Calender control system for thin photovoltaic glass production

Abstract

The invention discloses a calender control system for thin photovoltaic glass production, and belongs to the technical field of photovoltaic glass production control. The problems that an existing calender control system is insufficient in control precision, response speed and stability, and the high requirement for ultrathin photovoltaic glass production is difficult to meet are solved. The pressure sensor is used for monitoring the pressure of the compression roller in real time, anomaly detection and smooth processing are conducted in combination with the box plot method and the moving average method, the PID control model is adopted for dynamically adjusting the pressure, and equipment damage or the product quality problem is avoided; the temperature sensor monitors the temperature of the water-cooling and air-cooling systems in real time, accurate regulation and control are performed by using a discrete time PID algorithm, and an alarm mechanism is combined, so that the temperature stability is ensured, and the efficiency and quality are improved; based on a fuzzy control model, temperature and pressure data are integrated, the rolling speed is dynamically optimized through fuzzification, rule base, reasoning and defuzzification, the method adapts to complex nonlinear scenes, and the production stability and the product consistency are remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic glass production control, and particularly to a calender control system for thin photovoltaic glass production. Background Art

[0002] With the rapid development of the photovoltaic industry, the demand for ultra-thin photovoltaic glass is increasing day by day. In the production process of ultra-thin photovoltaic glass, the calender is one of the key devices, and the accuracy and stability of its control system directly affect the thickness, uniformity and surface quality of the glass. However, the existing calender control systems have deficiencies in control accuracy, response speed and stability, and it is difficult to meet the high requirements of ultra-thin photovoltaic glass production. Summary of the Invention

[0003] The purpose of the present invention is to solve the above problems and propose a calender control system for thin photovoltaic glass production.

[0004] The purpose of the present invention can be achieved by the following technical solutions: A calender control system for thin photovoltaic glass production, including a calender main body, a control unit, a pressure adjustment module, a temperature control module and a speed control module; The calender main body includes a lower pressing roller, a water cooling device, an air cooling device, a transition roller table and a transmission device; The control unit includes a PLC controller, sensors, actuators and a human-machine interface; the PLC controller is fixedly installed in the internal control cabinet of the calender main body, pressure sensors are installed at the adjustment bearing positions of the cylindrical lower pressing roller 1, cylindrical lower pressing roller 2, cylindrical lower pressing roller 3 and cylindrical lower pressing roller 4; temperature sensors are installed at the corresponding positions inside the water cooling pipeline, water tank and the internal air duct of the air cooling device; the actuator for adjusting the turbine fan of the air cooling device is installed inside the calender main body and receives control signals through the PLC controller, and the human-machine interface is installed on the operation panel of the calender main body; The pressure adjustment module is used to monitor and adjust the pressure of the rolling mill; The temperature control module is used to monitor and adjust the rolling temperature; The speed control module controls the rolling speed.

[0005] As a preferred embodiment of the present invention, the lower pressing roller includes a cylindrical lower pressing roller 1, a cylindrical lower pressing roller 2, a cylindrical lower pressing roller 3, a cylindrical lower pressing roller 4, an irregular hexagon column 1, an irregular hexagon column 2, an irregular hexagon column 3, and an irregular hexagon column 4; the water cooling device is composed of a water tank, a water cooling pipeline, and an external water cooling radiator tower; the transition roller table includes a feeding transition roller table and a discharging transition roller table; the transmission device is directly driven by a servo motor; the air cooling device includes an air outlet hole, a turbo fan, an internal air duct, and an air inlet shutter; the cylindrical lower pressing roller 1, the cylindrical lower pressing roller 2, the cylindrical lower pressing roller 3, the cylindrical lower pressing roller 4, the irregular hexagon column 1, the irregular hexagon column 2, the irregular hexagon column 3, and the irregular hexagon column 4 are all rotatably and fixedly connected to the calender main body through adjusting bearings and a servo motor, the feeding transition roller table and the discharging transition roller table are rotatably and fixedly connected to the calender main body, and are driven by a servo motor; a turbo fan, an air outlet hole, a water tank, an air inlet shutter, an upper pressing roller wall, and a lower pressing roller wall are fixedly installed inside the calender main body.

[0006] As a preferred embodiment of the present invention, the specific process of the pressure adjustment module for monitoring and adjusting the pressure of the rolling mill is as follows: The sensor collects data in real time: The pressure sensors installed on the cylindrical lower pressing roller 1, the cylindrical lower pressing roller 2, the cylindrical lower pressing roller 3, and the cylindrical lower pressing roller 4 monitor the pressure data of each pressing roller in real time, and transmit the pressure data to the PLC controller; the pressure data of the sensor includes the instantaneous pressure, the average pressure, and the pressure fluctuation value; When the PLC controller receives the pressure data, it performs outlier detection, smoothing processing, and statistical analysis.

[0007] As a preferred embodiment of the present invention, the specific process of performing outlier detection, smoothing processing, and statistical analysis is as follows: S01: Perform outlier detection: Use the box plot method to remove abnormal data: Calculate the first quartile Q1 and the third quartile ; Preset the outlier range: Or P i > Q3 + 1.5 × IQR; If a certain pressure data P i exceeds this range, it is determined as an outlier, and a pressure data abnormality instruction is generated; S02: Perform smoothing processing: Use the moving average method to calculate the pressure trend: , M is the moving window size; S03: Perform statistical analysis: Set the pressure threshold for the normal working range, based on historical data statistics or empirical formula: , P max = μ + k2σ; k1, k2 are threshold coefficients; P min , Pmax are the lower and upper pressure thresholds respectively; according to the collected smoothed pressure values , conduct pressure state classification: when the collected smoothed pressure value , it belongs to the normal state, that is, P min ≤ ≤P max , then the device operates normally without adjustment; when the collected smoothed pressure value belongs to the overpressure state, that is >P max , trigger the overpressure adjustment process; when the collected smoothed pressure value , it belongs to the underpressure state, that is, P min < , trigger the underpressure adjustment process; S04: When the pressure exceeds the threshold, automatically adjust the actuator of the roller compactor, set the target, P 目标 =μ; Adjustment step setting: , β is the adjustment coefficient; ΔP is the pressure adjustment amount; change the position of the roller of the roller compactor: , θ(t) is the current servo motor angle, γ is the pressure-angle conversion coefficient; continuously monitor the pressure data and adjust based on the PID control model: , is the error, K p , K i , K d are the PID control parameters.

[0008] As a preferred embodiment of the present invention, the temperature control module is used to monitor and adjust the rolling temperature, specifically: Real-time monitor the temperature changes of the water-cooling and air-cooling systems; the temperature sensor collects temperature data in real time and transmits the temperature and pressure data to the PLC controller for real-time processing and analysis.

[0009] As a preferred embodiment of the present invention, the specific process of the above-mentioned real-time processing and analysis: The temperature sensor collects temperature data in real time, denoted as T 当前 ; According to the characteristics of the rolling material, set the temperature range in the PLC controller in advance: including the lowest temperature T min and the highest temperature T max ; Determine the temperature range T min ≤T 当前 ≤T max ; The PLC controller calculates the deviation between the current temperature and the target temperature range: if T 当前 <T min , then the temperature is too low, and the deviation is: ; If T 当前>T max , the temperature is on the high side, and the deviation is: ; According to the historical temperature data, calculate the temperature change trend: Through the formula: , T 上 is the temperature value collected last time, and Δt is the time interval between two collections; Adopt the discrete-time PID control algorithm: Discretize the continuous-time PID formula, and the formula is: , Output(k) is the control output at the kth sampling moment; e(k) is the temperature deviation at the kth sampling moment; k p1 is the preset proportional coefficient; K j1 is the preset integral coefficient; K d1 is the preset differential coefficient; Δt is the sampling time interval; is the cumulative sum of the temperature deviation from the initial moment to the kth sampling moment; is the change rate of the temperature deviation; Then, according to the value of Output(k), adjust the output of the cooling or heating system; If Output(k)>0, reduce the output of the cooling system or start heating; If Output(k)<0, increase the output of the cooling system and update the deviation value of the previous moment in real time ; Repeat the process of the discrete-time PID control algorithm to achieve real-time temperature control; Through the alarm protection mechanism, obtain the temperature deviation ΔT and the preset temperature deviation threshold ΔT threshold for comparison. If ΔT>ΔT threshold , the PLC controller will trigger an alarm: , if the temperature remains abnormal, the PLC controller will start the preset protection mechanism.

[0010] As a preferred embodiment of the present invention, the specific process of the speed control module for controlling the rolling speed is as follows: Control the rolling speed based on the algorithm process of real-time monitoring and adjustment by the temperature control module and the pressure control module; S001: Input variable definition, temperature deviation e T and pressure deviation e P , S002: Convert the input variables into fuzzy language variables; Define fuzzy sets: The fuzzy set of temperature deviation e T : {Negative large (NB), Negative small (NS), Zero (ZO), Positive small (PS), Positive large (PB)}; The fuzzy set of pressure deviation e P : {Negative large (NB), Negative small (NS), Zero (ZO), Positive small (PS), Positive large (PB)}; Use triangular or trapezoidal membership functions to map the actual deviation values to the fuzzy sets; The membership function of temperature deviation e T : ; Similarly, the membership function of the pressure deviation e P is obtained; S003: Establish a fuzzy rule base according to process knowledge; Rule form: IF e T is A AND e p is B THEN ΔV is C; A and B are fuzzy sets of input variables; C is the fuzzy set of the output variable; S004: Calculate the output of each rule using the Mamdani inference method; Calculate the membership degree of the premise part of each rule: μ rule =min(μ A (e T ), μ B (e P )); According to the membership degree of the premise part, trim the membership function of the output variable: μ C (ΔV)=min(μ rule , μ C (ΔV)); Synthesize the outputs of all rules to obtain the fuzzy output ΔV: μ total (ΔV)=max(μ C1 (ΔV), μ C2 (ΔV), …) S005: Convert the fuzzy output ΔV into a specific speed adjustment amount; Calculate using the centroid method: Calculate the centroid of the fuzzy output and use it as the final speed adjustment amount; S006: Calculate the new rolling speed according to the defuzzified speed adjustment amount ΔV: V new =V current +ΔV; V new is the target rolling speed; V current is the current rolling speed; and limit the speed range so that the adjusted speed is within the preset allowable range [V min , V max ; S007: According to the adjusted speed V new , the PLC controller adjusts the rotational speed of the servo motor to drive the pressure roller to achieve speed adjustment.

[0011] Compared with the prior art, the beneficial effects of the present invention are: 1. The present invention monitors the working pressure of the calender roll in real time through a pressure sensor, and combines the box plot method (IQR) for outlier detection, the moving average method for smoothing processing, and statistical analysis to accurately identify abnormal pressure and dynamically adjust the pressure threshold. The PID control model is used to perform closed-loop control on the pressure to ensure a reasonable pressure distribution and avoid equipment damage or product quality problems caused by too high or too low pressure.

[0012] 2. The present invention monitors the temperature changes of the water-cooling and air-cooling systems in real time through a temperature sensor, and uses the discrete-time PID control algorithm to precisely adjust the temperature. Combining with the alarm protection mechanism, it can trigger an alarm or automatically shut down in case of abnormal temperature in a timely manner, ensuring that the rolling temperature is always within a reasonable range, thereby improving production efficiency and product quality.

[0013] 3. The present invention is based on a fuzzy control model, comprehensively considering the real-time monitoring data of temperature and pressure, and dynamically adjusts the rolling speed. Through fuzzification, fuzzy rule base, inference mechanism, and defuzzification, it can realize the intelligent optimization of the rolling speed, adapt to complex non-linear control scenarios, and significantly improve the stability of the production process and the consistency of product quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the drawings.

[0015] Figure 1 is the principle block diagram of the present invention; Figure 2 is the front view schematic diagram of the calender of the present invention; Figure 3 is the front elevation schematic diagram of the calender of the present invention; Figure 4 is the sectional view A-A schematic diagram of the calender of the present invention; Figure 5 is the sectional view B-B schematic diagram of the calender of the present invention.

[0016] BRIEF DESCRIPTION OF THE DRAWINGS: 1. Calender main body; 2. Discharge transition roller table; 3. Feed transition roller table; 4. Air inlet louvers; 5. Air outlet holes; 6. Turbo fan; 7. Water tank; 8. Cylindrical lower calender roll 1; 9. Cylindrical lower calender roll 2; 10. Cylindrical lower calender roll 3; 11. Cylindrical lower calender roll 4; 12. Irregular hexagon column 1; 13. Irregular hexagon column 2; 14. Irregular hexagon column 3; 15. Irregular hexagon column 4; 16. Lower calender roll wall; 17. Upper calender roll wall. DETAILED DESCRIPTION OF THE INVENTION

[0017] The technical solution of the present invention will be clearly and completely described below in conjunction with embodiments. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] It should be understood that the terms "including" and "comprising" used in the specification and claims of this disclosure indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0019] It should also be understood that the terms used in this disclosure specification are only for the purpose of describing specific embodiments and are not intended to limit this disclosure. As used in this disclosure specification and claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms. It should be further understood that the term "and / or" used in this disclosure specification and claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0020] Please refer to Figure 1 As shown, a calender control system for thin photovoltaic glass production includes a calender main body, a control unit, a pressure regulation module, a temperature control module, and a speed control module.

[0021] Please refer to Figures 2 - 5 As shown, the calender main body 1 includes a lower pressing roller, a water cooling device, an air cooling device, a transition roller table, and a transmission device; wherein, the lower pressing roller includes a cylindrical lower pressing roller 1, a cylindrical lower pressing roller 2, a cylindrical lower pressing roller 3, and a cylindrical lower pressing roller 4, as well as an irregular hexagon column 1, an irregular hexagon column 2, an irregular hexagon column 3, and an irregular hexagon column 4; the water cooling device is composed of a water tank 7, a water cooling pipeline, and an external water cooling radiator tower; the transition roller table includes a feeding transition roller table 3 and a discharging transition roller table 2; the transmission device is directly driven by a servo motor; the air cooling device includes an air outlet hole 5, a turbine fan 6, an internal air duct, and an air inlet louver 4.

[0022] The cylindrical lower pressing roller 1, the cylindrical lower pressing roller 2, the cylindrical lower pressing roller 3, the cylindrical lower pressing roller 4, the irregular hexagon column 1, the irregular hexagon column 2, the irregular hexagon column 3, and the irregular hexagon column 4 are all rotationally and fixedly connected to the calender main body 1 through adjusting bearings and servo motors. The feeding transition roller table 3 and the discharging transition roller table 2 are rotationally and fixedly connected to the calender main body 1 and are driven by servo motors. Inside the calender main body 1, a turbine fan 6, an air outlet 5, a water tank 7, an air inlet louver 4, an upper pressing roller wall 17, and a lower pressing roller wall 16 are fixedly installed.

[0023] The control unit includes a PLC controller, sensors, actuators, and a human-machine interface. The PLC controller is fixedly installed in the internal control cabinet of the calender main body 1 and is responsible for receiving sensor data and controlling the operation of the actuators. The sensors are mainly distributed near the pressing rollers, transition roller tables, air-cooling, and water-cooling devices. The pressure sensors are installed at the adjusting bearing positions of the cylindrical lower pressing roller 1, the cylindrical lower pressing roller 2, the cylindrical lower pressing roller 3, and the cylindrical lower pressing roller 4 to monitor the working pressure of the pressing rollers in real time. The temperature sensors are installed near the internal air ducts of the water-cooling pipes, the water tank 7, and the air-cooling device to monitor the temperature changes of the water-cooling and air-cooling systems. The actuators mainly refer to servo motors, which are respectively used to drive the pressing rollers, transition roller tables, and adjust the turbine fan 6 of the air-cooling device. They are installed inside the calender main body 1 and receive control signals through the PLC controller to achieve precise adjustment. The human-machine interface (HMI) is installed on the operation panel of the calender main body 1 to facilitate the operator to monitor the equipment status in real time, adjust parameters, and perform fault diagnosis.

[0024] The pressure adjustment module is used to monitor and adjust the pressure of the rolling mill. Specifically: The sensors collect data in real time: The pressure sensors installed on the cylindrical lower pressing roller 1, the cylindrical lower pressing roller 2, the cylindrical lower pressing roller 3, and the cylindrical lower pressing roller 4 monitor the pressure data of each pressing roller in real time and transmit the pressure data to the PLC controller. The pressure data of the sensors include instantaneous pressure, average pressure, and pressure fluctuation values to ensure a reasonable pressure distribution during the rolling process. When the PLC controller receives the pressure data, it performs outlier detection, smoothing processing, and statistical analysis: S01: Perform outlier detection: Use the box plot method (IQR) to remove abnormal data: Calculate the first quartile Q1 (the data point at the 25% position after sorting the data) and the third quartile Q3 (the data point at the 75% position after sorting the data): ; Preset the outlier range: Or P i > Q3 + 1.5×IQR; If a certain pressure data P iIf it exceeds this range, it is determined as an outlier, and a pressure data anomaly instruction is generated; i represents the moment when the pressure data is collected. S02: Perform smoothing processing: Calculate the pressure trend using the moving average method: , where M is the moving window size (such as 5 - 10 data points); the calculated is used as the smoothed pressure data. S03: Conduct statistical analysis: Set the pressure threshold for the normal operating range, based on historical data statistics or empirical formula: , P max = μ + k2σ; where k1 and k2 are threshold coefficients, set according to the working conditions of the roller compactor (usually k1 = 1.5, k2 = 2); P min , P max are the lower and upper pressure thresholds respectively; it should be noted that: for different working conditions, the thresholds can be adjusted dynamically: using the exponential smoothing method, making the thresholds change with the operating state: , ; where α is the smoothing factor (usually taken as 0.7 - 0.9); According to the collected smoothed pressure value , conduct pressure state classification: When the collected smoothed pressure value , it belongs to the normal state (P min ≤ ≤ P max ), then the equipment operates normally and no adjustment is required; the collected smoothed pressure value belongs to the high - pressure state ( > P max ), triggering the pressure - over - standard adjustment process (reducing the downward pressure); when the collected smoothed pressure value , it belongs to the low - pressure state (P min < ), triggering the pressure - insufficient adjustment process (increasing the downward pressure); S04: When the pressure exceeds the threshold, the system automatically adjusts the actuator of the roller compactor and sets the target, P 目标 = μ; Adjustment step setting: , β is the adjustment coefficient (usually 0.1 - 0.5); ΔP is the pressure adjustment amount, which may cause oscillation if too large; Adjust the servo motor to change the position of the roller of the roller compactor: , θ(t) is the current angle of the servo motor, γ is the pressure - angle conversion coefficient (set according to the equipment characteristics); Continuously monitor the pressure data and make adjustments based on the PID control model: , is the error, K p , K i , K dis the PID control parameter and needs to be debugged and optimized.

[0025] The temperature control module is used to monitor and adjust the rolling temperature. Specifically: It is installed near the internal air ducts of the water-cooling pipes, water tank 7 and air-cooling device to monitor the temperature changes of the water-cooling and air-cooling systems in real time; the temperature sensor collects temperature data in real time and transmits the pressure data to the PLC controller (the temperature data is transmitted to the PLC controller in digital signals (such as 4 - 20 mA or 0 - 10 V), and the PLC converts it into the actual temperature value), and performs real-time processing and analysis; judge whether the temperature is within the set range. The specific formula calculation process: The temperature sensor collects temperature data in real time, denoted as T 当前 (current temperature); then, according to the characteristics of the rolling material, a reasonable temperature range is set in the PLC controller in advance: including the lowest temperature: T min and the highest temperature: T max ; determine the temperature range T min ≤T 当前 ≤T max ; the PLC controller calculates the deviation between the current temperature and the target temperature range: if T 当前 <T min ,the temperature is too low, and the deviation is: ; if T 当前 >T max ,the temperature is too high, and the deviation is: ; according to the historical temperature data, calculate the temperature change trend (such as the heating or cooling rate): through the formula: ,where T 上 is the temperature value collected last time, and Δt is the time interval between two collections; adopt the discrete-time PID control algorithm: discretize the continuous-time PID formula, and the formula is: ,where Output(k) is the control output at the kth sampling moment; e(k) is the temperature deviation at the kth sampling moment; k p1 is the preset proportional coefficient for quickly responding to the temperature deviation; K j1 is the preset integral coefficient for eliminating the steady-state error; K d1 is the preset differential coefficient for suppressing the temperature fluctuation; Δt is the sampling time interval (i.e., the time difference between two samplings); is the cumulative sum of the temperature deviations from the initial moment to the kth sampling moment (integral term), and j is the sampling moment; is the change rate of temperature deviation; then, according to the value of Output(k), adjust the output of the cooling or heating system; if Output(k) > 0, it means the temperature is too low, reduce the output of the cooling system or start heating; if Output(k) < 0, it means the temperature is too high, increase the output of the cooling system (such as increasing the water cooling flow rate or the rotation speed of the air cooling fan), and update the deviation value of the previous moment in real time , and then execute in a loop: repeat the process of the discrete-time PID control algorithm to achieve real-time temperature control.

[0026] Through the alarm protection mechanism, obtain the temperature deviation ΔT and the preset temperature deviation threshold ΔT threshold for comparison. If ΔT > ΔT threshold , the PLC controller will trigger an alarm: , if the temperature remains abnormal, the PLC controller will start the protection mechanism (such as automatic shutdown).

[0027] The speed control module conducts rolling speed control, specifically: Conduct rolling speed control based on the algorithm process of real-time monitoring and adjustment of the temperature control module and the pressure control module; S001: Define input variables, the temperature deviation e T and the pressure deviation e P , S002: Convert the input variables (the temperature deviation e T and the pressure deviation e P ) into fuzzy language variables; define fuzzy sets: the fuzzy set of the temperature deviation e T : {Negative Big (NB), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Big (PB)}; the fuzzy set of the pressure deviation e P : {Negative Big (NB), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Big (PB)}; use triangular or trapezoidal membership functions to map the actual deviation values to the fuzzy sets; the membership function of the temperature deviation e T : ; Similarly, obtain the membership function of the pressure deviation e P ; S003: Establish a fuzzy rule base according to process knowledge; Rule form: IF e T is A AND e p is B THEN ΔV is C; A and B are the fuzzy sets of the input variables; C is the fuzzy set of the output variable (speed adjustment amount ΔV); S004: Calculate the output of each rule using the Mamdani inference method; calculate the membership degree of the premise part (IF part) of each rule: μ rule =min(μ A (e T ), μ B (e P )); According to the membership degree of the premise part, trim the membership degree function of the output variable: μ C (ΔV)=min(μ rule , μ C (ΔV)); Synthesize the outputs of all rules to obtain the fuzzy output ΔV: μ total (ΔV)=max(μ C1 (ΔV), μ C2 (ΔV), …) S005: Convert the fuzzy output ΔV into a specific speed adjustment amount; use the centroid method for calculation: Calculate the centroid of the fuzzy output and use it as the final speed adjustment amount; S006: Calculate the new rolling speed according to the defuzzified speed adjustment amount ΔV: V new =V current +ΔV; where, V new is the target rolling speed; V current is the current rolling speed; and limit the speed range to ensure that the adjusted speed is within the preset allowable range [V min , V max ; S007: According to the adjusted speed V new , the PLC controller adjusts the rotational speed of the servo motor to drive the pressure roller to achieve speed adjustment.

[0028] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only the specific implementation manners. Obviously, according to the content of this specification, many modifications and changes can be made. These embodiments are selected and specifically described in this specification to better explain the principle and practical application of the present invention, so that those skilled in the art can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. A calender control system for thin photovoltaic glass production, comprising a calender main body (1), a control unit, a pressure regulation module, a temperature control module, and a speed control module; characterized in that: The calender main body (1) includes a lower pressing roller, a water cooling device, an air cooling device, a transition roller table and a transmission device; The control unit includes a PLC controller, sensors, actuators and a human-machine interface; the PLC controller is fixedly installed in the internal control cabinet of the calender main body (1), the pressure sensors are installed at the adjusting bearing positions of the cylindrical lower pressing roller 1 (8), the cylindrical lower pressing roller 2 (9), the cylindrical lower pressing roller 3 (10) and the cylindrical lower pressing roller 4 (11); the temperature sensors are installed at the corresponding positions inside the water cooling pipeline, the water tank (7) and the internal air duct of the air cooling device; the actuator for adjusting the turbine fan (6) of the air cooling device is installed inside the calender main body (1) and receives control signals through the PLC controller, and the human-machine interface is installed on the operation panel of the calender main body (1); The pressure adjustment module is used to monitor and adjust the pressure of the rolling mill; The temperature control module is used to monitor and adjust the rolling temperature; The speed control module controls the rolling speed.

2. The calender control system for thin photovoltaic glass production according to claim 1, characterized in that, The lower pressing roller includes the cylindrical lower pressing roller 1 (8), the cylindrical lower pressing roller 2 (9), the cylindrical lower pressing roller 3 (10) and the cylindrical lower pressing roller 4 (11), as well as the irregular hexagon column 1 (12), the irregular hexagon column 2 (13), the irregular hexagon column 3 (14) and the irregular hexagon column 4 (15); the water cooling device consists of a water tank (7), a water cooling pipeline and an external water cooling radiator tower; the transition roller table includes a feeding transition roller table (3) and a discharging transition roller table (2); the transmission device is directly driven by a servo motor; the air cooling device includes an air outlet (5), a turbine fan (6), an internal air duct and an air inlet louver (4); the cylindrical lower pressing roller 1 (8), the cylindrical lower pressing roller 2 (9), the cylindrical lower pressing roller 3 (10), the cylindrical lower pressing roller 4 (11), as well as the irregular hexagon column 1 (12), the irregular hexagon column 2 (13), the irregular hexagon column 3 (14) and the irregular hexagon column 4 (15) are all rotationally and fixedly connected to the calender main body (1) through adjusting bearings and servo motors, the feeding transition roller table (3) and the discharging transition roller table (2) are rotationally and fixedly connected to the calender main body (1) and are driven by a servo motor; the turbine fan (6), the air outlet (5), the water tank (7), the air inlet louver (4), the upper pressing roller wall (17) and the lower pressing roller wall (16) are fixedly installed inside the calender main body (1).

3. The calender control system for thin photovoltaic glass production according to claim 1, characterized in that, The specific process of the pressure adjustment module for monitoring and adjusting the pressure of the rolling mill is as follows: The sensors collect data in real time: the pressure sensors installed on the cylindrical lower pressing roller 1 (8), the cylindrical lower pressing roller 2 (9), the cylindrical lower pressing roller 3 (10) and the cylindrical lower pressing roller 4 (11) monitor the pressure data of each pressing roller in real time and transmit the pressure data to the PLC controller; the pressure data of the sensors includes instantaneous pressure, average pressure and pressure fluctuation value; When the PLC controller receives the pressure data, it performs outlier detection, smoothing processing and statistical analysis.

4. The calender control system for thin photovoltaic glass production according to claim 3, wherein, The specific process of performing outlier detection, smoothing processing and statistical analysis is as follows: S01: Perform outlier detection: Use the box plot method to remove abnormal data: Calculate the first quartile Q1 and the third quartile ; Preset the outlier range: or P i > Q3 + 1.5 × IQR; If a certain pressure data P i exceeds this range, it is determined as an outlier, and an abnormal pressure data instruction is generated; S02: Perform smoothing processing: Calculate the pressure trend using the moving average method: , where M is the moving window size; S03: Conduct statistical analysis: Set the pressure threshold within the normal operating range, based on historical data statistics or empirical formulas: , P max = μ + k2σ; k1, k2 are threshold coefficients; P min , P max are the lower and upper pressure thresholds respectively; According to the collected smoothed pressure value , conduct pressure status classification: When the collected smoothed pressure value , it belongs to the normal state, that is, P min ≤ ≤ P max , then the device operates normally and no adjustment is required; The collected smoothed pressure value belongs to the overpressure state, that is > P max , trigger the overpressure adjustment process; When the collected smoothed pressure value , it belongs to the underpressure state, that is, P min < , trigger the underpressure adjustment process; S04: When the pressure exceeds the threshold, automatically adjust the actuator of the roller compactor, set the target, P 目标 = μ; Adjustment step setting: , where β is the adjustment coefficient; ΔP is the pressure adjustment amount; cause the position of the roller of the roller compactor to change: , where θ(t) is the current servo motor angle and γ is the pressure-angle conversion coefficient; continuously monitor the pressure data and adjust based on the PID control model: , is the error, K p , K i , K d are the PID control parameters.

5. The calender control system for thin photovoltaic glass production according to claim 1, characterized in that, The temperature control module is used to monitor and adjust the rolling temperature, specifically: Real-time monitor the temperature changes of the water-cooling and air-cooling systems; the temperature sensors collect temperature data in real time and transmit the temperature and pressure data to the PLC controller for real-time processing and analysis.

6. The calender control system for thin photovoltaic glass production according to claim 4, characterized in that, The specific process of performing the above real-time processing and analysis: The temperature sensor collects temperature data in real time, denoted as T 当前 ; According to the characteristics of the rolled material, the temperature range is set in the PLC controller in advance: including the minimum temperature T min and the maximum temperature T max ; Determine the temperature range T min ≤T 当前 ≤T max ; The PLC controller calculates the deviation between the current temperature and the target temperature range: If T 当前 <T min , then the temperature is too low, and the deviation is: ; If T 当前 >T max , then the temperature is too high, and the deviation is: ; According to the historical temperature data, calculate the temperature change trend: Through the formula: , T 上 is the temperature value collected last time, and Δt is the time interval between two collections; Adopt the discrete-time PID control algorithm: Discretize the continuous-time PID formula, and the formula is: , Output(k) is the control output at the k-th sampling moment; e(k) is the temperature deviation at the k-th sampling moment; k p1 is the preset proportional coefficient; K j1 is the preset integral coefficient; K d1 is the preset derivative coefficient; Δt is the sampling time interval; is the cumulative sum of temperature deviations from the initial moment to the k-th sampling moment; is the change rate of temperature deviation; then, according to the value of Output(k), adjust the output of the cooling or heating system; if Output(k) > 0, reduce the output of the cooling system or start heating; if Output(k) < 0, increase the output of the cooling system, and update the deviation value of the previous moment in real time e(k−1)=e(k); repeat the process of the discrete-time PID control algorithm to achieve real-time temperature control; Through the alarm protection mechanism, obtain the temperature deviation ΔT and the preset temperature deviation threshold ΔT threshold Compare them. If ΔT > ΔT threshold , the PLC controller will trigger an alarm: , if the temperature remains abnormal, the PLC controller will activate the preset protection mechanism.

7. The calender control system for thin photovoltaic glass production according to claim 1, characterized in that, The specific process of the speed control module for controlling the rolling speed is as follows: Based on the algorithm process of real-time monitoring and adjustment of the temperature control module and the pressure control module, the rolling speed is controlled; S001: Definition of input variables, temperature deviation e T and pressure deviation e P , S002: Convert the input variable into a fuzzy linguistic variable; define the fuzzy sets: the fuzzy set of temperature deviation e T : {Negative Big (NB), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Big (PB)}; the fuzzy set of pressure deviation e P : {Negative Big (NB), Negative Small (NS), Zero (ZO), Positive Small (PS), Positive Big (PB)}; use triangular or trapezoidal membership functions to map the actual deviation values to the fuzzy sets; the membership function of temperature deviation e T : ； Similarly, the membership function of the pressure deviation e is obtained. P ; S003: Establish a fuzzy rule base according to process knowledge; Rule form: IF e T is A AND e p is B THEN ΔV is C; A and B are fuzzy sets of input variables; C is the fuzzy set of the output variable; S004: Calculate the output of each rule using the Mamdani inference method; calculate the membership degree of the premise part of each rule: μ rule = min(μ A (e T ), μ B (e P )); According to the membership degree of the premise part, trim the membership function of the output variable: μ C (ΔV) = min(μ rule , μ C (ΔV)); Synthesize the outputs of all rules to obtain the fuzzy output ΔV: μ total (ΔV)=max(μ C1 (ΔV), μ C2 (ΔV), …) S005: Convert the fuzzy output ΔV into a specific speed adjustment amount; calculate using the centroid method: Calculate the centroid of the fuzzy output and use it as the final speed adjustment amount; S006: Calculate the new rolling speed according to the defuzzified speed adjustment amount ΔV; V new =V current +ΔV; V new is the target rolling speed; V current is the current rolling speed; and limit the speed range so that the adjusted speed is within the preset allowable range [V min , V max ; S007: According to the adjusted speed V new , the PLC controller adjusts the rotational speed of the servo motor to drive the pressure roller to achieve speed adjustment.

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