Detection method and system applied to film blowing forming equipment

Abstract

The invention relates to a detection method and system applied to film blowing forming equipment. The detection method comprises the following steps that parameter data of film thickness, temperature and airflow pressure in the film blowing process are collected; collecting change data of temperature and airflow pressure influencing the performance of the sensor; establishing a mathematical model between the parameter data and the change data according to the historical sensor data and the historical change data; calculating a compensation factor according to the established mathematical model and real-time sensor data; correcting the output data of the sensor; target control parameter data are set, the deviation between the compensated parameter data and the target control parameter data is calculated, and a control signal is generated and fed back to a control system of the film blowing forming equipment; according to the scheme, the influence of environmental change on the performance of the sensor is analyzed, and real-time correction is carried out through a compensation algorithm, so that key parameter data in the film blowing process are more accurate, and the film quality and the stability of the production process are improved.

Description

Technical Field

[0001] The invention specifically relates to a detection method and a system thereof applied to film blowing molding equipment. Background Art

[0002] Blown film molding technology is widely used in the production of plastic films, especially in the packaging industry. This process blows molten plastic materials into thin films, which has the advantages of high production efficiency, uniform film thickness, and wide application range. However, in the process of blown film molding, the control accuracy of the molding equipment, environmental conditions, and the performance stability of the sensor have a crucial impact on the quality and production efficiency of the final product.

[0003] In the film blowing process, the key control parameters include film thickness, temperature and airflow pressure. These parameters directly affect the quality of the film and the stability of production. Usually, the film blowing equipment is equipped with temperature sensors, film thickness sensors, airflow pressure sensors, etc., which are used to monitor and control the changes of these key parameters in real time. However, due to changes in ambient temperature, airflow fluctuations and performance deviations of the sensors themselves, errors may occur in the sensor measurement values, causing the control system to make decisions based on inaccurate parameters when adjusting the film blowing process, thereby affecting the quality of the film and production efficiency.

[0004] For example, in actual production, fluctuations in environmental factors such as temperature and airflow pressure will affect the sensor readings, resulting in deviations in the measurement of parameters such as film thickness, temperature, and airflow pressure. If these errors are not corrected, they will directly affect the quality control of the film blowing process, causing problems such as uneven film thickness and unstable bubbles, ultimately leading to reduced production efficiency and increased scrap rates.

[0005] Most current solutions focus on reducing errors through standardized equipment and stable environmental conditions. However, environmental conditions will inevitably change, and sensor performance will age over time, leading to the accumulation of measurement errors in long-term operation. Existing technologies lack an effective real-time compensation mechanism to deal with measurement errors caused by external factors or sensor changes.

[0006] Therefore, how to solve the measurement errors caused by changes in sensor performance or fluctuations in the external environment, and on this basis achieve precise adjustment of key control parameters in the film blowing process, is an important technical challenge to improve the production stability and film quality of film blowing molding equipment. Summary of the invention

[0007] In order to overcome the deficiencies and shortcomings of the prior art, the present invention proposes a detection method and system for film blowing molding equipment. The method collects historical data and real-time data of the sensor, analyzes the impact of environmental changes on sensor performance, and performs real-time correction through a compensation algorithm, thereby ensuring that key parameter data in the film blowing process is more accurate, thereby improving the quality of the film and the stability of the production process.

[0008] The primary purpose of the present invention is achieved through the following technical solutions:

[0009] A detection method for film blowing equipment comprises the following steps:

[0010] Collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data;

[0011] Collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain the historical change data and real-time change data;

[0012] According to the historical sensor data and historical change data, analyze the impact of the change data on the parameter data, and establish a mathematical model between the parameter data and the change data;

[0013] Calculate compensation factors based on the established mathematical model and real-time sensor data;

[0014] According to the calculated compensation factor, the output data of the sensor is corrected to obtain the compensated parameter data of temperature and airflow pressure;

[0015] The target control parameter data is set, and the deviation between the compensated parameter data and the target control parameter data is calculated, and a control signal is generated and fed back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

[0016] Preferably, the method for obtaining historical sensor data and real-time sensor data is:

[0017] Install a film thickness sensor in the molding area of ​​the film blowing equipment;

[0018] Install a temperature sensor in the die area;

[0019] Install an air flow pressure sensor in the air flow duct.

[0020] As a preference, the mathematical model between the parameter data and the variation data is established as follows:

[0021] A linear regression model is established to show the influence of the changing data on the parameter data, which is expressed as:

[0022] Y=β 0 +β 1 *T+β2 *P

[0023] Where Y is the film thickness, T is the temperature, P is the airflow pressure, and β0, β1, and β2 are the regression coefficients to be estimated.

[0024] Preferably, the method for calculating the compensation factor is:

[0025] Get the original sensor output data from the temperature sensor and the airflow pressure sensor. Let the original output data of these sensors be temperature Traw and airflow pressure Praw;

[0026] Based on the environmental change data and the sensor performance change model, the compensation factor C for temperature is calculated. T Compensation factor C for air flow pressure P ;

[0027] For the temperature compensation factor:

[0028] C T =T actual / T pred

[0029] Among them, T actual is the actual temperature data, T pred It is the temperature data predicted based on the environmental model;

[0030] For airflow pressure compensation factor:

[0031] C P =P actual / P pred

[0032] Among them, P actual is the actual air flow pressure data, P pred It is the airflow pressure data predicted based on the environmental model.

[0033] Preferably, the method for correcting the output data of the sensor according to the calculated compensation factor is:

[0034] Compensated temperature data T corrected Calculated by the following formula:

[0035] T corrected =T raw ×C T

[0036] Compensated air flow pressure data P corrected Calculated by the following formula:

[0037] P corrected =P raw ×C P

[0038] Corrected temperature and airflow pressure data T corrected and P corrected That is the actual parameter data after compensation.

[0039] Preferably, the method for calculating the deviation between the compensated parameter data and the target control parameter data is:

[0040] Temperature deviation:

[0041] ΔT=T corrected -T target

[0042] Airflow pressure deviation:

[0043] ΔP=P corrected -P target

[0044] Among them, ΔT is the temperature deviation, and ΔP is the airflow pressure deviation.

[0045] Preferably, the method of generating a control signal and feeding it back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process is:

[0046] The proportional-integral-differential control algorithm is adopted, as follows:

[0047]

[0048] Among them, u(t) is the control signal, K p ,K i ,K d are the proportional, integral and differential coefficients respectively;

[0049] Based on the control algorithm and deviation value calculated above, a control signal is generated. The formula for generating the control signal is as follows:

[0050] u T =f(ΔT,T corrected ,T target )

[0051] u P =f(ΔP,P corrected ,P target )

[0052] Among them, u T and u P are the control signals for adjusting the temperature and airflow pressure, respectively, and f(…) is the output of the control algorithm;

[0053] The generated control signal u T and u PFeedback is sent to the control system of the film blowing equipment to adjust the key parameters of the equipment.

[0054] Another technical problem to be solved by the present invention is to provide a detection system for film blowing molding equipment, comprising:

[0055] Data acquisition module, used to collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data;

[0056] The change data acquisition module is used to collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain historical change data and real-time change data;

[0057] A data analysis module is used to analyze the impact of change data on parameter data based on historical sensor data and historical change data, and to establish a mathematical model between parameter data and change data;

[0058] A compensation factor calculation module, used to calculate the compensation factor according to the mathematical model and real-time sensor data;

[0059] A data correction module, used to correct the output data of the sensor according to the calculated compensation factor to obtain compensated parameter data of temperature and airflow pressure;

[0060] A target control setting module is used to set target control parameter data;

[0061] A deviation calculation and control signal generation module, used to calculate the deviation between the compensated parameter data and the target control parameter data, and generate a control signal;

[0062] The feedback control module is used to feed back the generated control signal to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

[0063] Another technical problem to be solved by the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a detection method applied to film blowing molding equipment as described above is implemented.

[0064] Another technical problem to be solved by the present invention is to provide a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the detection method applied to a film blowing molding device as described above is implemented.

[0065] Compared with the prior art, the present invention has the following advantages:

[0066] The performance of the sensor is affected by environmental factors such as temperature and airflow pressure, which may cause deviations in the measured data. The solution collects real-time and historical sensor data and change data, establishes a mathematical model, analyzes the impact of environmental factors on sensor performance, and calculates compensation factors to perform real-time compensation, ensuring that the acquired parameter data such as temperature and airflow pressure are more accurate.

[0067] By real-time monitoring and correcting sensor output data, the solution can ensure that key control parameters in the film blowing process (such as film thickness, temperature, airflow pressure, etc.) are always maintained within the target range, eliminating parameter fluctuations caused by environmental changes or sensor errors, thereby achieving precise control of the film blowing process.

[0068] Through real-time feedback adjustment and control system, the solution effectively avoids unstable film quality caused by measurement errors or environmental changes, improves the accuracy of blown film molding and product quality, and reduces the scrap rate caused by inaccurate parameters in the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] Figure 1 The present invention is a flow chart of a detection method applied to film blowing molding equipment. DETAILED DESCRIPTION

[0070] The specific implementation modes of the present invention are further described in detail to make the technical solutions of the present invention easier to understand and grasp.

[0071] Example

[0072] See also Figure 1 As shown, a detection method applied to film blowing molding equipment includes the following steps:

[0073] Collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data;

[0074] Collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain the historical change data and real-time change data;

[0075] According to the historical sensor data and historical change data, analyze the impact of the change data on the parameter data, and establish a mathematical model between the parameter data and the change data;

[0076] Calculate compensation factors based on the established mathematical model and real-time sensor data;

[0077] According to the calculated compensation factor, the output data of the sensor is corrected to obtain the compensated parameter data of temperature and airflow pressure;

[0078] The target control parameter data is set, and the deviation between the compensated parameter data and the target control parameter data is calculated, and a control signal is generated and fed back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

[0079] By analyzing the relationship between historical sensor data and environmental change data and establishing a mathematical model, external factors that affect sensor output accuracy (such as temperature, airflow pressure fluctuations, etc.) can be effectively identified. Based on this analysis, real-time calculation of compensation factors and correction of sensor data can eliminate or reduce sensor errors and provide more accurate parameter data. This enables the control system to make decisions based on more accurate data, thereby improving the stability of the film blowing process.

[0080] The key to this method is to calculate the compensation factor based on real-time data and historical data and correct the output data of the sensor. This real-time correction mechanism enables quick adjustments when environmental conditions or equipment status change, ensuring that key parameters in the production process (such as film thickness, temperature, and airflow pressure) are always within the ideal range, avoiding product quality fluctuations caused by sensor errors.

[0081] By reducing quality instability and scrap rates caused by sensor errors or external environmental fluctuations, overall production efficiency is improved. Accurate real-time control can reduce equipment downtime and adjustment time, making the production process smoother and avoiding frequent manual intervention and debugging, thereby improving the efficiency and automation level of the production line.

[0082] In the process of blown film, the thickness and quality of the film are crucial to the final product. Through this detection method, the control system can adjust key parameters more accurately to avoid problems such as uneven film thickness and unstable temperature, thereby reducing waste and quality fluctuations. Especially in the production of films with high precision requirements, maintaining the stability of parameters is of great significance to reducing waste and improving the pass rate.

[0083] Since this method takes into account the impact of the external environment (such as temperature and airflow pressure changes) on sensor performance, it can make the film blowing equipment more adaptable in complex production environments. Regardless of factors such as ambient temperature fluctuations, airflow pressure changes or equipment aging, the compensation mechanism can be used to make real-time adjustments to maintain long-term stable operation of the equipment.

[0084] During the production process, setting the target control parameters (such as film thickness, temperature, air flow pressure, etc.) and constantly adjusting them according to the compensated data can ensure that the film blowing equipment always runs towards the optimal production conditions. The control system can accurately adjust the equipment operation by calculating the deviation between the compensated parameters and the target control parameters, ensuring that the key control parameters in the production process always meet the optimal requirements, thereby achieving higher quality film products.

[0085] This detection method is based on data collection and real-time feedback, combined with mathematical modeling and compensation algorithms, which can achieve more intelligent production process adjustment, further promoting the automation level of film blowing equipment. By combining with the control system of film blowing equipment, automatically generating control signals and making feedback adjustments, the system can autonomously and accurately adjust parameters, reduce manual intervention, and improve the automation and intelligence of the overall production line.

[0086] The methods for obtaining historical sensor data and real-time sensor data are:

[0087] Install a film thickness sensor in the molding area of ​​the film blowing equipment;

[0088] Install a temperature sensor in the die area;

[0089] Install an air flow pressure sensor in the air flow duct.

[0090] Installing film thickness sensors in the film blowing area, temperature sensors in the die area, and airflow pressure sensors in the airflow duct can fully cover the main control parameters in the film blowing process. This ensures that all important data from film thickness, temperature to airflow pressure are monitored and recorded in real time, reducing omissions and providing more accurate process data. This is crucial for subsequent analysis and control.

[0091] By collecting real-time data, the changes in various parameters during the production process can be dynamically monitored. If a parameter (such as film thickness, temperature or airflow pressure) deviates from the target range, the system can quickly provide feedback and make adjustments. This allows problems in the production process to be discovered and handled in a timely manner, avoiding quality fluctuations or material waste, thereby improving production efficiency and the quality consistency of membrane products.

[0092] Installing different types of sensors can obtain historical data and provide rich samples for building mathematical models. By analyzing the relationship between these historical data and real-time data, we can better understand the impact of different factors on key parameters such as film thickness. By establishing an accurate mathematical model, the system can make effective compensation based on real-time data in subsequent processes, improving the predictability and stability of the production process.

[0093] The mathematical model between parameter data and change data is established as:

[0094] A linear regression model is established to show the influence of the changing data on the parameter data, which is expressed as:

[0095] Y=β 0 +β 1 *T+β 2 *P

[0096] Where Y is the film thickness, T is the temperature, P is the airflow pressure, and β0, β1, and β2 are the regression coefficients to be estimated.

[0097] The linear regression model simplifies what could otherwise be a very complex process by assuming a linear relationship between film thickness (Y) and temperature (T) and airflow pressure (P). This simplification makes it easier for engineers or operators to understand how the various parameters affect film thickness together. Such a model not only facilitates quick calculations, but also helps decision makers make accurate data-based decisions.

[0098] By estimating the regression coefficient (β 1 ,β 2 ), the degree of influence of temperature and airflow pressure on film thickness can be clearly determined. This allows operators to control the change of film thickness by adjusting temperature or airflow pressure during the production process, accurately adjust production conditions, and optimize product quality. For example, if the film thickness deviates from the target at a certain moment, the effect of adjusting temperature or airflow pressure can be predicted based on the regression coefficient, thereby achieving effective control of film thickness.

[0099] The linear regression model is not only suitable for real-time control, but also for predicting future situations. Based on known temperature and airflow pressure data, the model can predict changes in film thickness. This prediction function is crucial for production planning, quality control, and fault warning systems. If the actual film thickness data does not match the predicted value, it may mean that the equipment has failed or deviated, which helps to detect problems early and take corresponding measures, reduce downtime and material waste, and improve production efficiency and product consistency.

[0100] The method to calculate the compensation factor is:

[0101] Get the original sensor output data from the temperature sensor and the airflow pressure sensor. Let the original output data of these sensors be temperature Traw and airflow pressure Praw;

[0102] Based on the environmental change data and the sensor performance change model, the compensation factor C for temperature is calculated. T Compensation factor C for air flow pressure P ;

[0103] For the temperature compensation factor:

[0104] C T =T actual / T pred

[0105] Among them, T actual is the actual temperature data, T pred It is the temperature data predicted based on the environmental model;

[0106] For airflow pressure compensation factor:

[0107] C P =P actual / P pred

[0108] Among them, P actual is the actual air flow pressure data, P pred It is the airflow pressure data predicted based on the environmental model.

[0109] The output of the temperature and airflow pressure sensors may be affected by environmental factors, sensor aging or other external interference, resulting in a certain error in the raw data. T ) and airflow pressure compensation factor (C P ), can correct the measurement error of the sensor and ensure that the data output by the sensor is more accurate and reliable. This is crucial for accurately controlling film thickness and other key production parameters.

[0110] Environmental changes (such as temperature fluctuations, airflow changes, etc.) may cause the performance of the sensor to shift, directly affecting the stability of the production process. By calculating and applying the compensation factor (C T and C P ), can dynamically adjust sensor data according to environmental changes. This means that even when environmental conditions change, the production process can still maintain high stability and accuracy, reducing production fluctuations or quality inconsistencies caused by environmental changes.

[0111] Compensation factors for temperature and airflow pressure not only correct sensor errors, but also provide an accurate basis for process control. By using the ratio of actual data to environmental model prediction data as compensation factors, the difference between the sensor and actual production conditions can be better understood, thereby optimizing the production process. For example, compensation factors can help determine which factors have a greater impact on film thickness changes, so that temperature or airflow pressure can be accurately adjusted to ensure that product quality meets the expected standards. In addition, historical data on compensation factors can be used to adjust the environmental model over time to further improve prediction accuracy.

[0112] According to the calculated compensation factor, the method for correcting the output data of the sensor is:

[0113] Compensated temperature data T corrected Calculated by the following formula:

[0114] T corrected =T raw ×C T

[0115] Compensated air flow pressure data P corrected Calculated by the following formula:

[0116] P corrected =P raw ×C P

[0117] The corrected temperature and airflow pressure data Tcorrected and Pcorrected are the compensated actual parameter data.

[0118] The introduction of compensation factors can correct sensor errors caused by factors such as temperature and airflow pressure. corrected =T raw ×C T and P corrected =P raw ×C P The correction formula can effectively reduce the impact of external environmental changes on sensor output, thereby improving the accuracy of temperature and airflow pressure data. This precise data can better reflect the control status of the actual film blowing process and avoid production fluctuations or quality problems caused by inaccurate data.

[0119] The corrected temperature and airflow pressure data enable the control system to understand the current equipment status more accurately, so as to make more accurate adjustments; for example, accurate temperature and airflow pressure data can help adjust the heating, cooling and airflow adjustment parameters of the film blowing machine to ensure the uniformity and quality stability of the film. Through effective control feedback, the occurrence of uneven film thickness or other defects can be reduced, and the consistency and quality of the final product can be improved.

[0120] Since environmental factors (such as temperature changes, air flow fluctuations, etc.) often affect the performance of sensors, using compensation factors to calibrate sensors can reduce the impact of these changes on equipment operation; in actual production, fluctuations in the accuracy of sensor data may lead to frequent equipment adjustments, increasing the risk of failure or downtime. After compensation, the data provided by the sensor will be more stable, helping the production line maintain a consistent operating state, thereby improving the stability and reliability of the equipment and reducing maintenance costs and downtime.

[0121] The method for calculating the deviation between the compensated parameter data and the target control parameter data is:

[0122] Temperature deviation:

[0123] ΔT=T corrected -T target

[0124] Airflow pressure deviation:

[0125] ΔP=P corrected -P target

[0126] Among them, ΔT is the temperature deviation, and ΔP is the airflow pressure deviation.

[0127] The method of generating control signals and feeding back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process is:

[0128] The proportional-integral-differential control algorithm is adopted, as follows:

[0129]

[0130] Among them, u(t) is the control signal, K p ,K i ,K d are the proportional, integral and differential coefficients respectively;

[0131] Based on the control algorithm and deviation value calculated above, a control signal is generated. The formula for generating the control signal is as follows:

[0132] u T =f(ΔT,T corrected ,T target )

[0133] u P =f(ΔP,P corrected ,P target )

[0134] Among them, u T and u P are the control signals for adjusting the temperature and airflow pressure, respectively, and f(…) is the output of the control algorithm;

[0135] The generated control signal u T and u P Feedback is sent to the control system of the film blowing equipment to adjust the key parameters of the equipment.

[0136] By calculating the deviations ΔT and ΔP and combining them with the proportional-integral-derivative (PID) control algorithm, the system can adjust the temperature and airflow pressure in real time to accurately align the actual value with the target value. This instant feedback can effectively reduce fluctuations and quickly respond to changes in equipment status, thereby maintaining the stability of the production process.

[0137] PID control automatically generates control signals based on current deviations, reducing the need for manual adjustments by operators. By continuously optimizing the regulation of temperature and airflow pressure, the efficient operation of the equipment is ensured, the possibility of human error is reduced, and production efficiency and consistency are improved.

[0138] By continuously adjusting the temperature and airflow pressure, the system can stably control the key parameters in the film blowing process to ensure uniform film thickness and product quality consistency. PID control can effectively eliminate the impact of external disturbances and keep the equipment in the optimal state, thereby enhancing the reliability of the production line and the quality stability of the product.

[0139] A detection system for film blowing equipment, comprising:

[0140] Data acquisition module, used to collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data;

[0141] The change data acquisition module is used to collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain historical change data and real-time change data;

[0142] A data analysis module is used to analyze the impact of change data on parameter data based on historical sensor data and historical change data, and to establish a mathematical model between parameter data and change data;

[0143] A compensation factor calculation module, used to calculate the compensation factor according to the mathematical model and real-time sensor data;

[0144] A data correction module, used to correct the output data of the sensor according to the calculated compensation factor to obtain compensated parameter data of temperature and airflow pressure;

[0145] A target control setting module is used to set target control parameter data;

[0146] A deviation calculation and control signal generation module, used to calculate the deviation between the compensated parameter data and the target control parameter data, and generate a control signal;

[0147] The feedback control module is used to feed back the generated control signal to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

[0148] By correcting the sensor data (based on the calculation of compensation factors and mathematical models), the measurement deviation caused by sensor errors, environmental changes, etc. can be effectively reduced. In this way, the data of key parameters such as temperature and airflow pressure can be more accurate, thereby improving the control accuracy and stability of the film blowing process and avoiding production instability and quality fluctuations caused by parameter fluctuations.

[0149] The change data acquisition module can monitor external changes that affect sensor performance in real time, such as temperature changes, airflow pressure fluctuations, etc. By collecting these change data in real time and combining them with historical data for analysis, a more reliable mathematical model can be established to dynamically compensate according to environmental changes and ensure the system's adaptability to external interference. This can maintain efficient operation of the system even in an unstable environment and reduce errors and defects in the production process.

[0150] Through the target control setting module and the deviation calculation and control signal generation module, the system can automatically calculate the deviation between the target parameters and real-time data and generate accurate control signals. This automatic adjustment reduces the need for manual intervention, improves production efficiency and operational convenience, and reduces errors and production losses caused by human factors. In addition, accurate control of key parameters in the film blowing process can also extend equipment life and reduce maintenance costs.

[0151] This embodiment also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the detection method for film blowing molding equipment as described above when executing the program.

[0152] This embodiment further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the detection method applied to the film blowing molding equipment as described above is implemented.

[0153] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0154] Those skilled in the art will clearly understand that for the sake of convenience and brevity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above.

[0155] Of course, the above are only typical examples of the present invention. In addition to these, the present invention may also have many other specific implementations. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope of protection required by the present invention. Of course, the above are only typical examples of the present invention. In addition to these, the present invention may also have many other specific implementations. Any technical solutions formed by equivalent replacement or equivalent transformation fall within the scope of protection required by the present invention.

Claims

1. A detection method for film blowing equipment, characterized in that , including the following steps: Collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data; Collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain the historical change data and real-time change data; According to the historical sensor data and historical change data, analyze the impact of the change data on the parameter data, and establish a mathematical model between the parameter data and the change data; Calculate compensation factors based on the established mathematical model and real-time sensor data; According to the calculated compensation factor, the output data of the sensor is corrected to obtain the compensated parameter data of temperature and airflow pressure; The target control parameter data is set, and the deviation between the compensated parameter data and the target control parameter data is calculated, and a control signal is generated and fed back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

2. The detection method applied to film blowing molding equipment according to claim 1, characterized in that: The methods for obtaining historical sensor data and real-time sensor data are: Install a film thickness sensor in the molding area of ​​the film blowing equipment; Install a temperature sensor in the die area; Install an air flow pressure sensor in the air flow duct.

3. The detection method applied to film blowing molding equipment according to claim 1, characterized in that: The mathematical model between parameter data and change data is established as: A linear regression model is established to show the influence of the changing data on the parameter data, which is expressed as: Y=β0+β1*T+β2*P Where Y is the film thickness, T is the temperature, P is the airflow pressure, and β0, β1, and β2 are the regression coefficients to be estimated.

4. The detection method applied to film blowing molding equipment according to claim 3 is characterized in that: The method to calculate the compensation factor is: Get the original sensor output data from the temperature sensor and the airflow pressure sensor. Let the original output data of these sensors be temperature Traw and airflow pressure Praw; Based on the environmental change data and the sensor performance change model, the compensation factor C for temperature is calculated. T Compensation factor C for air flow pressure P ; For the temperature compensation factor: C T =T actual / T pred Among them, T actual is the actual temperature data, T pred It is the temperature data predicted based on the environmental model; For airflow pressure compensation factor: C P =P actual / P pred Among them, P actual is the actual air flow pressure data, P pred It is the airflow pressure data predicted based on the environmental model.

5. The detection method applied to film blowing molding equipment according to claim 4 is characterized in that: According to the calculated compensation factor, the method for correcting the output data of the sensor is: Compensated temperature data T corrected Calculated by the following formula: T corrected =T raw ×C T Compensated air flow pressure data P corrected Calculated by the following formula: P corrected =P raw ×C P Corrected temperature and airflow pressure data T corrected and P corrected That is the actual parameter data after compensation.

6. The detection method applied to film blowing molding equipment according to claim 5, characterized in that: The method for calculating the deviation between the compensated parameter data and the target control parameter data is: Temperature deviation: ΔT=T corrected -T target Airflow pressure deviation: ΔP=P corrected -P target Among them, ΔT is the temperature deviation, and ΔP is the airflow pressure deviation.

7. The detection method applied to film blowing molding equipment according to claim 6, characterized in that: The method of generating control signals and feeding back to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process is: The proportional-integral-differential control algorithm is adopted, as follows: Among them, u(t) is the control signal, K p ,K i ,K d are the proportional, integral and differential coefficients respectively; Based on the control algorithm and deviation value calculated above, a control signal is generated. The formula for generating the control signal is as follows: u T =f(ΔT,T corrected ,T target ) u P =f(ΔP,P corrected ,P target ) Among them, u T and u P are the control signals for adjusting the temperature and airflow pressure, respectively, and f(…) is the output of the control algorithm; The generated control signal u T and u P Feedback is sent to the control system of the film blowing equipment to adjust the key parameters of the equipment.

8. A detection system for film blowing equipment, characterized in that: Included are: Data acquisition module, used to collect parameter data of film thickness, temperature, and airflow pressure during the film blowing process, and obtain historical sensor data and real-time sensor data; The change data acquisition module is used to collect the change data of temperature and airflow pressure that affect the performance of the sensor, and obtain historical change data and real-time change data; A data analysis module is used to analyze the impact of change data on parameter data based on historical sensor data and historical change data, and to establish a mathematical model between parameter data and change data; A compensation factor calculation module, used to calculate the compensation factor according to the mathematical model and real-time sensor data; A data correction module, used to correct the output data of the sensor according to the calculated compensation factor to obtain compensated parameter data of temperature and airflow pressure; A target control setting module is used to set target control parameter data; A deviation calculation and control signal generation module, used to calculate the deviation between the compensated parameter data and the target control parameter data, and generate a control signal; The feedback control module is used to feed back the generated control signal to the control system of the film blowing molding equipment to adjust the key control parameters in the film blowing process.

9. An electronic device, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the program, the detection method applied to the film blowing molding equipment as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the detection method applied to film blowing molding equipment as described in any one of claims 1 to 7 is implemented.

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