Multifunctional furnace body intelligent control and monitoring system

Abstract

The invention discloses a multifunctional furnace body intelligent control and monitoring system, and relates to the technical field of furnace body monitoring. The multifunctional furnace body intelligent control and monitoring system comprises a multifunctional furnace body oil smoke concentration distribution uniformity monitoring module; a temperature data acquisition accuracy monitoring module; a temperature adjusting signal transmission timeliness monitoring module; and a heating uniformity monitoring module. According to the method, whether the rotating speed of the oil smoke exhaust fan is adjusted or not is judged, then whether temperature measurement value fluctuation suppression optimization is adopted or not is judged based on a temperature data acquisition accuracy analysis result, and then whether transmission frequency band self-adaptive switching optimization is adopted or not is judged; and finally, whether heating uniformity dynamic matching regulation is performed or not is judged based on the heating uniformity evaluation result, the effect of improving the accuracy of the intelligent monitoring data of the multifunctional furnace body is achieved, and the problem that the accuracy of the intelligent monitoring data of the multifunctional furnace body is low due to oil smoke accumulation in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of furnace body monitoring technology, and in particular to a multifunctional intelligent control and monitoring system for furnace bodies. Background Technology

[0002] By integrating sensors for temperature, pressure, and gas concentration to collect real-time operating data inside the furnace for anomaly detection and status prediction, the system automatically compares preset process parameters and dynamically adjusts heating power, ventilation volume, and material feeding rhythm, ultimately achieving closed-loop control and energy efficiency optimization throughout the entire process from raw material input to finished product output.

[0003] Existing technologies for intelligent control and monitoring of multi-functional ovens involve installing multiple temperature sensors within the oven to collect real-time temperatures in various areas. By analyzing these sensors, key temperatures are obtained, generating a periodic temperature curve. This curve is then compared with a pre-set temperature curve to determine the current state of the multi-functional oven. Based on the adjustment amounts between the current and pending states, and combined with the oven's energy efficiency data, a precise state transition time is calculated. This timeline is then used to send adjustment commands to the oven's heating elements, ventilation devices, and other components, ultimately completing the entire baking process.

[0004] For example, Chinese invention patent CN119717585A discloses a cooking control method and device for an intelligent barbecue oven based on a multi-sensor combination. This method includes: deploying multiple sensors such as temperature and oil fume concentration on the barbecue oven to collect real-time environmental parameters and food status data during the cooking process; transmitting the collected data to the barbecue oven control center for analysis and processing; combining preset cooking recipe parameters and food type; calculating and generating corresponding control commands such as heating power, fan speed, and grill rotation speed; driving the heating device, smoke exhaust system, transmission mechanism, and other execution components of the barbecue oven to work together; and continuously monitoring the deviation between sensor data and preset thresholds during the cooking process to dynamically adjust the control commands.

[0005] For example, Chinese invention patent CN117872982A discloses a rotary hearth furnace control method and system based on in-furnace flue gas analysis. The method includes: setting up a flue gas detection device in the rotary hearth furnace to collect flue gas composition and concentration data in real time; transmitting the collected data to the rotary hearth furnace control center for analysis and processing; and establishing a correlation model between flue gas composition and in-furnace reaction state by combining the operating parameters of the rotary hearth furnace, such as furnace temperature, material feeding speed, and fuel supply. The model is used to calculate and determine whether the current in-furnace reaction is in an optimal state. If there is a deviation, a corresponding adjustment command is generated to dynamically adjust parameters such as fuel supply, air volume, and material conveying speed. At the same time, the adjusted flue gas data and in-furnace state are continuously monitored.

[0006] The above-mentioned technology has at least the following technical problems:

[0007] Multifunctional furnace intelligent monitoring systems are typically used for extended periods, resulting in significant oil fume accumulation. During the continuous internal circulation combustion of charcoal, the obstruction on top of the charcoal barrel module hinders some of the upward airflow, causing oil fumes to accumulate locally below the obstructed area. This accumulation interferes with the internal circulation airflow. Furthermore, the hexagonal furnace structure may create localized airflow dead zones, making it difficult for the multifunctional furnace control center to accurately determine the actual amount of oil fume generated. This leads to malfunctions in the start / stop and intensity adjustment of the exhaust system, which in turn interferes with the wireless transmission of temperature control signals. Consequently, the transmission of temperature control signals to the multifunctional furnace control center is delayed, resulting in low accuracy of the multifunctional furnace intelligent monitoring data due to oil fume accumulation. Summary of the Invention

[0008] To address the problem of low accuracy in intelligent monitoring data of multi-functional furnaces due to oil fume accumulation in existing technologies, this invention provides an intelligent control and monitoring system for multi-functional furnaces. This application provides an intelligent control and monitoring system for multi-functional furnaces, including: a multi-functional furnace oil fume concentration distribution uniformity monitoring module, a temperature data acquisition accuracy monitoring module, a temperature adjustment signal transmission timeliness monitoring module, and a heating uniformity monitoring module. The multi-functional furnace oil fume concentration distribution uniformity monitoring module is used to assess the degree of oil fume accumulation in the multi-functional furnace during intelligent monitoring. Based on the assessment result, it determines whether to adjust the exhaust fan speed. The exhaust fan speed adjustment is used to improve oil fume emission efficiency by dynamically adjusting the exhaust fan speed. The temperature data acquisition accuracy monitoring module is used to, after the assessment of the oil fume accumulation degree in the multi-functional furnace is deemed satisfactory, determine whether to adjust the exhaust fan speed based on the temperature data... The accuracy analysis results are used to determine whether temperature measurement fluctuation suppression optimization is needed. This optimization reduces abnormal temperature data fluctuations caused by oil fume interference. The timeliness monitoring module for temperature regulation signal transmission is used to determine whether adaptive switching optimization of transmission frequency band is needed after the temperature data acquisition accuracy analysis is qualified. This optimization reduces transmission delay caused by oil fume interference. The heating uniformity monitoring module is used to determine whether dynamic matching control of heating uniformity is needed after the timeliness assessment of temperature regulation signal transmission is qualified. This dynamic matching control of heating uniformity is used to improve the control accuracy of furnace heating uniformity.

[0009] The beneficial effects of the technical solutions provided by the embodiments of the present invention include at least the following:

[0010] 1. By assessing the degree of oil fume accumulation in the multi-functional furnace, the system determines whether adjusting the exhaust fan speed is necessary. This helps break the imbalance between localized oil fume accumulation and airflow collision, reducing airflow dead zones formed by the hexagonal furnace structure. This allows the multi-functional furnace control center to accurately monitor the actual amount of oil fume generated, preventing start-up, shutdown, and intensity adjustment disorders in the exhaust system due to misjudgment. This reduces interference from oil fume on monitoring data at the source. After the assessment of oil fume accumulation in the multi-functional furnace is deemed satisfactory, the system analyzes the accuracy of temperature data acquisition to determine whether temperature measurement fluctuation suppression optimization is needed. This improves the accuracy of temperature data acquisition, ensuring that the acquired temperature data accurately reflects the actual temperature inside the furnace, providing reliable data for subsequent temperature adjustments. Based on the accuracy analysis of temperature data acquisition, the system determines whether to adopt adaptive switching optimization of transmission frequency band based on the timeliness evaluation results of temperature regulation signal transmission. This helps reduce the temperature regulation signal transmission delay caused by oil fume interference. By adapting to the optimal transmission frequency band, it ensures that the temperature regulation signal can be transmitted to the multi-functional furnace control center in a timely and stable manner. After the timeliness evaluation of temperature regulation signal transmission is qualified, the system determines whether dynamic matching control of heating uniformity is needed based on the heating uniformity evaluation results. This helps to intelligently adjust the rotation speed of the rotating rack, reduce the problem of uneven heating of food caused by local temperature imbalance, and improve the accuracy of intelligent monitoring data of the multi-functional furnace. This effectively solves the problem of low accuracy of intelligent monitoring data of multi-functional furnaces caused by oil fume accumulation in the existing technology.

[0011] 2. By quantifying the proportion of temperature data acquisition parameters with standard temperature data acquisition parameters retrieved from the database, the offset of temperature data acquisition parameters is obtained. Based on the offset of temperature data acquisition parameters and the influence value of temperature data acquisition weights, a weighted fusion is performed to obtain the temperature data acquisition deviation index. This helps to overcome the inaccuracy caused by relying on a single parameter in the existing technology, forming a precise quantitative assessment of the accuracy of temperature data acquisition. Based on the temperature data acquisition deviation index, it is determined whether temperature measurement value fluctuation suppression optimization is needed. This helps to promptly detect and solve the problem of excessive temperature data acquisition deviation, ensuring the accuracy of the acquired data. Thus, precise control of the temperature data acquisition process is achieved, providing a reliable data foundation for the intelligent monitoring of multi-functional furnace bodies.

[0012] 3. By assigning weights to the temperature regulation signal transmission delay deviation and the qualified temperature data acquisition deviation index, respectively, along with the corresponding temperature regulation signal weight parameters, a weighted value for the temperature regulation signal parameters is obtained. This helps to address the one-sidedness of evaluating signal transmission status solely through a single indicator in existing technologies. It also avoids evaluation distortion caused by ignoring the impact of temperature data acquisition accuracy on signal transmission. By combining the different degrees of influence of the two parameters on the timeliness of signal transmission and assigning corresponding weight proportions, the influence of each parameter is reasonably quantified. The weighted value of the temperature regulation signal parameters is then harmonicly averaged to obtain a quantitative index for the timeliness of temperature regulation signal transmission. This helps to form a quantitative index that comprehensively reflects the matching degree between the response efficiency of the entire signal transmission link and the reliability of data acquisition through the weighted value of the temperature regulation signal parameters. Based on the quantitative index for the timeliness of temperature regulation signal transmission, it is possible to determine whether to adopt adaptive switching optimization of the transmission frequency band. This helps to specifically solve the problem of temperature regulation signal transmission efficiency, ensuring that the temperature regulation signal can efficiently and reliably act on the furnace heating control, thereby achieving precise control over the entire process of temperature regulation signal transmission. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of the structure of a multifunctional intelligent control and monitoring system for a furnace body provided in an embodiment of the present invention;

[0015] Figure 2 This is a flowchart outlining the general overview of a multifunctional intelligent control and monitoring system for a furnace body provided in an embodiment of the present invention.

[0016] Figure 3 This is a transmission frequency band adaptive switching optimization logic diagram of a multifunctional furnace body intelligent control and monitoring system provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0018] like Figure 1 The diagram shown is a structural schematic of a multifunctional intelligent control and monitoring system for a furnace body provided in an embodiment of the present invention. The multifunctional intelligent control and monitoring system for a furnace body includes: a multifunctional furnace body oil fume concentration distribution uniformity monitoring module, a temperature data acquisition accuracy monitoring module, a temperature regulation signal transmission timeliness monitoring module, and a heating uniformity monitoring module.

[0019] The multi-functional furnace body oil fume concentration distribution uniformity monitoring module is used to assess the degree of oil fume accumulation in the multi-functional furnace body during intelligent monitoring. Based on the assessment results, it determines whether the exhaust fan speed needs to be adjusted. The exhaust fan speed adjustment is used to improve oil fume emission efficiency and reduce interference with intelligent monitoring data by dynamically adjusting the exhaust fan speed. By monitoring the assessment results of the oil fume accumulation in the multi-functional furnace body, it is helpful to adjust the exhaust fan speed in a timely manner to reduce the interference of oil fumes on subsequent monitoring links, and provide a stable environmental foundation for the entire intelligent monitoring process of the multi-functional furnace body.

[0020] The temperature data acquisition accuracy monitoring module is used to determine whether temperature measurement fluctuation suppression optimization is needed based on the temperature data acquisition accuracy analysis results after the multi-functional furnace body oil fume accumulation degree assessment is qualified. Temperature measurement fluctuation suppression optimization is used to reduce abnormal temperature data fluctuation interference caused by oil fume interference, and improve the stability and accuracy of temperature acquisition data. By monitoring the temperature data acquisition accuracy analysis results, it helps to further ensure the stability and accuracy of temperature data acquisition after oil fume interference is reduced, and provides reliable data support for subsequent temperature adjustment signal transmission.

[0021] The temperature regulation signal transmission timeliness monitoring module is used to determine whether to adopt adaptive switching optimization of the transmission frequency band based on the temperature regulation signal transmission timeliness evaluation results after the temperature data acquisition accuracy analysis is qualified. The adaptive switching optimization of the transmission frequency band is used to reduce the transmission delay caused by oil fume interference and improve the real-time performance and reliability of temperature regulation signal transmission. By monitoring the temperature regulation signal transmission timeliness evaluation results, it helps to reduce the temperature regulation signal transmission delay on the basis of accurate temperature data, ensure the efficient transmission of temperature regulation signals, and provide timely signal support for the dynamic matching control of heating uniformity.

[0022] The heating uniformity monitoring module is used to determine whether dynamic matching control of heating uniformity is needed based on the heating uniformity assessment results after the timeliness assessment of temperature regulation signal transmission is qualified. By monitoring the heating uniformity assessment results, it helps to accurately control the heating uniformity of the furnace body under the premise of timely signal transmission, and ultimately improves the control accuracy of the heating uniformity of the furnace body.

[0023] It should be noted that a database storing various set data was established before the design of the multifunctional furnace body intelligent control and monitoring system provided in this application. The database includes, but is not limited to, standard oil fume particulate matter concentration values, standard temperature sensor surrounding airflow velocity deviation values, standard temperature measurement value fluctuation amplitude deviation values, standard multifunctional furnace body oil fume accumulation degree index, temperature adjustment signal transmission timeliness threshold, rotating rack speed adjustment threshold, heating uniformity threshold range, etc. Among them, various preset values ​​are directly set by technical personnel.

[0024] The multifunctional furnace body provided in this embodiment includes a furnace body structure module, a rotating module, a carbon barrel module, a firepower adjustment module, and a toxic gas alarm module. The furnace body structure module consists of six interlocking furnace wall units, each with protruding buckles and recessed slots on its sides. The buckles and slots are precisely matched in size, allowing for tight engagement of adjacent furnace wall units by manual pressing. After assembly, a stable hexagonal three-dimensional structure is formed, ensuring the furnace body has sufficient load-bearing capacity. The rotating module includes a rotating frame, a gear rod, and a rotating motor. The rotating frame has a circular frame structure with multiple evenly distributed frame holes along its edge. Elastic buckles are positioned below each hole. The gear rod surface is precision-threaded. One end connects to the central threaded hole of the rotating frame, and the other end is linked to the output shaft of the rotating motor through gear meshing. The rotating motor is a DC geared motor, and its rated speed can be adjusted through the multi-functional furnace body control center. It has an overload protection function and automatically stops when the load exceeds the set value. The carbon barrel module adopts a double-layer stainless steel structure with an air insulation layer between the two layers. The top edge is folded outward to form a load-bearing edge. The bottom of the barrel is equipped with a ventilation mesh to facilitate air circulation. A pull-out ash collection box is installed on one side of the barrel wall for easy cleaning of combustion residue. The firepower adjustment module consists of a fan, a fan motor, and a control switch. The fan is an axial flow fan, which is fixed to the ventilation opening on the side of the furnace body by a bracket. The fan motor is an AC asynchronous motor, and its speed can be adjusted via a signal output from the multi-functional furnace control center. The control switch uses waterproof touch buttons integrated into the control panel, supporting manual start / stop and speed adjustment. Simultaneously, the remote control unit has a built-in wireless communication module, allowing wireless connection to a mobile app or smart control terminal for remote fan start / stop and motor speed adjustment. Remote control commands are executed after verification by the multi-functional furnace control center, and the current operating status is fed back to the control terminal in real time. The toxic gas monitoring module consists of a gas sensor group, signal amplification circuit, microprocessor, and alarm device. The gas sensor group includes a carbon monoxide sensor and a methane sensor. The high-temperature support is installed inside the furnace body, above, away from the flame zone but close to areas where gas tends to accumulate. The signal amplification circuit amplifies and filters the weak electrical signal output by the sensor before transmitting it to the microprocessor. The microprocessor compares the toxic gas detection value with the preset safety threshold in real time. When the toxic gas detection value exceeds the preset safety threshold, the alarm device is immediately activated, emitting a buzzer alarm sound. At the same time, the red warning light on the control panel flashes at a high frequency. The multi-functional furnace control center also links with the firepower adjustment module to reduce the fan speed or stop the fan, and the rotation module stops operating to reduce the generation and diffusion of harmful gases. Simultaneously, the alarm information is pushed to the bound control terminal via the wireless communication module to remind the user to take timely action.

[0025] The core process of intelligent control and monitoring of the multi-functional oven includes: first, assembling the hexagonal oven body, installing the rotating skewer rack, and placing the charcoal bucket; then fixing the skewers, placing the teapot as needed, and setting the target temperature in the control module; after starting the multi-functional oven, the rotating skewer rack automatically rotates to ensure even heating of the food, and the temperature sensor monitors the oven temperature in real time, while the multi-functional oven control center controls the temperature by adjusting the fan speed; during the grilling process, the temperature can be manually adjusted, and functions such as brewing tea, grilling meat, and boiling water can be performed simultaneously; after grilling is completed, the multi-functional oven control center issues a prompt, and the grilling personnel turn off the multi-functional oven, remove the food and teapot, etc., and disassemble, clean, and store the components after cooling.

[0026] like Figure 2 The diagram shown is a general overview flowchart of a multifunctional intelligent control and monitoring system for a furnace body provided in an embodiment of the present invention. Figure 2 It can be seen that during the intelligent monitoring of the multi-functional furnace body, the degree of oil fume accumulation in the multi-functional furnace body is assessed, and it is determined whether the acquired oil fume accumulation index is less than the preset standard oil fume accumulation threshold. If so, a furnace heating qualified prompt is sent, and temperature data acquisition accuracy analysis is performed; otherwise, the exhaust fan speed is adjusted. After the assessment of the degree of oil fume accumulation in the multi-functional furnace body is qualified, temperature data acquisition accuracy analysis is performed, and it is determined whether the acquired temperature data acquisition deviation index is less than the preset temperature data acquisition safety deviation threshold. If so, the stability of temperature adjustment signal transmission is assessed; otherwise, temperature adjustment is implemented. The measurement fluctuation suppression optimization involves evaluating the timeliness of temperature regulation signal transmission after the temperature data acquisition accuracy analysis is qualified. It then determines whether the quantitative index of the acquired temperature regulation signal transmission timeliness is less than the preset temperature regulation signal transmission timeliness threshold. If so, it evaluates the heating uniformity; otherwise, it adopts adaptive switching optimization of transmission frequency band. After the temperature regulation signal transmission timeliness evaluation is qualified, it evaluates the heating uniformity and determines whether the acquired heating uniformity deviation index is within the preset heating uniformity threshold range. If so, it sends a heating uniformity qualified prompt; otherwise, it performs dynamic matching control of heating uniformity.

[0027] In this embodiment, the multi-functional furnace body oil fume concentration uniformity monitoring module, temperature data acquisition accuracy monitoring module, temperature regulation signal transmission timeliness monitoring module, and heating uniformity monitoring module form a progressive closed-loop control process through data transmission and process connection. The evaluation result of the multi-functional furnace body oil fume concentration uniformity monitoring module serves as a prerequisite for the temperature data acquisition accuracy monitoring module. By adjusting the speed of the exhaust fan, the interference of oil fumes on temperature data acquisition is reduced, providing a more stable monitoring environment for subsequent modules. After the multi-functional furnace body oil fume accumulation degree assessment is qualified, the temperature data acquisition accuracy monitoring module performs accuracy analysis on the temperature data and... The optimization provides a precise and reliable temperature data foundation for the temperature regulation signal transmission timeliness monitoring module. Based on qualified temperature data, the temperature regulation signal transmission timeliness monitoring module evaluates and optimizes signal transmission, ensuring efficient transmission of temperature regulation signals and providing stable temperature regulation signal support for the heating uniformity monitoring module. The heating uniformity monitoring module then performs dynamic matching control of heating uniformity based on the qualified results from the temperature regulation signal transmission timeliness monitoring module. This achieves end-to-end quality control of the multi-functional oven, from environmental optimization to oven heating uniformity control, effectively improving the accuracy of intelligent monitoring of the multi-functional oven and the stability of baking results.

[0028] Furthermore, the specific process for assessing the degree of oil fume accumulation in the multi-functional furnace is as follows: The degree of oil fume accumulation in the multi-functional furnace is obtained as an index. This index is represented by the quantified deviation between the concentration values ​​of oil fume particles in the preset monitoring areas within the furnace and the preset standard concentration values. A higher index indicates greater interference from oil fume accumulation on temperature data monitoring. The preset monitoring areas are pre-defined by designated personnel. Distributed oil fume sensors monitor the total number of oil fume particles per unit volume in each preset monitoring area, and the average value is used as the oil fume particle concentration. The index reflects the degree of interference from oil fume accumulation on temperature data monitoring. It is then determined whether the index is lower than the preset standard oil fume accumulation threshold, which is represented by the average value of the index over a historical time period. If so, a furnace heating qualification notification is sent, and temperature data acquisition accuracy analysis is performed; otherwise, the exhaust fan speed is adjusted.

[0029] Specifically, the process for adjusting the exhaust fan speed is as follows: AA1, the oil fume accumulation level index and oil fume temperature of the multi-functional furnace are input into the dynamic correction set of the exhaust fan speed in the database for correction. The preset exhaust fan speed adjustment coefficient is retrieved from the database. The oil fume temperature is monitored by an oil fume temperature sensor. The database contains a correction set that reflects the correspondence between the combination of the oil fume accumulation level index and the oil fume temperature of the multi-functional furnace and the corresponding preset exhaust fan speed adjustment coefficient; AA2, the preset exhaust fan speed adjustment coefficient boundary verification is performed: it is determined whether the exhaust fan speed adjustment coefficient exceeds the preset maximum adjustment threshold, which is set in advance by the preset personnel; if so, an exhaust overload alarm is sent; otherwise, the corresponding exhaust fan speed adjustment coefficient is marked as a valid exhaust fan speed adjustment value; AA3, the effective exhaust fan speed adjustment value corresponds to the amplitude... As an adjustment step, gradually increasing the exhaust fan speed helps reduce the impact of sudden changes in exhaust fan speed on the stability of airflow inside the furnace. The exhaust fan speed does not exceed the preset exhaust fan speed adjustment threshold, which is set in advance by a designated person. AA4, after the exhaust fan speed adjustment is completed, if the newly acquired multi-functional furnace body oil fume accumulation degree index is not less than the multi-functional furnace body oil fume accumulation degree index of the previous preset oil fume concentration distribution uniformity time period, and the multi-functional furnace body oil fume accumulation degree index is not less than the preset multi-functional furnace body oil fume accumulation degree index, then an exhaust fan optimization alarm is sent; otherwise, temperature data acquisition accuracy analysis is performed. The preset oil fume concentration distribution uniformity time period represents the time period during which the previous multi-functional furnace body oil fume accumulation degree assessment was conducted. The preset multi-functional furnace body oil fume accumulation degree index is represented by the average value of the multi-functional furnace body oil fume accumulation degree index over historical time periods.

[0030] In this embodiment, by assessing the degree of oil fume accumulation in the multi-functional furnace, it is helpful to determine the degree of local oil fume accumulation below the shielded area. This enables reasonable handling of local oil fume accumulation in the shielded area and abnormal distribution in airflow dead zones. The quantitative indicators intuitively reflect the degree of deviation between the oil fume diffusion pattern and the standard state, ensuring that when the oil fume distribution exceeds the threshold, the exhaust fan speed can be adjusted in time to reduce airflow collision and dead zone accumulation. When the oil fume distribution is qualified, the furnace heating state is stabilized, effectively improving the multi-functional furnace's dynamic control capability for oil fume distribution. This reduces the interference of oil fume accumulation on intelligent monitoring data from the source, laying the foundation for the accuracy of subsequent temperature acquisition, temperature adjustment signal transmission, and uniform heating control.

[0031] Furthermore, the specific process of temperature data acquisition accuracy analysis is as follows: First, by quantifying the proportion of temperature data acquisition parameters with standard temperature data acquisition parameters retrieved from the database, the offset of temperature data acquisition parameters is obtained. Here, proportion quantization means performing ratio calculation.

[0032] Specifically, the expression for the airflow velocity deviation rate around the temperature sensor is as follows:

[0033] P = 1, 2, ..., H, where P represents the number of the preset analysis time period, H is the total number of preset analysis time periods, and A 1 (P) represents the airflow velocity deviation rate around the temperature sensor during the Pth preset analysis time period, A(P) represents the airflow velocity deviation value around the temperature sensor during the Pth preset analysis time period, and A(0) represents the airflow velocity deviation value around the standard temperature sensor. The actual airflow velocity at the preset location point in the furnace during the preset analysis time period is monitored by the airflow velocity sensor, and the difference between its average value and the center value of the standard airflow velocity range is taken as the airflow velocity deviation value around the temperature sensor. The units of the airflow velocity deviation value around the temperature sensor and the airflow velocity deviation value around the standard temperature sensor are both meters per second.

[0034] Specifically, the expression for the deviation rate of temperature measurement fluctuation is as follows: B 1 (P) represents the temperature measurement fluctuation deviation rate during the Pth preset analysis time period, B(P) represents the temperature measurement fluctuation deviation value during the Pth preset analysis time period, and B(0) represents the standard temperature measurement fluctuation deviation value. The temperature value of the preset location point in the furnace is monitored by the temperature sensor during the preset analysis time period, and the difference between its maximum and minimum values ​​is taken as the temperature measurement fluctuation deviation value. The units of the temperature measurement fluctuation deviation value and the standard temperature measurement fluctuation deviation value are both in degrees Celsius.

[0035] Specifically, the expression for the deviation rate of oil fume concentration distribution in a multi-functional furnace is as follows: C 1 (P) represents the deviation rate of oil fume concentration distribution in the Pth preset analysis time period, C(P) represents the qualified oil fume accumulation index of the Pth preset analysis time period, and C(0) represents the standard oil fume accumulation index of the Pth preset analysis time period. The oil fume accumulation index of the Pth preset analysis time period is taken as the qualified oil fume accumulation index of the Pth preset analysis time period. The units of the qualified oil fume accumulation index and the standard oil fume accumulation index of the Pth preset analysis time period are both units / cubic meter.

[0036] Secondly, the temperature data acquisition parameter offset and the influence value of the temperature data acquisition weight are weighted and fused to obtain the temperature data acquisition deviation index, which is used to reflect the effect of temperature data acquisition parameters on the accuracy of temperature data acquisition results.

[0037] The temperature data acquisition deviation index was obtained through the following method:

[0038] D(P) = A 1 (P)×w1+B 1 (P)×w2+C 1 (P)×w3

[0039] In the formula, D(P) represents the temperature data acquisition deviation index for the Pth preset analysis time period, w1 represents the weight influence value of the airflow velocity around the temperature sensor, w2 represents the weight influence value of the temperature measurement fluctuation amplitude, and w3 represents the weight influence value of the oil fume concentration distribution of the multi-functional furnace.

[0040] The temperature data acquisition parameters include the airflow velocity deviation around the temperature sensor, the temperature measurement fluctuation range deviation, and the oil fume accumulation level index of the qualified multi-functional furnace body. The standard temperature data acquisition parameters include the airflow velocity deviation around the standard temperature sensor, the temperature measurement fluctuation range deviation, and the standard multi-functional furnace body oil fume accumulation level index. The airflow velocity deviation around the standard temperature sensor is represented by the average value of the airflow velocity deviation around the temperature sensor over a historical period. The temperature measurement fluctuation range deviation is represented by the average value of the temperature measurement fluctuation range deviation over a historical period. The standard multi-functional furnace body oil fume accumulation level index is represented by the average value of the multi-functional furnace body oil fume accumulation level index over a historical period. The temperature data acquisition parameter offsets include the airflow velocity deviation rate around the temperature sensor, the temperature measurement fluctuation range deviation rate, and the oil fume concentration distribution deviation rate of the multi-functional furnace body.

[0041] Determine whether the temperature data acquisition deviation index is less than the preset temperature data acquisition safety deviation threshold, which is represented by the average value of the temperature data acquisition deviation index over a historical period. If so, perform a temperature regulation signal transmission stability assessment; otherwise, optimize the temperature measurement value fluctuation suppression.

[0042] It should be added that the influence values ​​of temperature data acquisition weights include the influence values ​​of airflow velocity around the temperature sensor, temperature measurement fluctuation amplitude, and oil fume concentration distribution in the multi-functional oven. These are used to reflect the degree of influence of temperature data acquisition parameter offsets on the temperature data acquisition deviation index. In this embodiment, there is a mapping group obtained from the database. This mapping group contains mapping sets, which are preset by professional technicians. The mapping relationships are in a one-to-one or many-to-one form to accurately reflect the degree of influence of different temperature data acquisition parameter offsets on the temperature data acquisition deviation index under different baking scenarios.

[0043] Specifically, by establishing a mapping relationship between the deviation quantification results of temperature data acquisition parameter offset and standard temperature data acquisition parameters and the influence value of temperature data acquisition weight, and using the 0-1 value range to represent the weight ratio, when the multi-functional furnace control center receives the deviation quantification results of temperature data acquisition parameter offset and standard temperature data acquisition parameters, it can quickly retrieve the corresponding temperature data acquisition weight influence value from the pre-built mapping group, thereby accurately quantifying the influence degree of each temperature data acquisition parameter offset on the temperature data acquisition deviation index, thus improving the accuracy and adaptability of the multi-functional furnace temperature data acquisition accuracy analysis.

[0044] In this embodiment, the various parameters involved in temperature data acquisition accuracy analysis are closely related, and their synergistic effect is crucial to the accuracy analysis. The deviation of the acquired temperature data parameters from the standard temperature data acquisition parameters is quantified to obtain the temperature data acquisition parameter offset. This offset is then combined with the corresponding temperature data acquisition weight influence value to transform it into a quantifiable temperature data acquisition deviation index. Specifically, the larger the temperature data acquisition deviation index, the more significant the overall impact of the parameter offsets on the accuracy of temperature data acquisition, potentially leading to greater errors in subsequent temperature regulation signal transmission and heating control. Through weighted fusion quantization, a standardized mapping of multi-dimensional acquisition parameters is achieved, effectively avoiding the limitations of single-parameter evaluation.

[0045] Parameter correlation analysis in temperature data acquisition accuracy analysis can accurately capture the comprehensive impact of multiple parameters on data acquisition accuracy. The deviation rate of airflow velocity around the temperature sensor and the deviation rate of temperature measurement fluctuation amplitude typically show a positive correlation: a larger deviation rate of airflow velocity around the temperature sensor indicates poorer stability of the surrounding environment, potentially leading to a larger deviation rate of temperature measurement fluctuation amplitude. When both the deviation rate of airflow velocity around the temperature sensor and the deviation rate of temperature measurement fluctuation amplitude increase, the added influence of the deviation rate of oil fume concentration distribution in the multi-functional furnace further amplifies the temperature data acquisition deviation index. This increased deviation index, in turn, affects the parameter acquisition process, potentially making parameter deviations more difficult to control, creating a vicious cycle and ultimately affecting the stability of temperature regulation signal transmission. When the oil fume concentration distribution deviation rate of the multi-functional furnace body decreases, that is, when the oil fume concentration distribution is more uniform, it will reduce the adhesion and interference to the temperature sensor, which will help reduce the deviation rate of temperature measurement fluctuation. At the same time, stable oil fume emission can also reduce airflow turbulence, reduce the deviation rate of airflow velocity around the temperature sensor, and thus reduce the temperature data acquisition deviation index, providing a guarantee for the accuracy of temperature data acquisition and forming a virtuous cycle. Through the correlation analysis between parameters, it is beneficial to quantify the comprehensive impact of multiple parameters on the accuracy of temperature data acquisition, improve the comprehensiveness and accuracy of temperature data acquisition accuracy analysis, and provide a reliable decision basis for optimizing temperature regulation signal transmission and heating control.

[0046] Further, the specific process for optimizing temperature measurement fluctuation suppression is as follows: The temperature data acquisition deviation index and the temperature sensor operating voltage deviation value are input into the dynamic correction set of the filter window width in the database for correction. The corresponding preset filter window width adjustment coefficient is retrieved. The temperature sensor operating voltage at the preset location point is monitored in real-time by a high-precision voltage sampling chip, and the difference between this voltage and the preset standard operating voltage is taken as the temperature sensor operating voltage deviation value. The database contains a correction set reflecting the combination of the temperature data acquisition deviation index and the temperature sensor operating voltage deviation value, and the corresponding preset filter window width adjustment coefficient. The preset filter window width adjustment coefficient does not exceed the preset maximum filter window width threshold, which is set in advance by the user. Using the amplitude corresponding to the preset filter window width adjustment coefficient as the adjustment step size, the sliding filter window width is gradually increased, which helps suppress temperature measurement fluctuations. This specifically addresses the problem of unstable temperature measurements caused by data acquisition deviations and abnormal sensor voltages. By dynamically adjusting the filter window width, temperature data fluctuations are accurately smoothed, allowing the temperature acquisition deviation index to quickly converge towards the preset safe deviation threshold for temperature data acquisition. The process involves several steps: First, determining whether the number of optimization attempts for suppressing temperature fluctuations exceeds the preset maximum number of attempts. If the number of optimization attempts does not exceed the preset maximum number of attempts, the optimization continues until the temperature data acquisition deviation index of the multi-functional furnace body is less than the temperature data acquisition deviation index of the multi-functional furnace body during the previous preset temperature data acquisition and analysis period. At this point, a timeliness assessment of the temperature regulation signal transmission is performed. The preset maximum number of optimization attempts is set in advance by designated personnel, and the preset temperature data acquisition and analysis period represents the time period for temperature data acquisition and analysis. Second, if the number of optimization attempts exceeds the preset maximum number of attempts, but the monitored temperature data acquisition deviation index of the multi-functional furnace body is still not less than the temperature data acquisition deviation index of the multi-functional furnace body during the previous preset temperature data acquisition and analysis period, then a temperature fluctuation suppression optimization failure alarm is sent. This process avoids the continuous consumption of ineffective regulation by using the preset maximum number of optimization attempts and provides a stable temperature data foundation for subsequent timeliness assessment of temperature regulation signal transmission when optimization is effective, effectively improving the resistance of the temperature regulation signal to fluctuation interference.

[0047] In this embodiment, the optimization of temperature measurement fluctuation suppression helps to dynamically reduce temperature data fluctuations caused by factors such as oil fume interference and abnormal sensor voltage. With the help of a step-by-step adjustment and number of times limit mechanism, precise and efficient optimization is achieved. While reducing ineffective consumption, the temperature acquisition deviation is quickly controlled within a reasonable range, ensuring the long-term stability and accuracy of temperature data acquisition in the multi-functional furnace body, and providing reliable data support for the precise execution of furnace temperature control.

[0048] Furthermore, the specific process for evaluating the timeliness of temperature regulation signal transmission is as follows: The temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index are weighted with the corresponding temperature regulation signal weight parameters to obtain a weighted value for the temperature regulation signal parameters; the weighted value of the temperature regulation signal parameters is then harmonic-averaged to obtain a quantitative index of the timeliness of temperature regulation signal transmission; the weighted value of the temperature regulation signal parameters includes the weighted value of the temperature regulation signal transmission delay deviation and the weighted value of the qualified temperature data acquisition deviation; the temperature regulation signal transmission delay deviation value is represented by the ratio of the difference between the time the temperature regulation signal is emitted from the transmitting end monitored by the timestamp recorder and the time it is received by the multi-functional furnace control center, to the preset standard signal transmission delay value. The standard delay value for signal transmission is represented by the average value of the temperature regulation signal transmission delay deviation over a historical time period; the qualified temperature data acquisition deviation index represents the temperature data acquisition deviation index that is not greater than the preset temperature data acquisition safety deviation threshold; the timeliness quantification index for temperature regulation signal transmission is used to reflect the comprehensive matching degree between the end-to-end response efficiency of the temperature regulation signal from transmission to execution and the reliability of temperature data acquisition; it is determined whether the timeliness quantification index for temperature regulation signal transmission is less than the preset timeliness threshold for temperature regulation signal transmission. If so, heating uniformity is evaluated; otherwise, adaptive switching optimization of the transmission frequency band is adopted. The preset timeliness threshold for temperature regulation signal transmission is represented by the average value of the timeliness quantification index for temperature regulation signal transmission over a historical time period.

[0049] It should be added that the temperature regulation signal weight parameters include the temperature regulation signal transmission delay deviation weight and the qualified temperature data acquisition deviation weight, which are used to reflect the degree of influence of the temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index on the quantitative index of temperature regulation signal transmission timeliness. In this embodiment, there is a set of weight configuration groups retrieved from the database. This configuration group contains a set of weight coefficients, which are configured in advance by technicians. Specifically, by constructing the correlation relationship between the temperature regulation signal transmission delay deviation value, the qualified temperature data acquisition deviation index and the corresponding weight parameters, and using the value range of 0-1 to represent their respective weight proportions, when the multi-functional furnace control center obtains the temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index, it can quickly extract the corresponding weight parameters from the pre-constructed weight configuration group, thereby accurately quantifying the degree of influence of these two parameters on the quantitative index of transmission timeliness, so as to improve the accuracy and scenario adaptability of the temperature regulation signal transmission timeliness assessment.

[0050] In this embodiment, by weighting the temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index with corresponding weight parameters, and combining the harmonic average calculation, a quantitative index of transmission timeliness is obtained. This index is then compared with a preset signal transmission standard delay value. This helps to comprehensively consider the impact of temperature regulation signal transmission delay and data acquisition reliability on the overall response efficiency of the entire link. The weight allocation highlights the differentiated role of the two parameters, and the quantitative index intuitively reflects the overall matching status of the temperature regulation signal from issuance to execution. The overall process ensures the consistency of the evaluation standard through preset thresholds and improves the rationality of the judgment by using historical data benchmarks. This effectively improves the dynamic control capability of temperature regulation signal transmission, reduces the control error caused by transmission delay or unreliable data, and lays a solid foundation at the temperature regulation signal level for the accurate evaluation and control of heating uniformity.

[0051] like Figure 3 The diagram shown is a transmission frequency band adaptive switching optimization logic diagram of a multifunctional furnace intelligent control and monitoring system provided in an embodiment of the present invention. Figure 3 The specific process of adaptive switching optimization of transmission frequency bands is as follows: Obtain the preset channel occupancy rate and send a prompt to the preset personnel to set the preset target switching frequency band according to the preset channel occupancy rate; verify the signal transmission stability of the preset target switching frequency band: send a test signal to the preset target switching frequency band and obtain the test signal transmission success rate; determine whether the test signal transmission success rate is greater than the preset signal transmission stability threshold. If so, mark the preset target switching frequency band as a qualified switching frequency band and switch the current transmission frequency band of the temperature regulation signal to the qualified switching frequency band; otherwise, send an abnormal alarm. After the adaptive switching optimization of transmission frequency bands is completed, re-obtain the quantitative index of the timeliness of temperature regulation signal transmission. If the quantitative index of the timeliness of temperature regulation signal transmission is still less than the preset temperature regulation signal transmission timeliness threshold, perform a heating uniformity assessment; otherwise, send a frequency band switching failure alarm.

[0052] Furthermore, the specific process of adaptive switching optimization of transmission frequency bands is as follows: Frequency band matching is performed: The timeliness quantification index of temperature regulation signal transmission and the channel data transmission duration are input into the dynamic channel occupancy correction set in the database for correction to obtain the preset channel occupancy rate. A prompt is sent to the preset personnel to set the preset target switching frequency band according to the preset channel occupancy rate. The channel data transmission duration is represented by the difference between the temperature regulation signal entering the channel and completely leaving the channel, as recorded in real time by the channel monitoring unit. The database contains a correction set to reflect the correspondence between the combination of the timeliness quantification index of temperature regulation signal transmission and the channel data transmission duration, and the corresponding preset channel occupancy rate. Signal transmission stability verification of the preset target switching frequency band is performed: A test signal is sent to the preset target switching frequency band and the test signal transmission success rate is obtained. The test signal transmission success rate is then determined. If the signal transmission stability threshold is greater than the preset threshold, the preset target switching frequency band is marked as a qualified switching frequency band, and the current transmission frequency band of the temperature regulation signal is switched to the qualified switching frequency band. Otherwise, an abnormal alarm is sent. The test signal transmission success rate is calculated by continuously sending a preset number of test signals to the preset target switching frequency band through a signal quality tester. The preset number is set in advance by a preset number of personnel, and the preset signal transmission stability threshold is represented by the average value of the test signal transmission success rate over a historical period. After the adaptive switching optimization of the transmission frequency band is completed, the timeliness quantification index of the temperature regulation signal transmission is reacquired. If the timeliness quantification index of the temperature regulation signal transmission is still not less than the preset temperature regulation signal transmission timeliness threshold, a frequency band switching failure alarm is sent. Otherwise, a heating uniformity assessment is performed.

[0053] In this embodiment, adaptive switching optimization of transmission frequency bands helps to accurately match and adapt to the frequency bands of the current transmission environment. Quantitative success rate verification ensures that the switched frequency band can stably transmit temperature regulation signals, avoiding transmission interruptions or delays caused by improper frequency band selection. An alarm is issued in time when switching fails, and timely and reliable signal support is provided for heating uniformity assessment when switching is effective. This effectively improves the anti-interference capability and adaptive adjustment capability of temperature regulation signal transmission, reduces the impact of oil fume interference on signal transmission, and ensures that temperature regulation commands can be transmitted efficiently, laying the foundation for precise control of heating uniformity.

[0054] Furthermore, the specific process for assessing heating uniformity is as follows: Obtaining the heating uniformity deviation index; the heating uniformity deviation index is represented by the difference between the oven temperature deviation value during a preset food heating uniformity time period and a preset temperature deviation value. The preset food heating uniformity time period represents the time period for assessing heating uniformity, and the preset temperature deviation value is set by the preset personnel; the temperature deviation value is obtained by monitoring the difference between the maximum and minimum temperatures in the preset heating area within the oven using temperature sensors; the heating uniformity deviation index reflects the degree to which the heating degree of each part deviates from the ideal uniform state due to differences in oven temperature distribution; determining whether the heating uniformity deviation index is within the preset heating uniformity threshold range helps to accurately assess the rationality of the oven temperature distribution by comparing the actual temperature distribution with the preset heating uniformity threshold range, and promptly detect abnormalities such as local overheating or insufficient heating. The preset heating uniformity threshold range is set in advance by the preset personnel and includes both endpoints; if within the preset heating uniformity threshold range, a heating uniformity qualified prompt is sent; otherwise, dynamic matching control of heating uniformity is performed.

[0055] In this embodiment, by evaluating the heating uniformity, it is helpful to accurately capture the deviation of the heating of different parts of the food from the ideal state caused by the temperature distribution difference in the oven during the baking process. The actual situation of heating uniformity is presented intuitively with quantitative indicators. When the heating uniformity deviation index is within the preset heating uniformity threshold range, a qualified prompt is sent to ensure that the food baking process proceeds in an orderly manner under stable heating conditions. When the heating uniformity deviation index exceeds the preset heating uniformity threshold range, dynamic matching control of heating uniformity is triggered, which can correct the problem of uneven heating in time and avoid the decline in baking quality of food due to local overheating or underheating, effectively improving the heating uniformity of food in the multi-functional oven.

[0056] Furthermore, the specific process of dynamic matching control of heating uniformity is as follows: The heating uniformity deviation index and the rotation speed of the rotating gantry are input into the database to obtain the preset rotating gantry speed adjustment coefficient. The rotating gantry speed is monitored by a speed sensor. The database contains a set of corrections reflecting the relationship between the combination of the heating uniformity deviation index and the rotating gantry speed, and the corresponding preset rotating gantry speed adjustment coefficient. The preset rotating gantry speed adjustment coefficient boundary is verified: it is determined whether the preset rotating gantry speed adjustment coefficient exceeds the preset rotating gantry speed threshold range, which is preset by designated personnel. If so, an abnormal adjustment coefficient alarm is sent; otherwise, the corresponding preset rotating gantry speed adjustment coefficient is marked as a valid rotating gantry speed adjustment value, and heating uniformity monitoring and rotating gantry speed adjustment are performed.

[0057] Specifically, the process for monitoring heating uniformity and adjusting the rotation speed of the skewer is as follows: Monitoring and judging the heating uniformity deviation index: When the heating uniformity deviation index is less than the lower limit of the heating uniformity threshold range, the rotation speed is gradually increased using the effective adjustment value of the skewer speed as the adjustment step. This step-by-step rotation speed adjustment helps reduce heating fluctuations caused by sudden speed changes, ensuring that the heating uniformity of all parts of the food remains within the ideal range. When the heating uniformity deviation index is lower than the lower limit of the heating uniformity threshold range, the rotation speed is increased to accelerate the heating cycle of the food and balance local temperature differences. When the re-acquired heating uniformity deviation index is within the heating uniformity threshold range, execution stops; when the heating uniformity deviation index is greater than the upper limit of the heating uniformity threshold range... When the value is set, the adjustment step size is taken according to the effective rotation speed adjustment value of the skewer. The rotation speed of the skewer is gradually reduced. When the heating uniformity deviation index is higher than the upper limit of the heating uniformity threshold range, the speed is reduced. This can prolong the heating time of the food in the suitable temperature range to improve the problem of insufficient heating. When the heating uniformity deviation index is detected to be within the heating uniformity threshold range, the operation stops. The rotation speed of the skewer does not exceed the preset rotation speed adjustment threshold. After the heating uniformity dynamic matching control is completed, if the heating uniformity deviation index is still not within the heating uniformity threshold range in the next preset food heating uniformity time period, an abnormal alarm is sent. Otherwise, a heating uniformity qualified prompt is sent. The preset food heating uniformity time period represents the time period for the next heating uniformity assessment.

[0058] In this embodiment, dynamic matching control of heating uniformity helps to achieve precise dynamic adaptation between the rotation speed of the rotating frame and the heating state inside the furnace, enabling the heating uniformity deviation index to quickly converge to the heating uniformity threshold range, improving the accuracy of heating uniformity assessment data. By setting a preset speed adjustment threshold, equipment overload is prevented, and an alarm is issued in time when control fails, ensuring the continuity and stability of heating uniformity related data monitoring, effectively reducing heating uniformity data deviation caused by uneven heating, and further improving the accuracy of intelligent monitoring data of the multi-functional furnace body.

[0059] In summary, this application embodiment assesses the degree of oil fume accumulation in the multi-functional furnace body. Based on the assessment results, it determines whether adjusting the exhaust fan speed is necessary. This helps to break the imbalance between localized oil fume accumulation and airflow collision, reduces airflow dead zones formed by the hexagonal furnace structure, and allows the multi-functional furnace control center to accurately grasp the actual amount of oil fume generated. It avoids start-up / shutdown and intensity adjustment disorders in the exhaust system due to misjudgment, reducing interference from oil fume on monitoring data at the source. After the assessment of the degree of oil fume accumulation in the multi-functional furnace body is deemed satisfactory, the accuracy analysis of temperature data acquisition determines whether temperature measurement fluctuation suppression optimization is needed. This helps improve the accuracy of temperature data acquisition, ensuring that the acquired temperature data truly reflects the actual temperature inside the furnace, providing a reliable basis for subsequent temperature adjustment. Based on a solid data foundation, after the accuracy analysis of temperature data acquisition is qualified, the timeliness evaluation results of temperature regulation signal transmission determine whether to adopt adaptive switching optimization of transmission frequency band. This helps to reduce the problem of temperature regulation signal transmission delay caused by oil fume interference. By adapting to the optimal transmission frequency band, it ensures that the temperature regulation signal can be transmitted to the multi-functional furnace control center in a timely and stable manner. After the timeliness evaluation of temperature regulation signal transmission is qualified, the evaluation results of heating uniformity determine whether dynamic matching control of heating uniformity is needed. This helps to intelligently adjust the rotation speed of the rotating rack, reduce the problem of uneven heating of food caused by local temperature imbalance, and improve the accuracy of intelligent monitoring data of multi-functional furnace. This effectively solves the problem of low accuracy of intelligent monitoring data of multi-functional furnace due to oil fume accumulation in the existing technology.

[0060] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0061] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0062] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0063] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0064] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0065] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multifunctional intelligent control and monitoring system for furnace bodies, characterized in that, include: Multifunctional furnace body oil fume concentration distribution uniformity monitoring module, temperature data acquisition accuracy monitoring module, temperature regulation signal transmission timeliness monitoring module, and heating uniformity monitoring module: The multi-functional furnace body oil fume concentration distribution uniformity monitoring module is used to assess the degree of oil fume accumulation in the multi-functional furnace body during the intelligent monitoring process. Based on the assessment result of the degree of oil fume accumulation in the multi-functional furnace body, it is determined whether it is necessary to adjust the speed of the exhaust fan. The adjustment of the exhaust fan speed is used to improve the oil fume emission efficiency by dynamically adjusting the speed of the exhaust fan. The temperature data acquisition accuracy monitoring module is used to determine whether temperature measurement value fluctuation suppression optimization is needed based on the temperature data acquisition accuracy analysis results after the multi-functional furnace body oil fume accumulation degree assessment is qualified. The temperature measurement value fluctuation suppression optimization is used to reduce abnormal temperature data fluctuation interference caused by oil fume interference. The temperature regulation signal transmission timeliness monitoring module is used to determine whether to take adaptive switching optimization of transmission frequency band based on the temperature regulation signal transmission timeliness evaluation result after the temperature data acquisition accuracy analysis is qualified. The adaptive switching optimization of transmission frequency band is used to reduce the transmission delay caused by oil fume interference. The heating uniformity monitoring module is used to determine whether dynamic matching control of heating uniformity is needed based on the heating uniformity assessment result after the timeliness assessment of temperature regulation signal transmission is qualified. The dynamic matching control of heating uniformity is used to improve the control accuracy of furnace heating uniformity.

2. The multifunctional intelligent control and monitoring system for a furnace body according to claim 1, characterized in that, The specific process for assessing the degree of oil fume accumulation in the multi-functional furnace body is as follows: Obtain indicators of the degree of oil fume accumulation in the multi-functional furnace body; The multi-functional furnace body oil fume accumulation index is used to reflect the degree of interference of oil fume accumulation in the furnace on temperature data monitoring. If the oil fume accumulation level of the multi-functional furnace body is less than the preset standard oil fume accumulation threshold, a furnace body heating qualified prompt is sent and temperature data acquisition accuracy analysis is performed; otherwise, the exhaust fan speed is adjusted.

3. The multifunctional intelligent control and monitoring system for a furnace body according to claim 2, characterized in that, The specific process for adjusting the speed of the exhaust fan is as follows: AA1, the oil fume accumulation index and oil fume temperature of the multi-functional furnace body are entered into the dynamic correction set of the exhaust fan speed in the database for correction, and the preset exhaust fan speed adjustment coefficient is retrieved from the database; AA2, determine whether the exhaust fan speed adjustment coefficient exceeds the preset maximum adjustment threshold. If so, send an exhaust overload alarm; otherwise, mark the corresponding exhaust fan speed adjustment coefficient as a valid exhaust fan speed adjustment value. AA3, using the effective range of the exhaust fan speed adjustment value as the adjustment step size, gradually increases the exhaust fan speed; AA4. After the exhaust fan speed adjustment is completed, if the newly acquired multi-functional furnace body oil fume accumulation index is not less than the multi-functional furnace body oil fume accumulation index of the previous preset oil fume concentration distribution uniformity time period, and the multi-functional furnace body oil fume accumulation index is not less than the preset multi-functional furnace body oil fume accumulation index, then an exhaust fan optimization alarm will be sent; otherwise, a temperature data acquisition accuracy analysis will be performed.

4. The multifunctional intelligent control and monitoring system for a furnace body according to claim 3, characterized in that, The specific process of temperature data acquisition accuracy analysis is as follows: The offset of temperature data acquisition parameters is obtained by quantifying the ratio between the temperature data acquisition parameters and the standard temperature data acquisition parameters retrieved from the database. The temperature data acquisition parameter offset and the influence value of the temperature data acquisition weight are weighted and fused to obtain the temperature data acquisition deviation index. It is then determined whether the deviation index is less than the preset temperature data acquisition safety deviation threshold. If it is, the stability of temperature regulation signal transmission is evaluated; otherwise, temperature measurement fluctuation suppression optimization is adopted. The temperature data acquisition parameter offset includes the airflow velocity deviation rate around the temperature sensor, the temperature measurement value fluctuation deviation rate, and the oil fume concentration distribution deviation rate of the multi-functional furnace body. The temperature data acquisition weight influence value is used to reflect the degree of influence of the temperature data acquisition parameter offset on the temperature data acquisition deviation index. The temperature data acquisition deviation index is used to reflect the effect of temperature data acquisition parameters on the accuracy of temperature data acquisition results.

5. The multifunctional intelligent control and monitoring system for a furnace body according to claim 4, characterized in that, The specific process for optimizing the suppression of temperature measurement fluctuations is as follows: The temperature data acquisition deviation index and the temperature sensor operating voltage deviation value are input into the dynamic correction set of the filter window width in the database for correction, and the corresponding preset filter window width adjustment coefficient is retrieved. The sliding filter window width is gradually increased by using the amplitude corresponding to the preset filter window width adjustment coefficient as the adjustment step size. Determine if the number of optimization attempts to suppress temperature measurement fluctuations exceeds the preset maximum number of optimization attempts: If the number of optimization attempts to suppress temperature measurement fluctuations does not exceed the preset maximum number of optimization attempts, the optimization to suppress temperature measurement fluctuations will continue until the deviation index of the multi-functional furnace body temperature data acquisition is less than the deviation index of the multi-functional furnace body temperature data acquisition during the previous preset temperature data acquisition and analysis period. At this point, the timeliness of temperature regulation signal transmission will be evaluated. If the number of optimization attempts to suppress temperature fluctuations exceeds the preset maximum number of optimization attempts, and the monitored multi-functional furnace body temperature data acquisition deviation index is still not less than the multi-functional furnace body temperature data acquisition deviation index of the previous preset temperature data acquisition and analysis time period, then a temperature measurement fluctuation suppression optimization failure alarm will be sent.

6. The multifunctional intelligent control and monitoring system for a furnace body according to claim 5, characterized in that, The specific process for evaluating the timeliness of temperature regulation signal transmission is as follows: The temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index are respectively weighted with the corresponding temperature regulation signal weight parameters to obtain the temperature regulation signal parameter weight value. The weighted values ​​of the temperature regulation signal parameters are harmonic averaged to obtain a quantitative index of the timeliness of temperature regulation signal transmission. The temperature regulation signal weight parameters include the temperature regulation signal transmission delay deviation weight and the qualified temperature data acquisition deviation weight, which are used to reflect the degree of influence of the temperature regulation signal transmission delay deviation value and the qualified temperature data acquisition deviation index on the quantitative index of the timeliness of temperature regulation signal transmission, respectively. The weighted values ​​of the temperature regulation signal parameters include the weighted value of the temperature regulation signal transmission delay deviation and the weighted value of the qualified temperature data acquisition deviation; The timeliness quantification index of temperature regulation signal transmission is used to reflect the comprehensive matching degree between the end-to-end response efficiency of temperature regulation signal from issuance to execution and the reliability of temperature data acquisition. If the quantitative index of the timeliness of temperature regulation signal transmission is less than the preset threshold for the timeliness of temperature regulation signal transmission, then the heating uniformity is evaluated; otherwise, the transmission frequency band adaptive switching optimization is adopted.

7. The multifunctional intelligent control and monitoring system for a furnace body according to claim 6, characterized in that, The specific process of the adaptive switching optimization of the transmission frequency band is as follows: Perform frequency band switching matching: Input the temperature regulation signal transmission timeliness quantification index and channel data transmission duration into the dynamic channel occupancy correction set in the database for correction, obtain the preset channel occupancy rate, and send a prompt to the preset personnel to set the preset target frequency band according to the preset channel occupancy rate; Verify the stability of signal transmission in the preset target switching frequency band: obtain the test signal transmission success rate, determine whether the test signal transmission success rate is greater than the preset signal transmission stability threshold, if so, mark the preset target switching frequency band as a qualified switching frequency band, and switch the current transmission frequency band of the temperature regulation signal to the qualified switching frequency band; otherwise, send an abnormal alarm. After the adaptive switching optimization of the transmission frequency band is completed, the quantitative index of the timeliness of the temperature regulation signal transmission is reacquired. If the quantitative index of the timeliness of the temperature regulation signal transmission is still not less than the preset temperature regulation signal transmission timeliness threshold, a frequency band switching failure alarm is sent; otherwise, a heating uniformity assessment is performed.

8. The multifunctional intelligent control and monitoring system for a furnace body according to claim 7, characterized in that, The specific process for evaluating heating uniformity is as follows: Obtain the heating uniformity deviation index; The heating uniformity deviation index is used to reflect the degree to which the degree of heating of various parts deviates from the ideal uniform state due to the difference in temperature distribution inside the furnace; Determine whether the heating uniformity deviation index is within the preset heating uniformity threshold range; If the heating uniformity is within the preset threshold range, a heating uniformity qualified prompt will be sent; otherwise, dynamic matching adjustment of heating uniformity will be performed.

9. The multifunctional intelligent control and monitoring system for a furnace body according to claim 8, characterized in that, The specific process of regulating the dynamic matching of heating uniformity is as follows: Input the heating uniformity deviation index and the rotation speed of the rotating trough into the database to obtain the preset rotation speed adjustment coefficient of the rotating trough. Perform boundary verification of the preset rotating shunt frame speed adjustment coefficient: determine whether the preset rotating shunt frame speed adjustment coefficient exceeds the preset rotating shunt frame speed threshold range; If yes, an alarm for abnormal adjustment coefficient is sent; otherwise, the corresponding preset rotational speed adjustment coefficient is marked as an effective rotational speed adjustment value, and heating uniformity is monitored and rotational speed is adjusted.

10. The multifunctional intelligent control and monitoring system for a furnace body according to claim 9, characterized in that, The specific process for monitoring heating uniformity and adjusting the rotation speed of the rotating truss is as follows: Monitor and judge the heating uniformity deviation index: When the heating uniformity deviation index is less than the lower limit of the heating uniformity threshold range, the adjustment step size is taken as the amplitude corresponding to the effective rotation speed adjustment value of the rotating frame, and the rotation speed of the rotating frame is increased step by step. When the heating uniformity deviation index that has been re-acquired is within the heating uniformity threshold range, the execution is stopped. When the heating uniformity deviation index is greater than the upper limit of the heating uniformity threshold range, the rotation speed of the rotating trough is gradually reduced by using the magnitude corresponding to the effective rotation speed adjustment value as the adjustment step size. When the heating uniformity deviation index is detected to be within the heating uniformity threshold range, the execution stops. After the dynamic matching control of heating uniformity is completed, if the heating uniformity deviation index is still not within the heating uniformity threshold range in the next preset food heating uniformity time period, an abnormal alarm will be sent; otherwise, a heating uniformity qualified prompt will be sent.

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