the material at the start of Phase Two; M 0 represents the moisture content of the material at the beginning of the stage.

2. The stir-frying control system according to claim 1, characterized in that, The specific method for calculating the output temperature based on the initial surface temperature at the beginning of the stage is as follows: ； in, T lt for t It continuously outputs the temperature in degrees Celsius. T 0 The initial surface temperature of the material at the start of the stage, in degrees Celsius; R The heating rate is expressed in degrees Celsius per second. t The cooking time is in seconds.

3. The stir-frying control system according to claim 1, characterized in that, The specific method for calculating the energy proportion of the preset frequency band is as follows: ； in, S t for t At any given time, the energy percentage of the preset frequency band; a The lowest frequency of the preset frequency band, in Hertz; b The highest frequency of the preset frequency band, in Hertz; c The highest frequency in sound information, measured in Hertz; PSD(f) The power spectral density of the signal; df This refers to the frequency resolution.

4. The stir-frying control system according to claim 1, characterized in that, The specific method for calculating and predicting the color value based on the material's real-time color value, real-time moisture content, and real-time surface temperature is as follows: ； in, b 1 represents the predicted color value; b 0 represents the real-time color value of the material; The rate of change of color values, in seconds; ∆t The time step is predicted in seconds.

5. A stir-frying control system according to claim 4, characterized in that, The rate of change of the color value is calculated as follows: ； in, A The exponential factor is expressed in seconds. Ea The apparent activation energy of the Maillard reaction, expressed in joules per mole; r The ideal gas coefficient is expressed in joules per mole per Kelvin. M t for t Real-time moisture content of the material; T t for t Real-time surface temperature of the material, in Kelvin; n denoted as the reaction order.

6. A method for controlling the stir-frying process, characterized in that, The control method is executed using a stir-frying control system as described in any one of claims 1 to 5, comprising: After the material is put into the oil pot, it enters the first stage. At this time, the controller acquires the initial surface temperature at the beginning of the first stage, the real-time surface temperature of the material during the frying process, and the sound information during the frying process. The output temperature is calculated based on the initial surface temperature at the beginning of the stage, and the output temperature calculation result is obtained. Based on the deviation between the calculated output temperature and the real-time surface temperature of the material, the output power of the heater is adjusted in real time using the first PID control algorithm. The power spectral density of the sound information is obtained by performing a Fourier transform, and the energy proportion of the preset frequency band is calculated. When the real-time surface temperature of the material reaches the preset value, the energy proportion of the preset frequency band is less than the preset value, and the absolute value of the rate of change of the energy proportion of the preset frequency band is less than or equal to 0.01 seconds, the process enters stage two. Acquire spectral information, substitute the spectral information into a pre-established NIR spectral model, and determine the real-time moisture content and real-time color value of the material. Dynamic peak temperature is calculated based on the material moisture content at the beginning of Phase 2 and the material moisture content at the beginning of Phase 1. With dynamic peak temperature as the control target, the power output of the heater is adjusted by a second PID control algorithm based on the deviation between the dynamic peak temperature and the real-time surface temperature of the material. The predicted color value is calculated based on the real-time color value, the real-time moisture content, and the real-time surface temperature. The frying process is terminated based on the predicted color value. When the predicted color value reaches or exceeds the preset target color threshold, the frying process is considered complete and terminated.

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