An oven hot air control system

Abstract

The present application relates to the field of oven, and discloses an oven hot air control system, comprising a region state initial score module, a thermal coupling atlas construction module, a coupling state aggregation module, a thermal interference deviation analysis module, a space-time joint risk assessment module, an intervention analysis module and a collaborative regulation and deviation correction module. By collecting multi-dimensional running parameters of each region to generate an initial state score vector, combining space topology and temperature difference wind speed to construct a global thermal coupling atlas, and generating a global comprehensive score through coupling aggregation, the deviation between the initial score and the comprehensive score is analyzed, the properties of heat excess dispersion zones or interference attenuation zones are identified, the space-time joint thermal risk coefficient is calculated in combination with historical time series, high-risk areas are screened, target intervention regulation indexes are calculated according to abnormal properties, running parameters of target areas and associated areas are collaboratively regulated, and thermal interference deviation is corrected in real time through closed-loop feedback, so as to realize precise intelligent control of oven hot air.

Description

Technical Field

[0001] This invention relates to the field of oven technology, and more specifically to an oven hot air control system. Background Technology

[0002] Modern commercial and industrial ovens typically employ a complex architecture with independent multi-temperature zone control and strong convection circulation. Their internal space is divided into multiple control zones equipped with independent heating elements and circulating fans to meet the differentiated temperature environment requirements of different baking stages or different ingredients. During actual system operation, each control zone not only relies on its local heating source and air supply mechanism to maintain the set target temperature, but also relies on high-frequency operating fans to drive hot air to form strong convection within the cavity. After the hot air flows through the heating source and heats up, it not only covers its own zone, but also continuously migrates heat and exchanges fluids with adjacent and even non-adjacent zones through common air supply ducts, return air channels, and physical gaps between zones. This multi-zone heat transfer mechanism based on forced convection means that the temperature changes in each control zone inside the oven are no longer determined solely by the local actuator, but exhibit a physical phenomenon of dynamic heat overflow and intrusion across zones. Temperature fluctuations or power adjustments in any zone will be transmitted to other zones as thermal disturbances along the airflow network, causing the entire oven's thermal field to evolve into a complex system with strong multivariable coupling and dynamic spatiotemporal correlation.

[0003] Current technologies for hot air control in multi-temperature zone ovens typically employ a single-loop closed-loop control strategy based on local real-time temperature. This means each control zone independently adjusts its heating element and fan based solely on feedback from its own temperature sensor, without considering the cross-zone heat transfer and dynamic coupling characteristics within the oven caused by forced convection. This isolated, "each fighting its own battle" control method has significant drawbacks: On the one hand, due to the lack of quantitative perception of the thermal coupling relationship between regions, the local controller cannot predict the passive interference caused by heat overflow or intrusion from adjacent regions to its own region, which can easily lead to control lag and reverse overshoot, making it difficult to converge local temperature field fluctuations. On the other hand, when a thermal anomaly occurs in a certain region, the existing technology can only passively respond to the temperature deviation in that region, and cannot trace the spatial correlation source of the thermal anomaly, nor can it assess the cascading impact of local intervention along the wind path network on other regions. Lacking a spatiotemporal coordinated intervention mechanism, it is very easy to induce secondary imbalances in the global temperature field while suppressing local thermal deviations, making it difficult to achieve high-precision and high-stability control in complex and strongly coupled thermal field environments. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides an oven hot air control system to solve the problems existing in the background art.

[0005] This invention provides the following technical solution: an oven hot air control system, comprising: Initial state scoring module for each control zone: This module is used to collect multi-dimensional operating parameters of each independent control zone inside the oven, evaluate each operating parameter in conjunction with the target temperature, and generate an initial state scoring vector for each control zone. Thermal coupling map construction module: Based on the spatial topological relationship and initial state score vector of each control area, combined with the real-time temperature difference and wind speed direction between areas, a global thermal coupling map is constructed. Coupled State Aggregation Module: Based on the global thermal coupling map, thermal coupling analysis and state aggregation are performed on each control region, the initial state score vector is updated, and a comprehensive global coupled state score for each control region is generated. Thermal Interference Deviation Analysis Module: By analyzing and calculating the initial state score vector of each control area and the comprehensive score of the global coupling state, the regional thermal interference deviation index is obtained. Combined with the overall distribution trend of the comprehensive score of the global coupling state, the thermal anomaly correlation attributes of each control area are identified. Spatiotemporal joint risk assessment module: Based on thermal anomaly correlation attributes and global thermal coupling map, combined with the time series of global coupling state comprehensive scores of each control area at historical moments, spatial-temporal joint evolution analysis is performed on each control area to calculate the spatiotemporal joint thermal risk coefficient of each control area; Intervention Analysis Module: Target intervention areas are screened based on the spatiotemporal joint thermal risk coefficient, and intervention analysis and calculation are performed based on thermal anomaly correlation attributes and global thermal coupling map to obtain the target intervention regulation index; Coordinated regulation and deviation correction module: Based on the target intervention regulation index, the module regulates the operating parameters of the target intervention area and its related areas, and corrects thermal interference deviations in real time.

[0006] Preferably, the initial scoring module for the regional status uses temperature sensors, humidity sensors, wind speed sensors, wind direction sensors, wind pressure sensors, and infrared radiation sensors deployed in each independent control area to collect temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity in each area in real time; the collected data is then processed sequentially by sliding window filtering, outlier removal, and normalization to obtain multidimensional operating parameters for each area. Each operating parameter is calculated with its corresponding target value to obtain an initial deviation value. The initial deviation value is then corrected based on the target temperature set by the oven to obtain the equivalent deviation of each parameter. Based on the equivalent deviation and the preset allowable deviation range, a single score for each parameter is generated. The single scores are then combined into an initial state score vector for each control area.

[0007] Preferably, the thermally coupled graph construction module maps each independent control area to a graph node and carries the corresponding initial state score vector. It extracts spatial topological relationships through physical layout, determines interaction paths between spatially adjacent control areas, and calculates a temperature difference driving factor based on the ratio of the real-time temperature difference between the two adjacent areas to the preset maximum allowable temperature difference for two adjacent control areas directly connected by the interaction path. It calculates a wind speed direction factor based on the cosine similarity between the wind direction of the air outlet of one of the adjacent areas and the direction of the interaction path. It calculates a state score modulation factor based on the smaller value of the comprehensive score of the initial state score vectors of the two adjacent areas. Then, it performs weighted calculation on the temperature difference driving factor, wind speed direction factor and state score modulation factor to obtain the relationship weight corresponding to the interaction path. Finally, it constructs a global thermally coupled graph with each control area as a graph node, the interaction path as a directed edge, and the calculated relationship weight as the directed edge weight.

[0008] Preferably, the coupling state aggregation module is used to, for any target node in the global thermal coupling graph, filter all incident directed edges ending at the target node, obtain the source node and relation weight corresponding to each incident directed edge; calculate the product of the comprehensive score of the initial state score vector of each source node and the relation weight of the corresponding incident directed edge, and accumulate all products to obtain the global coupling influence value of the target node; fuse the global coupling influence value of the target node with the comprehensive score of the initial state score vector of the target node to generate the global coupling state comprehensive score of the node, and use the global coupling state comprehensive score to modulate and update the scores of each dimension in the initial state score vector of the node; traverse all nodes in the global thermal coupling graph to complete state aggregation, and obtain the updated global coupling state comprehensive score of each control region.

[0009] Preferably, the thermal interference deviation analysis module is used to calculate the absolute value of the difference between the comprehensive score of the global coupling state of each control region and the comprehensive score of the initial state score vector to obtain the regional thermal interference deviation index; and to calculate the mean and variance of the comprehensive score of the global coupling state of all control regions to evaluate the overall global distribution trend. The thermal interference significance coefficient of this region is calculated based on the ratio of the thermal interference deviation index of this region to the variance of the comprehensive score of the global coupling state of all control regions. For any control region, when the thermal interference significance coefficient of the region is greater than the preset significance threshold, the thermal anomaly association attribute is identified based on the relationship between the comprehensive score of the global coupling state of the region and the comprehensive score of the initial state score vector. If the comprehensive score of the global coupling state is less than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a disturbance attenuation zone. If the comprehensive score of the global coupling state is greater than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a heat excess dissipation zone.

[0010] Preferably, the spatiotemporal joint risk assessment module is used to extract the comprehensive score of the global coupling state of each control area within a preset historical time window to form a time series sequence, calculate the rate of change of the time series sequence, and obtain the time series evolution trend value of each control area; For any control region, the corresponding relation weights are obtained based on the global thermal coupling map. The spatial risk calculation strategy is determined according to the thermal anomaly correlation attributes of the region. If it is a heat excess dispersion zone, the cumulative sum of the relation weights of all outgoing directed edges starting from the region is calculated. If it is a disturbance attenuation zone, the cumulative sum of the relation weights of all incoming directed edges ending from the region is calculated. The obtained cumulative sum is multiplied by the thermal interference significance coefficient of the region to obtain the spatial evolution status value of the control region. The temporal evolution trend value and the spatial evolution status value of each control region are weighted and calculated to obtain the spatiotemporal joint thermal risk coefficient of each control region.

[0011] Preferably, the intervention analysis module is used to filter control areas with a spatiotemporal joint thermal risk coefficient greater than a preset risk threshold as target intervention areas; For any target intervention area, the difference between the comprehensive score of its initial state score vector and the comprehensive score of the global coupled state is calculated, and this difference is multiplied by the spatiotemporal joint thermal risk coefficient of the area to obtain the basic intervention amount. Based on the thermal anomaly correlation attribute of the area and the global thermal coupling map, the spatial intervention modulation factor is calculated. If it is a heat excess dispersion area, the average weight of all outgoing directed edge relationships starting from the area is calculated as the spatial spillover modulation factor. If it is a disturbance attenuation area, the average weight of all incoming directed edge relationships ending from the area is calculated as the spatial intrusion modulation factor. The basic intervention amount and the corresponding spatial intervention modulation factor are fused to obtain the target intervention control index of the target intervention area.

[0012] Preferably, the coordinated regulation and deviation correction module is used to calculate the incremental regulation of operating parameters in the target intervention area based on the target intervention regulation index; based on the global thermal coupling map, it extracts the associated areas with directed edges connected to the target intervention area and their corresponding relationship weights, and multiplies the incremental regulation of operating parameters with the corresponding relationship weights to obtain the coordinated regulation increment of each associated area; it simultaneously regulates the hot air operating parameters of the target intervention area and associated areas according to the incremental regulation of operating parameters and the coordinated regulation increment; after the regulation cycle, it re-collects the operating parameters, updates the global coupling state comprehensive score and recalculates the thermal interference deviation index to complete the real-time closed-loop correction.

[0013] The technical effects and advantages of this invention are as follows: (1) The global thermal coupling map is constructed based on spatial topology, real-time temperature difference and wind speed direction by the thermal coupling map construction module. The coupling state aggregation module performs thermal coupling analysis and state aggregation based on the map to generate a global coupling state comprehensive score. This integrates the cross-regional heat migration interference into the local state assessment, enabling the system to predict and accurately perceive the passive impact of heat overflow or intrusion from adjacent areas on the local area, effectively avoiding control lag and reverse overshoot, and significantly improving the convergence speed and stability of local temperature field fluctuations.

[0014] (2) By calculating the regional thermal interference deviation index through the thermal interference deviation analysis module and combining the overall distribution trend of the global coupling state comprehensive score, the thermal anomaly correlation attributes of each control area are identified, thereby analyzing the spatial source of thermal anomalies. This can break through the limitation of only passively responding to local temperature deviations, accurately locate the spatial correlation source and propagation path of thermal anomalies, and provide accurate spatial basis for subsequent targeted interventions.

[0015] (3) The intervention analysis module calculates the target intervention control index based on the thermal anomaly correlation attributes and the global thermal coupling spectrum. The collaborative control and deviation correction module adjusts the operating parameters of the target intervention area and its related areas simultaneously based on the index. Thus, the collaborative intervention amount is allocated based on the network topology. It can accurately assess and dynamically allocate the cascading effects of local intervention along the wind path network on the related areas, realize multi-region spatiotemporal collaborative intervention, effectively avoid the secondary imbalance of the global temperature field induced when suppressing local deviations, and ensure the high precision and high stability of system control under complex and strongly coupled thermal field environment. Attached Figure Description

[0016] Figure 1 This is a system structure block diagram of the present invention.

[0017] Figure 2 This is a diagram illustrating the method steps of the present invention. Detailed Implementation

[0018] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The oven hot air control system involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] like Figure 1 The embodiment shown provides an oven hot air control system, including: The initial state scoring module for each control zone is used to collect multi-dimensional operating parameters of each independent control zone within the oven, evaluate each operating parameter in conjunction with the target temperature, and generate an initial state scoring vector for each control zone.

[0020] In this embodiment, the initial scoring module for the regional status collects the temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity of each region in real time through temperature sensors, humidity sensors, wind speed sensors, wind direction sensors, wind pressure sensors, and infrared radiation sensors deployed in each independent control region; the collected data is then processed sequentially by sliding window filtering, outlier removal, and normalization to obtain the multidimensional operating parameters of each region. Each operating parameter is calculated with its corresponding target value to obtain an initial deviation value. The initial deviation value is then corrected based on the target temperature set by the oven to obtain the equivalent deviation of each parameter. Based on the equivalent deviation and the preset allowable deviation range, a single score for each parameter is generated. The single scores are then combined into an initial state score vector for each control area.

[0021] It should be specifically explained that, through temperature sensors, humidity sensors, wind speed sensors, wind direction sensors, wind pressure sensors, and infrared radiation sensors deployed in each independent control zone of the oven, six-dimensional raw data of temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity are collected in real time for each zone; specifically, taking zone i ( The raw data collected at time t; the collected data were then subjected to sliding window filtering, outlier removal, and normalization in sequence: first, the window length was used... A sliding window mean filter is used to eliminate high-frequency noise, where wind direction is calculated using an angle-weighted average method instead of a direct mean due to its angular characteristics; then... Outliers are eliminated based on the criterion that if a parameter value differs from the mean value of the region over the past 60 seconds by more than three times the standard deviation, the mean value is used instead. Finally, Min-Max normalization is used to map all parameters to the interval [0, 1], resulting in a multidimensional operating parameter vector for region i. Where T is temperature, H is humidity, V is wind speed, D is wind direction, P is wind pressure, and R is thermal radiation intensity; then, the initial deviation value is obtained by calculating the deviation of each operating parameter from its corresponding target value, and the calculation formula is: ,in Let be the initial deviation value of parameter j in region i at time t. For the normalized running value of parameter j in region i, Let j be the normalized target value of parameter j, where j is the parameter index and Considering that the same absolute deviation can have significantly different effects on cooking results at different oven target temperatures—for example, a 1°C deviation during low-temperature fermentation is more fatal than during high-temperature baking—the system uses the oven's target temperature as the primary setting. The initial deviation value is corrected based on the user-defined value (in °C). Specifically, the correction is performed based on the target temperature. Dynamically allocate temperature modulation coefficients to each parameter This coefficient reflects the system's sensitivity to deviations from this parameter at the current target temperature, and its calculation formula is as follows: ,in To maintain a fixed reference temperature, for temperature parameters, when hour To amplify the bias penalty, when hour To reduce the penalty for deviation, the temperature modulation coefficients for non-temperature parameters such as humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity can be set individually or uniformly using the same modulation coefficient as the temperature parameter, based on the coupling relationship between each parameter and temperature; thus, the equivalent deviation can be calculated. ,in The equivalent deviation value of parameter j in region i at time t; after obtaining the equivalent deviation, based on the preset allowable deviation range... Individual scores are generated for each parameter. The preset allowable deviation range defines the limit threshold for parameter fluctuations. The preset allowable deviation range is segmented or dynamically mapped based on the target temperature set in the oven and the process tolerance of the corresponding parameter. The allowable deviation range is different for different parameters. The relative deviation rate of the equivalent deviation to the allowable deviation range is calculated. ,in Let j represent the relative deviation rate of parameter j in region i at time t, and use a linear deduction mechanism to calculate the individual score. The calculation formula is as follows: in, Let j represent the individual score of parameter j in region i at time t, with a value range of [0, 1]. The individual scores of the six parameters—temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity—are combined to form the initial state score vector of region i. .

[0022] Thermal coupling map construction module: Based on the spatial topology relationship and initial state score vector of each control area, combined with the real-time temperature difference and wind speed direction between areas, a global thermal coupling map is constructed.

[0023] In this embodiment, the thermally coupled graph construction module maps each independent control area to a graph node and carries the corresponding initial state score vector. It extracts spatial topological relationships through physical layout, determines interaction paths between spatially adjacent control areas, and calculates a temperature difference driving factor based on the ratio of the real-time temperature difference between the two adjacent areas to the preset maximum allowable temperature difference for two adjacent control areas directly connected by the interaction path. It calculates a wind speed direction factor based on the cosine similarity between the wind direction of the air outlet of one of the adjacent areas and the direction of the interaction path. It calculates a state score modulation factor based on the smaller value of the comprehensive score of the initial state score vectors of the two adjacent areas. Then, it performs weighted calculation on the temperature difference driving factor, wind speed direction factor, and state score modulation factor to obtain the relationship weight corresponding to the interaction path. Finally, it constructs a global thermally coupled graph with each control area as a graph node, the interaction path as a directed edge, and the calculated relationship weight as the directed edge weight.

[0024] It should be specifically explained that the thermal coupling map construction module constructs a global thermal coupling map based on the spatial topological relationship of each control region and the initial state score vector of each control region output by the initial state score module, combined with the real-time temperature difference and wind speed direction between regions. Specifically, the N independent control regions inside the oven are mapped to N nodes in the map, and the set of nodes is denoted as . , where nodes The attribute is the initial state score vector output by the region state initial score module. This vector comprehensively reflects the operating status of region i in six dimensions: temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity. The value range of each component is [0, 1]. Spatial topology is extracted through the physical layout of each independent control region within the oven, where the physical layout is determined by the geometric coordinates of each region within the oven cavity. To determine the interaction path between spatially adjacent control areas, the specific determination method is as follows: for any two nodes... and Calculate the Euclidean distance between the two within the oven cavity. ,like Less than the preset maximum interaction distance (In this embodiment) If the distance is less than 150mm, then there is an interaction path between region i and region m. Let the interaction path from region i to region m be a directed edge. For two adjacent control regions i and m directly connected by an interaction path, the three factors required to calculate the relationship weight corresponding to this interaction path are as follows: The first is the temperature difference driving factor, where the real-time temperature difference between region i and region m is... ,in , These are the normalized temperature values ​​for regions i and m, respectively. The temperature difference driving factor is calculated by the ratio of the real-time temperature difference to the preset maximum allowable temperature difference. ,in The maximum permissible temperature difference is a preset value (normalized and pre-set based on the oven's process temperature control accuracy requirements). In this embodiment... The range of values ​​for this factor is: When the calculated result is greater than 1, it is taken as 1, which means that the greater the temperature difference, the stronger the driving force of heat conduction and convection between regions; the second is the wind speed direction factor, assuming that the spatial azimuth angle of the interaction path from region i to region m is . It is calculated from the spatial coordinates of the two regions, and the calculation method is as follows: Among them, due to the wind direction collected by the wind direction sensor The azimuth angle of the interaction path is the angle within the horizontal plane (range 0-360°). The calculation is based solely on the coordinate difference between the two regions in the horizontal plane, without considering the height difference along the z-axis. The air outlet direction of region i is... (Data collected by a wind direction sensor, ranging from 0-360°), the wind speed direction factor is calculated using the cosine of the angle between the wind direction at the outlet and the direction of the interaction path, i.e. The value range of this factor is [-1, 1]. When the wind direction is completely consistent with the interaction path direction, that is, the hot wind blows directly from region i to region m, the heat transfer effect is strongest. The time indicates that the wind direction is completely opposite to the direction of the interaction path, that is, the hot wind blows from region m to region i. Heat transfer is weakened when The first factor indicates that the wind direction is perpendicular to the interaction path direction, and the hot wind has no directional transport effect on this path; the third factor is the state score modulation factor, which first calculates the comprehensive score of region i as the arithmetic mean of the individual scores of the six dimensions, i.e. The value range is [0, 1]. Similarly, the comprehensive score of region m is calculated. The state score modulation factor is calculated by subtracting the smaller value from the combined scores of the two regions from 1. The value range of this factor is [0, 1]. Its physical meaning is that when the operating state of either region in the two regions is poor, i.e., the overall score is low, the thermal coupling between them has a greater negative impact on the global temperature uniformity. Therefore, the larger the value of this factor, the more important the coupling path needs to be controlled. Combining the above three factors, the interaction path... The corresponding relational weights are calculated by weighted summation of the three factors, using the following formula: ,in These are the weighting coefficients for the temperature difference driving factor, wind speed direction factor, and state score modulation factor, respectively, which are set to values ​​of [value missing] in this embodiment. , , That is, the weight coefficient of the temperature difference driving factor is the largest, the weight coefficient of the wind speed direction factor is the second largest, and the weight coefficient of the state score modulation factor is the smallest, and it satisfies the following condition. The resulting global thermal coupling map is denoted as . Where Z is the set of nodes, L is the set of directed edges, and W is the directed edge weight matrix. Each directed edge in this graph... weight The thermal coupling strength of region i to region m was characterized. The larger the edge weight, the more significant the thermal influence of region i on region m, which provides a quantitative basis for determining the priority control path and control direction in subsequent hot air control strategies.

[0025] Coupled State Aggregation Module: Based on the global thermal coupling map, it performs thermal coupling analysis and state aggregation on each control region, updates the initial state score vector, and generates a comprehensive global coupled state score for each control region.

[0026] In this embodiment, the coupling state aggregation module is used to select all incident directed edges with the target node as the endpoint for any target node in the global thermal coupling graph, obtain the source node and relation weight corresponding to each incident directed edge; calculate the product of the comprehensive score of the initial state score vector of each source node and the relation weight of the corresponding incident directed edge, and accumulate all products to obtain the global coupling influence value of the target node; fuse the global coupling influence value of the target node with the comprehensive score of the initial state score vector of the target node to generate the global coupling state comprehensive score of the node, and use the global coupling state comprehensive score to modulate and update the scores of each dimension in the initial state score vector of the node; traverse all nodes in the global thermal coupling graph to complete state aggregation, and obtain the updated global coupling state comprehensive score of each control region.

[0027] It should be noted that the coupling state aggregation module is based on the global thermal coupling map. Thermal coupling analysis and state aggregation are performed on each control region, the initial state score vector is updated, and a comprehensive global coupling state score for each control region is generated; specifically, for any target node in the global thermal coupling map... First, filter based on the target node. Let the set of incident directed edges that terminate at point be denoted as . The meanings of i and m are consistent with those in the thermal coupling map construction module, i.e. For the source node region, For the target node area, To obtain each incident directed edge from region i to region m. corresponding source node and relation weights Then calculate each source node. Overall score of the initial state score vector Weights related to the corresponding incident directed edges The product of all products is summed to obtain the target node. The global coupling effect value is calculated using the following formula: Due to the influence of global coupling, the value The range of values ​​for is related to the number of incident edges and may exceed the interval [0, 1], therefore Divide by the sum of the weights of all incident directed edges to the target node. Normalization is performed to obtain the normalized coupling effect value. Its value range is constrained to [0, 1]; thus, the normalized coupling influence value is... The combined score with the initial state score vector of the target node itself A weighted fusion calculation is performed to generate a comprehensive global coupling state score for this node. The calculation formula is as follows: ,in This is the self-assessment weighting coefficient, with a value range of [value range missing]. In this embodiment, we take That is, the new comprehensive score of the target node is determined by a weighted average of its original score and the coupling influence of the surrounding area; after obtaining the comprehensive score of the global coupling state. Then, the scores of each dimension in the initial state score vector of the target node are modulated and updated using this comprehensive score. Specifically, the modulation method is as follows: while maintaining the relative proportions between the scores of each dimension, the overall comprehensive score is changed from... Updated to That is, the updated scores for each dimension are ,in These correspond to six dimensions: temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity. For the target node The individual score of the j-th dimension in the initial state score vector; traversing all nodes in the global thermal coupling graph. The above state aggregation process is completed sequentially, and finally the updated global coupled state comprehensive score and the corresponding updated state score vector of each control region are obtained.

[0028] Thermal Interference Deviation Analysis Module: By analyzing and calculating the initial state score vector of each control area and the comprehensive score of the global coupling state, the regional thermal interference deviation index is obtained. Combined with the overall distribution trend of the comprehensive score of the global coupling state, the thermal anomaly correlation attributes of each control area are identified.

[0029] In this embodiment, the thermal interference deviation analysis module is used to calculate the absolute value of the difference between the comprehensive score of the global coupling state of each control region and the comprehensive score of the initial state score vector to obtain the regional thermal interference deviation index; and to calculate the mean and variance of the comprehensive score of the global coupling state of all control regions to evaluate the overall global distribution trend. The thermal interference significance coefficient of this region is calculated based on the ratio of the thermal interference deviation index of this region to the variance of the comprehensive score of the global coupling state of all control regions. For any control region, when the thermal interference significance coefficient of the region is greater than the preset significance threshold, the thermal anomaly association attribute is identified based on the relationship between the comprehensive score of the global coupling state of the region and the comprehensive score of the initial state score vector. If the comprehensive score of the global coupling state is less than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a disturbance attenuation zone. If the comprehensive score of the global coupling state is greater than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a heat excess dissipation zone.

[0030] It should be specifically noted that the thermal interferometry deviation analysis module is used to calculate the comprehensive score of the global coupling state of each control region. Combined score with the initial state score vector The absolute value of the difference is used to obtain the regional thermal interference deviation index, and the calculation formula is: Then, the mean and variance of the comprehensive global coupling state score for all N control regions are calculated; subsequently, based on the thermal interference deviation index of that region... Variance of the comprehensive score of global coupling state with all control regions The ratio is used to calculate the thermal interference significance coefficient of this region, and the calculation formula is: For any control region, when the thermal interference significance coefficient of that region... Greater than the preset significance threshold When this occurs, it indicates that the thermal interference deviation in that region is statistically significant in the global distribution. In this case, a comprehensive score is given based on the global coupling state of that region. Combined score with the initial state score vector Identifying thermal anomaly association attributes based on size relationship: If This indicates that the coupling effect of the surrounding area has a negative drag on this area, and the thermal anomaly correlation attribute of this area is identified as a disturbed attenuation zone; if This indicates that the coupling effect of the surrounding area has positively heated this area, and the thermal anomaly correlation attribute of this area is identified as a region of excessive heat dissipation; if If the thermal coupling effect of the surrounding area on the region is completely balanced with its own state and has no significant net effect, then the thermal anomaly correlation attribute of the region is identified as a thermal equilibrium stable zone.

[0031] Spatiotemporal joint risk assessment module: Based on the thermal anomaly correlation attributes and global thermal coupling map, combined with the time series of global coupling state comprehensive scores of each control area at historical moments, the module performs spatial-temporal joint evolution analysis on each control area and calculates the spatiotemporal joint thermal risk coefficient of each control area.

[0032] In this embodiment, the spatiotemporal joint risk assessment module is used to extract the comprehensive score of the global coupling state of each control area within a preset historical time window to form a time series sequence, calculate the rate of change of the time series sequence, and obtain the time series evolution trend value of each control area. For any control region, the corresponding relation weights are obtained based on the global thermal coupling map. The spatial risk calculation strategy is determined according to the thermal anomaly correlation attributes of the region. If it is a heat excess dispersion zone, the cumulative sum of the relation weights of all outgoing directed edges starting from the region is calculated. If it is a disturbance attenuation zone, the cumulative sum of the relation weights of all incoming directed edges ending from the region is calculated. The obtained cumulative sum is multiplied by the thermal interference significance coefficient of the region to obtain the spatial evolution status value of the control region. The temporal evolution trend value and the spatial evolution status value of each control region are weighted and calculated to obtain the spatiotemporal joint thermal risk coefficient of each control region.

[0033] It should be specifically noted that the spatiotemporal joint risk assessment module, based on the correlation attributes of thermal anomalies and the global thermal coupling map, combined with the time series consisting of the comprehensive score of the global coupling state of each control region at historical moments, performs a spatial-temporal joint evolution analysis on each control region and calculates the spatiotemporal joint thermal risk coefficient of each control region; specifically, it first extracts the thermal risk coefficient of each control region. In the preset historical time window Comprehensive score of global coupling state at U time points A time series is constructed, and the ratio of the difference between the first and last moments of the time series to the length of the time window is calculated to obtain the temporal evolution trend value of each control region. The calculation formula is as follows: ,in This indicates that the thermal state of the region has been trending upward within the historical window. This indicates a downward trend. This indicates that the thermal state remains stable; then, for any control region... Based on the global thermal coupling map, the corresponding relationship weights for the region are obtained. The spatial risk calculation strategy is determined according to the thermal anomaly correlation attributes of the region: if the thermal anomaly correlation attribute of the region is a heat excess dispersion zone, it indicates that the region is radiating heat outwards and has a positive thermal impact on the surrounding areas. Therefore, the calculation strategy is based on the region. All outgoing directed edges starting from the origin Relationship weight The sum of the weights of all incident directed edges ending at this region is recorded as the sum of the weights of the outgoing edges. If the thermal anomaly correlation attribute of this region is a disturbed attenuation zone, it indicates that this region is affected by the surrounding regions and has a weak influence on the external thermal field. In this case, the weights of all incident directed edges ending at this region are summed, and this sum is recorded as the sum of the weights of the incident edges. The sum is multiplied by the thermal interference significance coefficient of this region to obtain the spatial evolution status value of the control region. The sum is taken as the sum of the weights of the outgoing edges or the sum of the weights of the incident edges according to the thermal anomaly correlation attribute. The thermal interference significance coefficient is the value calculated by the thermal interference deviation analysis module for this region. The larger the spatial evolution status value, the more significant the influence of the region on the external thermal field. The stronger the thermal risk diffusion trend in the spatial dimension, the more weighted and integrated the temporal evolution trend value and spatial evolution trend value of each control area are calculated. The temporal evolution trend value is multiplied by the temporal weight coefficient, and the difference between one and the temporal weight coefficient is multiplied by the spatial evolution trend value. The two are added together to obtain the spatiotemporal joint thermal risk coefficient of each control area. The value of the temporal weight coefficient is greater than 0 and less than 1. In this embodiment, the temporal weight coefficient is 0.5, that is, the temporal evolution trend and the spatial evolution trend each contribute half of the weight to the final risk coefficient. The larger the spatiotemporal joint thermal risk coefficient, the higher the thermal risk of the control area in the spatiotemporal joint dimension, and the more priority is needed for regulation and intervention.

[0034] Intervention Analysis Module: Target intervention areas are screened based on the spatiotemporal joint thermal risk coefficient. Intervention analysis is performed and calculated based on thermal anomaly correlation attributes and global thermal coupling map to obtain the target intervention regulation index.

[0035] In this embodiment, the intervention analysis module is used to filter control areas with a spatiotemporal joint thermal risk coefficient greater than a preset risk threshold as target intervention areas; For any target intervention area, the difference between the comprehensive score of its initial state score vector and the comprehensive score of the global coupled state is calculated, and this difference is multiplied by the spatiotemporal joint thermal risk coefficient of the area to obtain the basic intervention amount. Based on the thermal anomaly correlation attribute of the area and the global thermal coupling map, the spatial intervention modulation factor is calculated. If it is a heat excess dispersion area, the average weight of all outgoing directed edge relationships starting from the area is calculated as the spatial spillover modulation factor. If it is a disturbance attenuation area, the average weight of all incoming directed edge relationships ending from the area is calculated as the spatial intrusion modulation factor. The basic intervention amount and the corresponding spatial intervention modulation factor are fused to obtain the target intervention control index of the target intervention area.

[0036] It should be specifically explained that the intervention analysis module selects target intervention areas based on the spatiotemporal joint thermal risk coefficient, performs intervention analysis and calculation based on thermal anomaly correlation attributes and global thermal coupling map, and obtains the target intervention control index. Specifically, firstly, control areas with a spatiotemporal joint thermal risk coefficient greater than a preset risk threshold are selected as target intervention areas, where the risk threshold is a risk judgment threshold preset according to actual control needs. Then, for any target intervention area, the difference between its initial state score vector comprehensive score and the global coupling state comprehensive score is calculated. This difference reflects the degree of deviation between the area's own state and the state after coupling influence. This difference is multiplied by the spatiotemporal joint thermal risk coefficient of the area to obtain the basic intervention amount. That is, the basic intervention amount is equal to the difference between the initial state score vector comprehensive score minus the global coupling state comprehensive score multiplied by the spatiotemporal joint thermal risk coefficient. Wherein, a basic intervention amount greater than zero indicates that the area's own state is better than the coupled state and requires positive intervention to improve the thermal state. A basic intervention amount less than zero indicates that the area's own state is worse than the coupled state and requires negative intervention to suppress the thermal state. The larger the spatiotemporal joint thermal risk coefficient, the higher the comprehensive thermal risk coefficient of the area. The higher the risk, the greater the intervention required. Therefore, based on the thermal anomaly correlation attributes of the region and the global thermal coupling map, a spatial intervention modulation factor is calculated: if the thermal anomaly correlation attribute of the region is a heat excess dispersion zone, it indicates that the region is a source of outward heat dissipation, and intervention should focus on controlling the intensity of its outward diffusion. Then, the sum of the relation weights of all outgoing directed edges originating from this region is divided by the number of outgoing directed edges in the region, i.e., the out-degree. The quotient is used as the spatial spillover modulation factor. The more outgoing directed edges there are, the larger the denominator. A larger spatial spillover modulation factor indicates that the region is a source of heat dissipation. The stronger the channel for external heat diffusion, the greater the force required to suppress the outflow during intervention. If the thermal anomaly correlation attribute of the region is a disturbed attenuation zone, it indicates that the region is a passive receiver of heat. During intervention, it is necessary to focus on blocking the external heat intrusion into the region. Then, the sum of the relation weights of all incident directed edges ending at the region is calculated and divided by the number of incident directed edges in the region, i.e., the in-degree. The quotient is used as the spatial intrusion modulation factor. The more incident directed edges there are, the larger the denominator becomes. The larger the spatial intrusion modulation factor, the stronger the external heat intrusion channel into the region, and the greater the force required to block the intrusion during intervention.Finally, the basic intervention amount is fused with the corresponding spatial intervention modulation factor to obtain the target intervention control index for the target intervention area. That is, the target intervention control index equals the basic intervention amount multiplied by the corresponding spatial intervention modulation factor. The spatial intervention modulation factor is either a spatial spillover modulation factor or a spatial intrusion modulation factor, depending on the thermal anomaly correlation attribute. A larger absolute value of the target intervention control index indicates a stronger intervention effort required for the area. The sign of the target intervention control index indicates the intervention direction: a positive value indicates that the thermal state of the area needs to be improved, and a negative value indicates that the thermal state of the area needs to be suppressed. Based on this, the target intervention areas can be sorted from largest to smallest by the absolute value of the target intervention control index, with priority given to the area with the largest absolute value of the control index for intervention control.

[0037] Coordinated regulation and deviation correction module: Based on the target intervention regulation index, the module regulates the operating parameters of the target intervention area and its related areas, and corrects thermal interference deviations in real time.

[0038] In this embodiment, the coordinated regulation and deviation correction module is used to calculate the incremental regulation of operating parameters in the target intervention area based on the target intervention regulation index; based on the global thermal coupling map, it extracts the associated regions with directed edges connected to the target intervention area and their corresponding relationship weights, and calculates the coordinated regulation increment of each associated region by multiplying the incremental regulation of operating parameters with the corresponding relationship weights; it then regulates the hot air operating parameters of the target intervention area and associated regions synchronously according to the incremental regulation of operating parameters and the coordinated regulation increment; after the regulation cycle, it re-collects the operating parameters, updates the comprehensive score of the global coupling state, and recalculates the thermal interference deviation index to complete the real-time closed-loop correction.

[0039] It should be specifically explained that the coordinated control and deviation correction module adjusts the operating parameters of the target intervention area and its related areas based on the target intervention control index, and corrects thermal interference deviations in real time. Specifically, it first calculates the operating parameter adjustment increment of the target intervention area based on the target intervention control index, that is, the operating parameter adjustment increment equals the control gain coefficient multiplied by the target intervention control index. The control gain coefficient is a pre-set proportional mapping parameter based on the actual response sensitivity of the hot air system, used to map the control index to the actual executable parameter adjustment range. The target intervention control index is the value calculated by the intervention analysis module for this area. The sign of the operating parameter adjustment increment is related to... The target intervention and control index consistently indicates the direction of control: a positive value indicates that the hot air operating parameters in the region need to be increased, while a negative value indicates that the hot air operating parameters in the region need to be suppressed. The larger the absolute value of the increment in operating parameter control, the greater the required parameter adjustment range. Furthermore, based on the global thermal coupling map, associated regions with directed edges connected to the target intervention region are extracted: if the thermal anomaly associated attribute of the target intervention region is a heat excess dispersion region, then the associated region is the region pointed to by all outgoing directed edges originating from the target intervention region; if the thermal anomaly associated attribute of the target intervention region is a disturbance attenuation region, then the associated region is the region pointed to by all incoming directed edges ending from the target intervention region. The region is then calculated by multiplying the incremental adjustment of the operating parameters by the relation weights corresponding to each associated region. The result is the coordinated adjustment increment for each associated region: if the associated region is the region pointed to by the outgoing edge, the coordinated adjustment increment for that region is equal to the incremental adjustment of the operating parameters multiplied by the relation weight of the directed edge from the target intervention region to the associated region. A larger relation weight indicates a stronger thermal coupling effect of the target intervention region on the associated region and a greater required coordinated adjustment amplitude for that region. If the associated region is the region pointed to by the incoming edge, the coordinated adjustment increment for that region is equal to the incremental adjustment of the operating parameters multiplied by the relation weight of the directed edge from the associated region to the target intervention region. The system weights are then determined. Finally, the hot air operating parameters of the target intervention area and each associated area are simultaneously adjusted according to the operating parameter control increment and the collaborative control increment. Specifically, the current hot air operating parameter value of the target intervention area is added to its operating parameter control increment to obtain the new operating parameter value after adjustment. The current hot air operating parameter value of each associated area is added to its corresponding collaborative control increment to obtain the new operating parameter value after adjustment for each area. That is, the hot air operating parameters of the target intervention area are adjusted according to its operating parameter control increment, and the hot air operating parameters of each associated area are adjusted according to its corresponding collaborative control increment. The parameter adjustments of all areas are executed simultaneously within the same control cycle.After the control cycle ends, the operating parameters of each control area are recollected, the global coupling state comprehensive score is updated, and the thermal interference deviation index is recalculated. The updated thermal interference deviation index is compared with the thermal interference deviation index before control. If the deviation decreases, the control is effective; if the deviation does not decrease or increases, control is re-executed according to the new target intervention control index, thereby completing real-time closed-loop correction.

[0040] like Figure 2 The embodiment shown provides a method for controlling the hot air flow in an oven, including the following steps: Step 1: Collect multi-dimensional operating parameters of each independent control zone in the oven, evaluate each operating parameter in conjunction with the target temperature, and generate an initial state score vector for each control zone; Step 2: Based on the spatial topology and initial state score vector of each control area, and combined with the real-time temperature difference and wind speed direction between areas, construct a global thermal coupling map; Step 3: Based on the global thermal coupling map, perform thermal coupling analysis and state aggregation on each control region, update the initial state score vector, and generate a comprehensive global coupling state score for each control region; Step 4: Analyze and calculate the regional thermal interference deviation index by combining the initial state score vector of each control area with the global coupling state comprehensive score. Combine the overall distribution trend of the global coupling state comprehensive score to identify the thermal anomaly correlation attributes of each control area. Step 5: Based on the thermal anomaly correlation attributes and global thermal coupling map, and combined with the time series of global coupling state comprehensive scores of each control area at historical moments, perform spatial-temporal joint evolution analysis on each control area, and calculate the spatiotemporal joint thermal risk coefficient of each control area. Step 6: Select target intervention areas based on the spatiotemporal joint thermal risk coefficient, conduct intervention analysis and calculation based on thermal anomaly correlation attributes and global thermal coupling spectrum, and obtain the target intervention regulation index; Step 7: Based on the target intervention and control index, adjust the operating parameters of the target intervention area and its related areas, and correct the thermal interference deviation in real time.

[0041] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0042] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. An oven hot air control system, characterized in that, include: Initial state scoring module for each control zone: This module is used to collect multi-dimensional operating parameters of each independent control zone inside the oven, evaluate each operating parameter in conjunction with the target temperature, and generate an initial state scoring vector for each control zone. Thermal coupling map construction module: Based on the spatial topological relationship and initial state score vector of each control area, combined with the real-time temperature difference and wind speed direction between areas, a global thermal coupling map is constructed. Coupled State Aggregation Module: Based on the global thermal coupling map, thermal coupling analysis and state aggregation are performed on each control region, the initial state score vector is updated, and a comprehensive global coupled state score for each control region is generated. Thermal Interference Deviation Analysis Module: By analyzing and calculating the initial state score vector of each control area and the comprehensive score of the global coupling state, the regional thermal interference deviation index is obtained. Combined with the overall distribution trend of the comprehensive score of the global coupling state, the thermal anomaly correlation attributes of each control area are identified. Spatiotemporal joint risk assessment module: Based on thermal anomaly correlation attributes and global thermal coupling map, combined with the time series of global coupling state comprehensive scores of each control area at historical moments, spatial-temporal joint evolution analysis is performed on each control area to calculate the spatiotemporal joint thermal risk coefficient of each control area; Intervention Analysis Module: Target intervention areas are screened based on the spatiotemporal joint thermal risk coefficient, and intervention analysis and calculation are performed based on thermal anomaly correlation attributes and global thermal coupling map to obtain the target intervention regulation index; Coordinated regulation and deviation correction module: Based on the target intervention regulation index, the module regulates the operating parameters of the target intervention area and its related areas, and corrects thermal interference deviations in real time.

2. The oven hot air control system according to claim 1, characterized in that, The initial scoring module for the regional status uses temperature sensors, humidity sensors, wind speed sensors, wind direction sensors, wind pressure sensors, and infrared radiation sensors deployed in each independent control area to collect temperature, humidity, wind speed, wind direction, wind pressure, and thermal radiation intensity in each area in real time. The collected data is then processed sequentially by sliding window filtering, outlier removal, and normalization to obtain multidimensional operating parameters for each area. Each operating parameter is calculated with its corresponding target value to obtain an initial deviation value. The initial deviation value is then corrected based on the target temperature set by the oven to obtain the equivalent deviation of each parameter. Based on the equivalent deviation and the preset allowable deviation range, a single score for each parameter is generated. The single scores are then combined into an initial state score vector for each control area.

3. The oven hot air control system according to claim 2, characterized in that, The thermally coupled graph construction module maps each independent control area to a graph node and carries the corresponding initial state score vector. It extracts spatial topological relationships through physical layout, determines interaction paths between spatially adjacent control areas, and calculates a temperature difference driving factor based on the ratio of the real-time temperature difference between the two adjacent areas to the preset maximum allowable temperature difference for two adjacent control areas directly connected by the interaction path. It calculates a wind speed direction factor based on the cosine similarity between the wind direction of the air outlet of one of the adjacent areas and the direction of the interaction path. It calculates a state score modulation factor based on the smaller value of the comprehensive score of the initial state score vectors of the two adjacent areas. Then, it performs a weighted calculation on the temperature difference driving factor, the wind speed direction factor, and the state score modulation factor to obtain the relationship weight corresponding to the interaction path. Finally, it constructs a global thermally coupled graph with each control area as a graph node, the interaction path as a directed edge, and the calculated relationship weight as the directed edge weight.

4. The oven hot air control system according to claim 3, characterized in that, The coupling state aggregation module is used to filter all incident directed edges with the target node as the endpoint for any target node in the global thermal coupling graph, and obtain the source node and relation weight corresponding to each incident directed edge. Calculate the product of the comprehensive score of the initial state score vector of each source node and the corresponding incident directed edge relation weight, and sum all products to obtain the global coupling influence value of the target node; fuse the global coupling influence value of the target node with the comprehensive score of the initial state score vector of the target node to generate the global coupling state comprehensive score of the node, and use the global coupling state comprehensive score to modulate and update the scores of each dimension in the initial state score vector of the node; traverse all nodes in the global thermal coupling graph to complete state aggregation, and obtain the updated global coupling state comprehensive score of each control region.

5. The oven hot air control system according to claim 4, characterized in that, The thermal interference deviation analysis module is used to calculate the absolute value of the difference between the comprehensive score of the global coupling state of each control area and the comprehensive score of the initial state score vector, so as to obtain the regional thermal interference deviation index; and to calculate the mean and variance of the comprehensive score of the global coupling state of all control areas to evaluate the overall global distribution trend. The thermal interference significance coefficient of this region is calculated based on the ratio of the thermal interference deviation index of this region to the variance of the comprehensive score of the global coupling state of all control regions. For any control region, when the thermal interference significance coefficient of the region is greater than the preset significance threshold, the thermal anomaly association attribute is identified based on the relationship between the comprehensive score of the global coupling state of the region and the comprehensive score of the initial state score vector. If the comprehensive score of the global coupling state is less than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a disturbance attenuation zone. If the comprehensive score of the global coupling state is greater than the comprehensive score of the initial state score vector, the thermal anomaly association attribute of the region is identified as a heat excess dissipation zone.

6. The oven hot air control system according to claim 5, characterized in that, The spatiotemporal joint risk assessment module is used to extract the comprehensive score of the global coupling state of each control area within a preset historical time window to form a time series, calculate the rate of change of the time series, and obtain the time series evolution trend value of each control area. For any control region, the corresponding relation weights are obtained based on the global thermal coupling map. The spatial risk calculation strategy is determined according to the thermal anomaly correlation attributes of the region. If it is a heat excess dispersion zone, the cumulative sum of the relation weights of all outgoing directed edges starting from the region is calculated. If it is a disturbance attenuation zone, the cumulative sum of the relation weights of all incoming directed edges ending from the region is calculated. The obtained cumulative sum is multiplied by the thermal interference significance coefficient of the region to obtain the spatial evolution status value of the control region. The temporal evolution trend value and the spatial evolution status value of each control region are weighted and calculated to obtain the spatiotemporal joint thermal risk coefficient of each control region.

7. The oven hot air control system according to claim 6, characterized in that, The intervention analysis module is used to filter control areas with a spatiotemporal joint thermal risk coefficient greater than a preset risk threshold as target intervention areas; For any target intervention area, the difference between the comprehensive score of its initial state score vector and the comprehensive score of the global coupled state is calculated, and this difference is multiplied by the spatiotemporal joint thermal risk coefficient of the area to obtain the basic intervention amount. Based on the thermal anomaly correlation attribute of the area and the global thermal coupling map, the spatial intervention modulation factor is calculated. If it is a heat excess dispersion area, the average value of the weights of all outgoing directed edge relationships starting from the area is calculated as the spatial spillover modulation factor. If it is a disturbance attenuation area, the average value of the weights of all incoming directed edge relationships ending from the area is calculated as the spatial intrusion modulation factor. The target intervention regulation index for the target intervention area is obtained by fusing the basic intervention amount with the corresponding spatial intervention modulation factor.

8. The oven hot air control system according to claim 7, characterized in that, The coordinated regulation and deviation correction module is used to calculate the regulation increment of the operating parameters of the target intervention area based on the target intervention regulation index; Based on the global thermal coupling map, the associated regions with directed edge connections to the target intervention area and their corresponding relation weights are extracted. The operational parameter control increment is multiplied by the corresponding relation weights to obtain the collaborative control increment of each associated region. The hot air operating parameters are simultaneously adjusted in the target intervention area and related areas according to the incremental adjustment of operating parameters and the incremental adjustment of coordinated control. After the adjustment cycle, the operating parameters are collected again, the comprehensive score of global coupling state is updated and the thermal interference deviation index is recalculated to complete the real-time closed-loop correction.

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