Kitchen intelligent processing collaborative work control system

Abstract

The application relates to the technical field of cooperative control, and particularly discloses a kitchen intelligent processing cooperative work control system. The system comprises: a reference extraction module which determines a transmission calibration sequence in a wind-disturb-free environment; a disturbance judgment module which judges whether a phase lock loss signal is triggered, and then identifies a space interference source to obtain a shear disturbance event; a thermal loss evaluation module which controls a cooking utensil to perform heat compensation at a system level; a heat compensation module which tracks a temperature recovery curve after heat compensation to verify heat recovery efficiency, and converts a control instruction into a compensation gear when the efficiency meets the standard; and a state reconstruction module which is used for performing efficiency regression analysis, and identifies a drift state of a physical boundary based on an analysis result, and adjusts historical calibration. The application is beneficial to shear airflow disturbance in a kitchen environment, and realizes dynamic adaptive control of the system through experience accumulation and efficiency regression analysis.

Description

Technical Field

[0001] This invention relates to the field of collaborative control technology, specifically to a smart kitchen processing collaborative work control system. Background Technology

[0002] With the increasing popularity of open-plan kitchens in modern homes, the cooking process is easily disrupted by complex external airflows (such as crosswinds caused by the opening and closing of doors and windows). When encountering external crosswinds, the rising fumes are instantly dispersed, causing a sharp drop in the concentration detected by the range hood's sensors.

[0003] When a sudden drop in concentration occurs, traditional systems often misinterpret it as a decrease in cooking intensity, thus incorrectly reducing the exhaust fan speed. Simultaneously, the strong airflow rapidly strips away the layer of hot airflow covering the bottom of the pot, causing significant heat loss and a sharp drop in the pot's temperature, disrupting the cooking process. Current technology cannot identify this false concentration drop caused by external turbulence and lacks a feedforward heat compensation mechanism for heat loss at the bottom of the pot.

[0004] Therefore, the present invention provides a kitchen intelligent processing and collaborative work control system. Summary of the Invention

[0005] The purpose of this invention is to provide a smart kitchen processing and collaborative work control system to solve the aforementioned background problems.

[0006] The objective of this invention can be achieved through the following technical solutions: A smart kitchen processing and collaborative control system includes the following modules: The disturbance determination module is used to read the transmission calibration sequence, monitor the dynamic phase drift of the real-time concentration sequence and the fire sequence, compare the dynamic phase drift with the transmission spatiotemporal calibration sequence, and determine whether a phase lock-out signal is triggered; based on the phase lock-out signal, the characteristics of the interference source in the space are identified to obtain the shear disturbance event; Heat loss assessment module: used to extract the capture time and duration of shear turbulence events, analyze the heat dissipation gradient of the pot bottom and generate feedforward heat compensation equivalent; control the stove to perform heat compensation based on the feedforward heat compensation equivalent; Thermal compensation module: used to track the temperature recovery curve after thermal compensation and verify whether the thermal recovery efficiency of the current compensation action meets the standard; if the efficiency meets the standard, it organizes the turbulence parameters and compensation commands and establishes an effective control sample; based on the effective control sample, it converts the control commands into compensation levels; State Reconstruction Module: Used to continuously monitor the execution decay rate of compensation levels, perform performance regression analysis of historical experience samples based on the execution decay rate, identify the drift state of physical boundaries based on the analysis results, and adjust the historical calibration.

[0007] Furthermore, the method for reading the transmission calibration sequence is as follows: Simultaneously collect the firepower fluctuation sequence from the stove side and the oil fume concentration sequence from the range hood side, and perform state consistency analysis on the two sets of sequences to obtain steady-state correlation characteristics; based on the steady-state correlation characteristics, determine the transmission calibration sequence for cooking in a windless environment.

[0008] Furthermore, the state consistency analysis is performed as follows: Extract the step abrupt change point in the firepower fluctuation sequence on the time axis as the initiation control peak; Simultaneously, a translation search is performed on the oil fume concentration sequence to identify the concentration response peak on the time axis; Calculate the time difference between the timestamp of the initiation peak and the timestamp of the concentration response peak, and use the time difference as the one-way physical transmission delay. During a continuous initial cooking period without significant environmental interference, multiple sudden changes in fire intensity were induced, and the corresponding multiple unidirectional physical transmission delays were extracted. The extracted unidirectional physical transmission delays are statistically averaged to obtain the steady-state delay constant, which is then used as a steady-state correlation feature.

[0009] Furthermore, the method for identifying the characteristics of the interference source is as follows: Based on the comparison results of dynamic phase drift and transmission spatiotemporal calibration sequence, the transmission deviation margin is extracted; Analyze the absolute amplitude offset of the transmission deviation margin to determine whether the current physical transmission phase of the system is in a disturbed state. If it is, generate a transient phase loss signal. The causes of concentration decrease are identified by using transient phase-locked signals to determine the characteristics of the disturbance source, and the disturbance events are classified based on the identification results; The classification results include: shear disturbance events and routine cooking interventions.

[0010] Furthermore, the method for extracting the transmission deviation margin is as follows: Extract the moment of the heat step within the current cooking cycle as the zero point of time, and retrieve the corresponding expected concentration rise curve in the transmission spatiotemporal calibration sequence as a reference benchmark; The real-time concentration sequence fed back by the oil fume concentration sensor is acquired synchronously, and the starting moment of the first effective concentration increase in the real-time concentration sequence is found by using a time window sliding comparison method, which is defined as the real-time response time point. The phase drift value is obtained by calculating the time deviation between the real-time response time and the theoretical starting time in the expected concentration rise curve; The dimensionless deviation margin coefficient is obtained by dividing the acquired phase drift value by the steady-state delay constant in the transmission spatiotemporal calibration sequence.

[0011] Furthermore, the heat compensation is performed as follows: At the moment the shear turbulence event is detected, a takeover command is sent to the underlying control unit of the smart range hood to freeze the range hood status and cut off the normal linkage feedback loop between the oil fume concentration sensor and the motor speed. The generated feedforward thermal compensation equivalent is subjected to time-limited allocation processing. Based on the result of the amplitude limiting and allocation processing, a firepower control command is issued to the smart stove to drive the smart stove to execute incremental firepower output; When the actual cumulative heat release from the incremental firepower output reaches the feedforward heat compensation equivalent, the control of the smart range hood is released, and the output power of the smart stove is controlled to drop back to the initial heating load to achieve heat compensation.

[0012] Furthermore, the feedforward thermal compensation equivalent is generated as follows: The phase loss signal that triggers the shear disturbance event is continuously tracked until the phase loss signal disappears and the phase of the concentration sequence and the fire sequence are rematched. The total duration of the loss state is defined as the duration period. Obtain the initial heating load of the smart cooktop at the capture time; Combining the initial heating load with the current kitchen ambient temperature, the instantaneous temperature drop rate of the pot bottom during the process of dissipating heat to the surrounding cold air is evaluated and defined as the dissipation gradient. The superposition quantization calculation of the dissipation gradient over time during the continuous period is performed to obtain the equivalent temperature drop at the bottom of the pot during the shear turbulence. The lost temperature drop equivalent is converted into the feedforward heat compensation equivalent required by the smart cooktop.

[0013] Furthermore, the method for switching to compensation levels is as follows: After extracting all effective control samples accumulated in the local historical experience database after long-term operation for a preset period, cross-overlap comparison is performed on all effective control samples, and typical disturbance control intersections are established based on the comparison results. Based on the intersection of typical disturbance control, the corresponding compensation command is extracted as a fire compensation parameter and discretized. The discretized fire compensation parameters are directly associated with the expected environmental feature intervals to construct a condition-triggered state machine mapping relationship. Based on the state machine mapping relationship, several compensation levels are established.

[0014] Furthermore, the method for adjusting historical calibration is as follows: Extract the real-time operating current fluctuation value of the intelligent range hood fan motor under the output constant speed command, as well as the average ambient temperature of the current season; The real-time operating current fluctuation value is compared with the reference load current under the initial interference-free calibration state. If the difference continuously exceeds the fault tolerance range and the attenuation rate deviates from the expectation, it is determined that an irreversible physical drift has occurred. If an irreversible physical drift occurs, the system generates a global reconstruction instruction to adjust the target data subset and the transmission spatiotemporal calibration sequence.

[0015] Furthermore, the execution decay rate is obtained as follows: The frequency of failure compensation events where the thermal recovery efficiency fails to meet the standard is counted within a preset time window, and the execution attenuation rate is calculated.

[0016] The beneficial effects of this invention are as follows: 1. In the disturbance determination stage, the phase drift value is calculated by extracting the moment of the fire step and retrieving the expected concentration rise curve, combined with the start time of the effective concentration increase in real time. This value is then compared with the steady-state delay constant to generate a transient phase loss signal. By introducing phase change into disturbance identification and using whether or not this loss signal is captured to distinguish the cause of the sudden drop in concentration, it is helpful to identify shear disturbance events caused by external transverse drafts and changes in internal state caused by users routinely adding water or covering the pot. Identifying the characteristics of the interference source helps reduce the probability of system misjudgment and improves the reliability of environmental disturbance determination.

[0017] 2. During the heat loss assessment phase, the capture time and duration of shear disturbance events are recorded. The dissipation gradient is extrapolated by combining the initial heating load and ambient temperature. The dissipation gradient is then quantified over time to obtain the equivalent temperature drop, and a feedforward heat compensation equivalent is generated in reverse. By establishing a dynamic mapping relationship between heat dissipation and compensation, airflow disturbances are transformed into energy loss. The conventional linkage feedback loop of the flue gas fan is physically shut off to freeze the fan state, and the feedforward heat compensation equivalent is distributed with limited amplitude. Fire control commands are issued within a short execution window, which helps to offset the instantaneous heat loss caused by cold air intrusion and maintain the stability of the boiler's heating state.

[0018] 3. During the thermal compensation phase, the actual temperature recovery curve over time after the compensation action is tracked to verify the thermal recovery efficiency. The posterior verification mechanism of cross-domain thermal compensation facilitates the evaluation of the actual effect of a single compensation. For cases where the efficiency meets the standards, effective control samples are constructed. Then, cross-overlap comparisons of all samples are performed to establish typical disturbance control intersections. This allows the validated data to be structured into control templates, improving response agility when triggered under the same environmental conditions.

[0019] 4. During the state reconstruction phase, the system continuously extracts failure compensation events where thermal recovery performance fails to meet standards and calculates the execution attenuation rate during long-term operation. This attenuation statistics reflect the degradation characteristics of the system's operational performance. By comparing the difference between the fluctuating operating current of the intelligent range hood fan motor and the reference load current under the initial interference-free calibration state, if the difference is abnormal and the execution attenuation rate deviates from expectations, it is determined that irreversible physical drift has occurred at the fluid dynamics boundary. Generating a global reconstruction command to clear the affected data subset and forcibly waking up the reference extraction module for recalibration helps extend the effective operating range of the overall control logic. Attached Figure Description

[0020] The invention will now be further described with reference to the accompanying drawings.

[0021] Figure 1 This is a functional block diagram of a kitchen intelligent processing and collaborative work control system according to the present invention; Figure 2 This is a flowchart of the interference source characteristic identification process in this invention; Figure 3 This is a flowchart of a kitchen intelligent processing collaborative work control method according to the present invention. Detailed Implementation

[0022] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments. Example 1:

[0023] like Figure 1 As shown, a smart kitchen processing and collaborative control system includes the following modules: The benchmark extraction module is used to simultaneously collect the firepower fluctuation sequence from the cooktop side and the oil fume concentration sequence from the range hood side, perform state consistency analysis on the two sets of sequences to obtain steady-state correlation characteristics, and determine the transmission calibration sequence for cooking in a windless environment based on the steady-state correlation characteristics. The method for obtaining steady-state correlation characteristics by simultaneously collecting the firepower fluctuation sequence from the cooktop side and the oil fume concentration sequence from the range hood side, and performing state consistency analysis on the two sets of sequences is as follows: In some embodiments, a synchronization sampling command is sent to the combustion controller of the smart stove and the internal sensors of the smart range hood via the unified system clock of the kitchen central controller; Based on the synchronous sampling command, data reflecting the change in heat source intensity is collected when the smart stove adjusts the firepower, and the data is recorded and arranged in chronological order to construct a firepower fluctuation sequence; It should be noted that, depending on the smart stove, the firepower fluctuation sequence can be the opening change data of the gas proportional valve or the power output pulse data of the induction cooker. At the same time, the particulate matter concentration sensor or volatile organic compound sensor at the air inlet of the smart range hood; Using the same sampling frequency as smart stoves, the concentration values ​​of oil fume particles were obtained, and the concentration values ​​were recorded and arranged in chronological order to construct an oil fume concentration sequence that reflects the amount of oil fume generated. It is understandable that, since there is a fluid flight time in physical space from the time the stove generates oil fumes to the time the oil fumes rise upward under the action of thermal buoyancy and are captured by the range hood sensor, there is a time lag in the waveform changes of the two sets of sequences. Extract the step abrupt change point representing the instantaneous increase in firepower in the firepower fluctuation sequence on the time axis as the initiation control peak; Preferably, the step change point refers to: within a sampling interval of no more than 0.5 seconds, the opening step value of the gas proportional valve exceeds 20% of the full range opening, or the output power jump of the induction cooker exceeds 30% of the rated total power; Simultaneously, a translational search is performed in the oil fume concentration sequence to identify the concentration response peak that lags behind the initial control peak on the time axis and shows a corresponding sharp upward trend in value. Preferably, the sharp upward trend refers to the following: in the oil fume concentration sequence, starting from the timestamp corresponding to the initial control peak, within the subsequent search window of 3 to 8 seconds, the instantaneous change rate of the particulate matter concentration value remains positive, and the maximum value of its peak increases by more than 150% compared to the environmental baseline value at the beginning of the search window; Calculate the time difference between the timestamp of the initiation peak and the timestamp of the concentration response peak, and use the time difference as the one-way physical transmission delay of the oil fume airflow in the vertical space between the cooktop and the range hood air inlet. During a continuous initial cooking period without significant environmental interference, multiple sudden changes in fire intensity were induced, and the corresponding multiple unidirectional physical transmission delays were extracted. It should be noted that "no significant environmental interference" means that the ambient background light fluctuation detected by the optical sensor of the smart range hood is less than ±5%, and the ambient air flow velocity at the air inlet of the range hood is maintained below 0.2 m / s for one minute. The time difference for extraction is only driven by the vertical thermal buoyancy of the flue gas. The extracted unidirectional physical transmission delays are statistically averaged to remove extreme data caused by random minor disturbances in the hot airflow inside the kitchen, thus obtaining a steady-state delay constant characterizing the inherent time consumption of the physical rise of oil fumes between the stove and the range hood at a fixed installation distance. The steady-state delay constant is used as a steady-state correlation feature; Among them, the method for determining the transmission calibration sequence for cooking in a windless environment based on steady-state correlation characteristics is as follows: Read the current baseline firepower output level of the smart cooktop and the current baseline negative pressure level of the smart range hood; Physical data binding is performed between the baseline fire output level, the baseline ventilation negative pressure level and the steady-state phase correlation characteristics to construct the expected time axis mapping relationship from the issuance of the fire change command to the peak of the oil fume concentration under the current operating conditions of the kitchen equipment. Extract the absolute concentration amplitude baseline of the corresponding concentration response peak under windless disturbance conditions; By combining the expected time axis mapping relationship with the absolute concentration amplitude base in a spatiotemporal dimension, a feature sequence describing the evolution law of oil fume under normal cooking conditions is constructed, which serves as the transmission spatiotemporal calibration sequence.

[0024] The disturbance determination module is used to monitor the dynamic phase drift of the real-time concentration sequence and the fire sequence, compare the dynamic phase drift with the transmission spatiotemporal calibration sequence, and determine whether a phase loss signal is triggered; based on the phase loss signal, the characteristics of the interference source in the space are identified to obtain the shear disturbance event; Among them, the dynamic phase drift of the real-time concentration sequence and the fire sequence is monitored, and the dynamic phase drift is compared with the transmission spatiotemporal calibration sequence in the following way: The system extracts the moment of the fire intensity step within the current cooking cycle in real time and uses this as the zero point of time to retrieve the corresponding expected concentration rise curve in the transmission spatiotemporal calibration sequence as a reference benchmark. The real-time concentration sequence fed back by the oil fume concentration sensor is acquired synchronously, and the starting moment of the first effective concentration increase in the real-time concentration sequence is found by using a time window sliding comparison method, which is defined as the real-time response time point. Preferably, the effective concentration increase refers to: the real-time concentration value sequence maintains a growth rate of more than 10% in each of the three consecutive sampling periods, and the final cumulative concentration value reaches more than twice the environmental background value. The phase drift value is obtained by calculating the time deviation between the real-time response time and the theoretical starting time in the expected concentration rise curve; The obtained phase drift value is divided by the steady-state delay constant in the transmission spatiotemporal calibration sequence to obtain the dimensionless deviation margin coefficient. The method for determining whether a phase unlock signal has been triggered, and for identifying the spatial interference source characteristics based on the phase unlock signal to obtain the shear disturbance event, is as follows: S201. Analyze the absolute amplitude offset of the transmission deviation margin to determine whether the current physical transmission phase of the system is in a disturbed state. If it is, generate a transient phase loss signal. Preferably, the method for determining that the state is under disturbance is as follows: if the transmission deviation margin coefficient continues to exceed 50% and the current state does not recover to the normal calibration range within 2 consecutive seconds, a transient phase loss signal is generated. The transient phase-lock signal can be used to distinguish between the minute time fluctuations caused by the natural pulsation of hot airflow and the changes in the physical transmission path caused by the intrusion of strong external airflow. S202. Use transient phase-locked signals to identify the characteristics of interference sources that cause concentration decrease, and classify disturbance events based on the identification results; Preferred, such as Figure 2 As shown, the method for identifying the characteristics of interference sources is as follows: if the real-time monitoring shows a sudden drop in the concentration of oil fumes, but the system does not capture the transient phase lock-out signal, that is, the phase relationship between the real-time response time and the fire step time still conforms to the preset range of the transmission spatiotemporal calibration sequence, then it is determined that the sudden drop in concentration is caused by the user adding cold water to the pot or covering a large area of ​​food, which is determined to be a normal cooking intervention event. If the system detects a transient phase lock-out signal at the same time as the oil fume concentration drops sharply, it indicates that the oil fume airflow has not only decreased in quantity, but also experienced a break or unexpected delay in the temporal pattern of spatial transmission, which does not conform to the preset range of the transmission spatiotemporal calibration sequence. Therefore, it is determined that the sudden drop in concentration is caused by the external transverse draft blowing away the smoke cloud, and conventional cooking intervention is excluded. It is determined to be a shear turbulence event. Example 2:

[0025] Please see Figure 1 As shown, a smart kitchen processing and collaborative control system includes the following modules: Heat loss assessment module: used to extract the capture time and duration of shear turbulence events, analyze the heat dissipation gradient of the pot bottom and generate feedforward heat compensation equivalent; control the stove to perform system-level heat compensation based on the feedforward heat compensation equivalent; The process of extracting the capture time and duration of the shear disturbance event, analyzing the heat dissipation gradient at the bottom of the pot, and generating the feedforward heat compensation equivalent is as follows: Preferably, when the system determines a shear turbulence event, it records the absolute timestamp of the event as the capture time point; The phase loss signal that triggers the shear disturbance event is continuously tracked until the phase loss signal disappears and the phase of the concentration sequence and the fire sequence are rematched. The total duration of the loss state is defined as the duration period. Obtain the initial heating load of the smart cooktop at the capture time; Combining the initial heating load with the current kitchen ambient temperature, the instantaneous temperature drop rate of the pot bottom during the process of dissipating heat to the surrounding cold air is evaluated and defined as the dissipation gradient. It should be noted that the larger the initial heating load and the lower the ambient temperature, the steeper the deduced dissipation gradient, indicating that the heat loss is faster. The superposition quantization operation is performed on the dissipation gradient over time during the continuous period to obtain the equivalent temperature drop at the bottom of the pot during the shear disturbance. Preferably, the superposition quantization method is as follows: the dissipation gradient is integrated over time during the continuous period to obtain the equivalent temperature drop of the apparent loss of the bottom of the pot during the shear disturbance; combined with the reference heat capacity coefficient corresponding to the current stove type stored in the system, the equivalent temperature drop is converted into the additional fuel supply or additional power consumption required by the smart stove to generate the feedforward heat compensation equivalent. The lost temperature drop equivalent is converted into the additional fuel supply or additional power consumption required by the smart cooktop, generating a feedforward heat compensation equivalent. The method for system-level heat compensation based on feedforward heat compensation equivalent control of the stove is as follows: S301. At the moment the shear turbulence event is determined, a takeover command is sent to the underlying control unit of the smart range hood to freeze the range hood status and physically cut off the normal linkage feedback loop between the oil fume concentration sensor and the motor speed. It should be noted that the conventional linkage feedback loop works by locking the current motor operating condition of the smart range hood and forcing the fan speed to freeze at the working state before the turbulence occurred, so as to maintain the current negative pressure state of exhaust smoke and prevent the complete loss of control over the airflow due to the weakening of the airflow caused by the sudden drop in concentration. S302. While freezing the smoke machine, the generated feedforward thermal compensation equivalent is subjected to time-limited allocation processing. Preferably, the method for limiting the distribution is as follows: keeping the total energy to be compensated represented by the feedforward thermal compensation equivalent unchanged, calculating the shortest compensation time under the current maximum allowable transient output power of the smart stove; using this shortest compensation time as the execution window, issuing a full-load firepower control command to the smart stove in exchange for extremely high instantaneous output power; if the calculated instantaneous output power exceeds the rated maximum output power of the smart stove, then clamping the output power to the rated maximum output power, and extending the duration of the extremely short execution window proportionally according to the law of conservation of energy; Based on the results of the amplitude-limited allocation processing, instantaneous firepower control commands exceeding the current conventional cooking levels are issued to the smart stove. Based on instantaneous fire control commands, the combustion valve or electromagnetic coil of the smart stove is driven to execute incremental fire output; When the actual cumulative heat release of the incremental firepower output reaches the feedforward heat compensation equivalent, the control of the smart range hood is released, and the output power of the smart stove is controlled to smoothly drop back to the initial heating load, so as to achieve cross-domain heat compensation. Thermal compensation module: used to track the temperature recovery curve after thermal compensation and verify whether the thermal recovery efficiency of the current compensation action meets the standard; if the efficiency meets the standard, it organizes the turbulence parameters and compensation commands and establishes an effective control sample; based on the effective control sample, it converts the control commands into compensation levels; The method for tracking the temperature recovery curve after heat compensation and verifying whether the heat recovery efficiency of the current compensation action meets the standard is as follows: Preferably, the system simultaneously starts a time-dimensional temperature tracking window at the end of the cross-domain heat compensation action; The real-time temperature values ​​of the bottom of the pot are collected at high frequency and continuously by the contact temperature sensor or infrared temperature array at the bottom of the smart stove, and the actual temperature rise curve over time is plotted. Calculate the time span taken for the actual recovery curve to reach the initial set temperature before the turbulence occurred, as well as the maximum overshoot temperature difference during the recovery process, and generate the thermal recovery efficiency that reflects the accuracy of this compensation action; If the calculated heat recovery performance meets the set valid verification criteria; Preferably, the effective verification standard refers to: the actual recovery curve recovers to the range of ±2℃ of the initial set temperature within a time span of no more than 15 seconds, and there is no secondary temperature drop or serious temperature overshoot that would damage the cooking temperature of the dish; The method for organizing the disturbance parameters and compensation commands and establishing effective control samples is as follows: The phase drift value and dissipation gradient of the shear disturbance event that triggered this compensation are extracted as environmental parameters, as well as the instantaneous fire control commands actually issued by the system. The environmental parameters and control commands are structured and packaged in a one-to-one correspondence to form a complete and effective control sample, which is then stored in a local historical experience database for array storage. The method for converting control commands into compensation gears based on effective control samples is as follows: S401. Extract all effective control samples accumulated in the local historical experience database after long-term operation for a preset period, compare the cross-overlap of all effective control samples, and establish typical disturbance control intersections based on the comparison results. Preferably, the method for comparing cross-overlap is as follows: Cross-overlap comparison is performed on environmental parameters and control commands in all valid control samples to find the data subset with the most concentrated physical data distribution and the highest overlap frequency, which is then used as the target data subset. The environmental characteristic range and fire compensation parameters corresponding to the selected target data subset are used as the intersection of typical disturbance control that occurs frequently in the current specific kitchen physical environment. S402. Based on the intersection of typical disturbance control, extract the corresponding compensation command as fire compensation parameter and discretize it. The discretized fire compensation parameters are directly associated with the expected environmental feature intervals to construct a condition-triggered state machine mapping relationship. Based on the state machine mapping relationship, several compensation levels for graded firepower are established, which are triggered by different environmental thresholds. For example, the way to trigger the compensation level of tiered firepower is as follows: Weak disturbance compensation level: When the system detects the dissipation gradient as an environmental characteristic region ( When the state is in (0,0.5], the state machine triggers the weak disturbance compensation mode. At this time, the system does not perform complex continuous fine-tuning of the fan speed, but directly calls the preset discrete compensation command, such as directly increasing the opening of the gas proportional valve by 2% to offset the heat loss caused by the small disturbance. Medium shear compensation mode: When the dissipation gradient is in (0.5, 1.5], the state machine transitions and triggers the medium shear compensation mode. At this time, the system determines that there is a continuous wind direction shear outside and directly maps and outputs the medium firepower compensation parameters, such as simultaneously increasing the fan speed by 300 RPM and increasing the gas valve opening by 5% to ensure flame rigidity. Strong through-draft compensation mode: When the dissipation gradient is higher than the upper limit of the dissipation gradient of the moderate shear compensation mode, the state machine transitions and triggers the strong through-draft compensation mode. Within this extreme value range, the system no longer performs feedforward equivalent calculation, but instead prioritizes maintaining the flame and maps the extreme value compensation parameters, such as forcing the fan to enter the windproof high speed mode and switching to high fire section combustion.

[0026] State Reconstruction Module: Used to continuously monitor the execution decay rate of compensation levels, perform performance regression analysis of historical experience samples based on the execution decay rate, identify the drift state of physical boundaries based on the analysis results, and adjust the historical calibration. The process of continuously monitoring the execution attenuation rate of compensation levels and performing performance regression analysis on historical experience samples based on the execution attenuation rate is as follows: In some embodiments, the system continuously extracts failure compensation events where the thermal recovery performance fails to meet the standard during long-term operation. The frequency of failure compensation events where the thermal recovery efficiency fails to meet the standard is counted within a preset time window (e.g., 30 consecutive calendar days), and the execution attenuation rate is calculated. It should be noted that the increase in the execution decay rate indicates that the current physical fluid environment of the kitchen (such as flue damping and base pressure) has deviated from the initial state when the effective control sample was established. Based on the execution decay rate, a time decay factor is introduced for the corresponding valid control samples in the local historical experience database. Preferably, when the execution attenuation rate exceeds the first preset safety threshold (e.g., 20%), the weight of the effective control sample is reduced. In the event of a shear disturbance in the future, the system proportionally reduces the feedforward thermal compensation equivalent of the compensation level output to prevent erroneous experience from causing severe overshoot. The method for identifying the drift state of the physical boundary based on the analysis results and adjusting the historical calibration is as follows: S501. Extract the real-time operating current fluctuation value of the intelligent range hood fan motor under the constant speed output command, as well as the average ambient temperature of the current season; S502. Compare the real-time operating current fluctuation value with the reference load current under the initial interference-free calibration state. If the difference continuously exceeds the fault tolerance range and the attenuation rate deviates from the expectation, it is determined that an irreversible physical drift has occurred. Preferably, the execution decay rate deviates from the expected value, i.e., the execution decay rate exceeds the second preset safety threshold (e.g., 40%). The fault tolerance range refers to the fluctuation range of ±10% to ±15% of the baseline load current established by the smart range hood after initial installation and with unobstructed airflow. Understandably, the purpose of setting a fault tolerance range is to filter out reasonable current fluctuations caused by unstable grid voltage or normal heating of the motor itself, and to ensure that only when oil accumulation or increased wind resistance causes a substantial jump in motor load is it judged as exceeding the fault tolerance range. If the fluid dynamics boundary of the current system has undergone irreversible physical drift (such as severe filter blockage or drastic changes in flue gas pressure), then it can be objectively determined that the fluid dynamics boundary of the current system has undergone irreversible physical drift (such as severe filter blockage or drastic changes in flue gas pressure). S503. If an irreversible physical drift occurs, the system generates a global reconstruction instruction to adjust the target data subset and the transmission spatiotemporal calibration sequence. Preferably, the method for adjusting the target data subset and the transmission spatiotemporal calibration sequence is as follows: By receiving the generated global reconstruction command, the system clears or archives the subset of target data affected by physical drift in the local historical experience database; At the same time, the system temporarily disables all transient compensation actions based on historical experience and downgrades to the basic PID closed-loop temperature control mode. Based on the global reconstruction command, the reference extraction module is forcibly woken up. In the next windless disturbance environment, the synchronous sampling and state consistency analysis are re-executed to update the steady-state delay constant and the transmission spatiotemporal calibration sequence, thus completing the closed loop adjustment of the control reference. Example 3:

[0027] Please see Figure 3 As shown, a method for intelligent collaborative control of kitchen processing includes the following steps: S1. Simultaneously collect the firepower fluctuation sequence from the stove side and the oil fume concentration sequence from the range hood side, and perform state consistency analysis on the two sets of sequences to obtain steady-state correlation characteristics; based on the steady-state correlation characteristics, determine the transmission calibration sequence for cooking in a windless environment. S2. Monitor the dynamic phase drift of the real-time concentration sequence and the fire sequence, compare the dynamic phase drift with the transmission spatiotemporal calibration sequence, and determine whether a phase lock-out signal is triggered; based on the phase lock-out signal, identify the characteristics of the interference source in the space to obtain the shear disturbance event; S3. Extract the capture time and duration of the shear turbulence event, analyze the heat dissipation gradient of the pot bottom and generate the feedforward heat compensation equivalent; control the stove to perform system-level heat compensation based on the feedforward heat compensation equivalent. S4. Track the temperature recovery curve after heat compensation and verify whether the heat recovery performance of the current compensation action meets the standard; if the performance meets the standard, organize the turbulence parameters and compensation commands and establish an effective control sample; based on the effective control sample, convert the control command into the compensation level; S5. Continuously monitor the execution attenuation rate of the compensation level, and perform performance regression analysis of the historical experience sample based on the execution attenuation rate; identify the drift state of the physical boundary based on the analysis results, and adjust the historical calibration.

[0028] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A kitchen intelligent processing and collaborative work control system, characterized in that, Includes the following modules: The disturbance determination module is used to read the transmission calibration sequence, monitor the dynamic phase drift of the real-time concentration sequence and the fire sequence, compare the dynamic phase drift with the transmission spatiotemporal calibration sequence, and determine whether a phase lock-out signal is triggered; based on the phase lock-out signal, the characteristics of the interference source in the space are identified to obtain the shear disturbance event; Heat loss assessment module: used to extract the capture time and duration of shear turbulence events, analyze the heat dissipation gradient of the pot bottom and generate feedforward heat compensation equivalent; control the stove to perform heat compensation based on the feedforward heat compensation equivalent; Thermal compensation module: used to track the temperature recovery curve after thermal compensation and verify whether the thermal recovery efficiency of the current compensation action meets the standard; if the efficiency meets the standard, it organizes the turbulence parameters and compensation commands and establishes an effective control sample; based on the effective control sample, it converts the control commands into compensation levels; State Reconstruction Module: Used to continuously monitor the execution decay rate of compensation levels, perform performance regression analysis of historical experience samples based on the execution decay rate, identify the drift state of physical boundaries based on the analysis results, and adjust the historical calibration.

2. The kitchen intelligent processing and collaborative work control system according to claim 1, characterized in that, The method for reading the transmission calibration sequence is as follows: Simultaneously collect the firepower fluctuation sequence from the stove side and the oil fume concentration sequence from the range hood side, and perform state consistency analysis on the two sets of sequences to obtain steady-state correlation characteristics; Based on steady-state correlation characteristics, a transmission calibration sequence for cooking under windless disturbance conditions is determined.

3. The kitchen intelligent processing and collaborative work control system according to claim 2, characterized in that, The state consistency analysis is performed as follows: Extract the step abrupt change point in the firepower fluctuation sequence on the time axis as the initiation control peak; Simultaneously, a translation search is performed on the oil fume concentration sequence to identify the concentration response peak on the time axis; Calculate the time difference between the timestamp of the initiation peak and the timestamp of the concentration response peak, and use the time difference as the one-way physical transmission delay. During a continuous initial cooking period without significant environmental interference, multiple sudden changes in fire intensity were induced, and the corresponding multiple unidirectional physical transmission delays were extracted. The extracted unidirectional physical transmission delays are statistically averaged to obtain the steady-state delay constant, which is then used as a steady-state correlation feature.

4. The kitchen intelligent processing and collaborative work control system according to claim 1, characterized in that, The method for identifying the characteristics of the interference source is as follows: Based on the comparison results of dynamic phase drift and transmission spatiotemporal calibration sequence, the transmission deviation margin is extracted; Analyze the absolute amplitude offset of the transmission deviation margin to determine whether the current physical transmission phase of the system is in a disturbed state. If it is, generate a transient phase loss signal. The causes of concentration decrease are identified by using transient phase-locked signals to determine the characteristics of the disturbance source, and the disturbance events are classified based on the identification results; The classification results include: shear disturbance events and routine cooking interventions.

5. The kitchen intelligent processing and collaborative work control system according to claim 4, characterized in that: The method for extracting the transmission deviation margin is as follows: Extract the moment of the heat step within the current cooking cycle as the zero point of time, and retrieve the corresponding expected concentration rise curve in the transmission spatiotemporal calibration sequence as a reference benchmark; The real-time concentration sequence fed back by the oil fume concentration sensor is acquired synchronously, and the starting moment of the first effective concentration increase in the real-time concentration sequence is found by using a time window sliding comparison method, which is defined as the real-time response time point. The phase drift value is obtained by calculating the time deviation between the real-time response time and the theoretical starting time in the expected concentration rise curve; The dimensionless deviation margin coefficient is obtained by dividing the acquired phase drift value by the steady-state delay constant in the transmission spatiotemporal calibration sequence.

6. The kitchen intelligent processing and collaborative work control system according to claim 1, characterized in that: The heat compensation is performed as follows: At the moment the shear turbulence event is detected, a takeover command is sent to the underlying control unit of the smart range hood to freeze the range hood status and cut off the normal linkage feedback loop between the oil fume concentration sensor and the motor speed. The generated feedforward thermal compensation equivalent is subjected to time-limited allocation processing. Based on the result of the amplitude limiting and allocation processing, a firepower control command is issued to the smart stove to drive the smart stove to execute incremental firepower output; When the actual cumulative heat release from the incremental firepower output reaches the feedforward heat compensation equivalent, the control of the smart range hood is released, and the output power of the smart stove is controlled to drop back to the initial heating load to achieve heat compensation.

7. A kitchen intelligent processing and collaborative work control system according to claim 6, characterized in that: The method for generating the feedforward thermal compensation equivalent is as follows: The phase loss signal that triggers the shear disturbance event is continuously tracked until the phase loss signal disappears and the phase of the concentration sequence and the fire sequence are rematched. The total duration of the loss state is defined as the duration period. Obtain the initial heating load of the smart cooktop at the capture time; Combining the initial heating load with the current kitchen ambient temperature, the instantaneous temperature drop rate of the pot bottom during the process of dissipating heat to the surrounding cold air is evaluated and defined as the dissipation gradient. The superposition quantization calculation of the dissipation gradient over time during the continuous period is performed to obtain the equivalent temperature drop at the bottom of the pot during the shear turbulence. The lost temperature drop equivalent is converted into the feedforward heat compensation equivalent required by the smart cooktop.

8. The kitchen intelligent processing and collaborative work control system according to claim 1, characterized in that: The method to switch to the compensation gear is as follows: After extracting all effective control samples accumulated in the local historical experience database after long-term operation for a preset period, cross-overlap comparison is performed on all effective control samples, and typical disturbance control intersections are established based on the comparison results. Based on the intersection of typical disturbance control, the corresponding compensation command is extracted as a fire compensation parameter and discretized. The discretized fire compensation parameters are directly associated with the expected environmental feature intervals to construct a condition-triggered state machine mapping relationship. Based on the state machine mapping relationship, several compensation levels are established.

9. A kitchen intelligent processing and collaborative work control system according to claim 1, characterized in that: The method for adjusting historical calibration is as follows: Extract the real-time operating current fluctuation value of the intelligent range hood fan motor under the output constant speed command, as well as the average ambient temperature of the current season; The real-time operating current fluctuation value is compared with the reference load current under the initial interference-free calibration state. If the difference continuously exceeds the fault tolerance range and the attenuation rate deviates from the expectation, it is determined that an irreversible physical drift has occurred. If an irreversible physical drift occurs, the system generates a global reconstruction instruction to adjust the target data subset and the transmission spatiotemporal calibration sequence.

10. A kitchen intelligent processing and collaborative work control system according to claim 9, characterized in that, The method for obtaining the execution decay rate is as follows: The frequency of failure compensation events where the thermal recovery efficiency fails to meet the standard is counted within a preset time window, and the execution attenuation rate is calculated.

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