Intelligent steam control system of steam setting machine
Through the integrated steam intelligent control system, the steam supply subsystem, flow regulation subsystem, etc. can be used to achieve accurate control of steam supply and flow. Combined with technologies such as artificial intelligence and deep learning, the accuracy and intelligence of the traditional steam shaping machine control system are solved. The problem has improved product quality and equipment reliability, expanded the scope of application, and promoted the technological progress of the industry.
Patent Information
- Application Number
- CN202411356407.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-27
- Publication Date
- 2025-01-03
AI Technical Summary
The traditional steam styling machine control system has insufficient steam supply and flow control, low data processing efficiency, lack of intelligent monitoring and self-adjustment capabilities, resulting in unstable product quality, insufficient equipment reliability, and limited applicability, making it difficult to stand out in the market. .
A steam intelligent control system was designed, integrating steam supply subsystem, flow regulation subsystem, pressure monitoring subsystem, data acquisition and processing subsystem, as well as new technology subsystem based on artificial intelligence, the Internet of Things, deep learning and quantum computing The system uses unique algorithms and formulas to achieve precise control of steam supply and flow, and has intelligent fault prediction and adaptive adjustment functions to improve the intelligence and reliability of the system.
It realizes precise control of steam supply and flow, improves the performance and working quality of the steam shaping machine, enhances the intelligence level and reliability of the system, expands the scope of application, enhances the competitiveness of the enterprise, and provides new technologies for the industry. The development direction has created higher commercial value.
Smart Images
Figure CN119247740A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the technical field of mechanical engineering, and in particular relates to a steam intelligent control system of a steam setting machine. Background Art
[0002] With the continuous development of industrial technology, steam setting machines play an important role in many fields. However, the traditional steam setting machine control system has many limitations.
[0003] In the existing technology, steam supply and flow control are often not precise enough to meet the increasing process requirements, resulting in unstable product quality. At the same time, data processing efficiency is low, the system lacks intelligent monitoring, prediction and self-adjustment capabilities, and the reliability of equipment operation needs to be improved. Moreover, the applicability of different types of steam setting machines is relatively limited and cannot be flexibly adapted to a variety of application scenarios.
[0004] In addition, with the increasingly fierce market competition, it is difficult for existing technical solutions to stand out in the competition, and enterprises are facing great competitive pressure. The overall technological development of the industry is also relatively slow, lacking breakthrough technical ideas and development directions.
[0005] In this context, the present invention aims to provide a steam intelligent control system for a steam setting machine, which innovatively integrates a variety of advanced technologies and subsystems, and achieves precise control of steam supply and flow through the application of unique algorithms and formulas, thereby improving performance and work quality. Functions such as intelligent fault prediction and adaptive adjustment greatly improve the intelligence level and reliability of the system. Efficient data processing ensures the stable operation of the system, and its wide applicability enables the system to be applied to various types of steam setting machines. Its unique technical solution not only enhances the competitiveness of enterprises, but also provides a new direction for the development of the industry. It has significant commercial value, can create higher economic benefits, and promote the entire steam setting machine industry to a new stage of development. Summary of the invention
[0006] The present invention mainly solves the technical problems existing in the above-mentioned prior art and provides a steam intelligent control system for a steam setting machine.
[0007] The above-mentioned technical problems of the present invention are mainly solved by the following technical solutions: a steam intelligent control system for a steam setting machine, comprising a basic subsystem and a new technology subsystem, wherein the basic subsystem includes a steam supply subsystem, a steam flow regulation subsystem, a pressure monitoring subsystem, a temperature monitoring subsystem, and a data acquisition and processing subsystem; the new technology subsystem includes an artificial intelligence-based fault prediction subsystem, an intelligent adaptive regulation subsystem, an Internet of Things connection and remote control subsystem, a deep learning optimization subsystem, a quantum computing assisted decision-making subsystem, and a micro-nano material application subsystem; the basic subsystem and the new technology subsystem are connected through a data bus to achieve high-speed data transmission and sharing.
[0008] Preferably, the steam supply subsystem determines the steam supply amount according to the formula Q=kP, wherein Q represents the steam supply amount, P represents the steam pressure, and k represents the supply coefficient.
[0009] Preferably, the steam flow regulation subsystem adopts PID algorithm for precise flow regulation, and the formula is u(t)=Kp[e(t)+1 / Ti∫e(t)dt+Td*de(t) / dt], where u(t) is the regulation output, Kp is the proportional coefficient, Ti is the integral time constant, Td is the differential time constant, and e(t) is the deviation.
[0010] Preferably, the pressure monitoring subsystem monitors the pressure value in real time, and calculates the force exerted by the pressure on the equipment according to the formula F=m*g / S, where F represents the force, m is the mass of the monitoring point, g is the acceleration of gravity, and S is the pressure area.
[0011] Preferably, the temperature monitoring subsystem obtains the temperature value through the thermal resistor temperature measurement formula Rt=R0[1+A(T-T0)], where Rt is the resistance value at temperature T, R0 is the resistance value at reference temperature T0, and A is the resistance temperature coefficient.
[0012] Preferably, the data acquisition and processing subsystem uses a Kalman filter algorithm to process the collected data, and the formula is X(k|k)=X(k|k-1)+Kg(k)[Z(k)-HX(k|k-1)].
[0013] Preferably, the artificial intelligence-based fault prediction subsystem uses a neural network algorithm to perform fault prediction, and the prediction model is y=f(w*x+b), where y is the prediction result, w is the weight matrix, x is the input feature vector, and b is the bias term.
[0014] Preferably, the intelligent adaptive regulation subsystem performs adaptive adjustment according to a fitness function F=f(x1, x2, ...xn), wherein x1, x2, ...xn are relevant parameters.
[0015] Preferably, the IoT connection and remote control subsystem ensures data transmission efficiency based on the communication protocol formula C=L / D, where C represents transmission efficiency, L represents data volume, and D represents transmission time.
[0016] Preferably, the deep learning optimization subsystem uses the loss function formula Loss=1 / 2*sum((y_pred-y_true)^2) to measure the optimization effect, where y_pred is the predicted value and y_true is the true value.
[0017] The present invention has the beneficial effects:
[0018] 1. Innovation: It covers the integration of multiple advanced technologies and subsystems, and demonstrates unique innovative concepts, such as the architecture design of the steam intelligent control system, the unique algorithms and formula applications of each subsystem, etc.
[0019] 2. Improve performance: Through the formula of the steam supply subsystem and the PID algorithm of the steam flow regulation subsystem, the precise control of steam supply and flow can be achieved, thereby improving the performance and working quality of the steam setting machine.
[0020] 3. Intelligence: The fault prediction subsystem based on artificial intelligence, intelligent adaptive adjustment subsystem, etc., enable the system to have the ability of intelligent monitoring, prediction and self-adjustment, and increase the intelligence level and reliability of the equipment.
[0021] 4. Efficient data processing: The Kalman filter algorithm of the data acquisition and processing subsystem helps to improve the accuracy and efficiency of data processing and ensure that the system operates based on reliable data.
[0022] 5. Wide applicability: The design and technology of this system can be applied to different types of steam setting machines and has a wide range of applications.
[0023] 6. Improve competitiveness: Unique technical solutions can enhance the competitiveness of related products in the market and bring competitive advantages to enterprises.
[0024] 7. Promote industry development: It can provide new technical ideas and development directions for the steam setting machine industry and promote technological progress of the entire industry.
[0025] 8. Commercial value: It helps to develop products with higher performance and added value, and create higher commercial value and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS
[0026] Figure 1 It is a schematic diagram of the system structure of the present invention. DETAILED DESCRIPTION
[0027] The technical solution of the present invention is further specifically described below through embodiments and in conjunction with the accompanying drawings.
[0028] Example: Figure 1 As shown, the above technical problem of the present invention is mainly solved by the following technical solutions: a steam intelligent control system of a steam setting machine, including a basic subsystem and a new technology subsystem;
[0029] Among them, the basic subsystems include steam supply subsystem, steam flow regulation subsystem, pressure monitoring subsystem, temperature monitoring subsystem, and data acquisition and processing subsystem. The steam supply subsystem provides stable and appropriate steam to ensure that the steam setting machine has sufficient steam source to perform the setting process and ensure the continuity and stability of production. The steam flow regulation subsystem accurately controls the flow of steam and can flexibly adjust the steam volume according to different process requirements to achieve accurate setting effect and improve product quality and consistency. The pressure monitoring subsystem monitors the steam pressure in real time, which helps to detect abnormal pressure in time and avoid adverse effects on equipment and products due to excessive or low pressure, ensuring the safe operation of the system. The temperature monitoring subsystem monitors the temperature of the relevant area so that the operator can accurately grasp the temperature condition and make corresponding adjustments according to temperature changes to ensure that the setting process is carried out at an appropriate temperature. The data acquisition and processing subsystem collects and processes the data of each subsystem to provide data support for the intelligent control and optimization of the system. Through the analysis and processing of large amounts of data, more efficient and accurate system operation and management can be achieved.
[0030] The new technology subsystems include an AI-based fault prediction subsystem, an intelligent adaptive adjustment subsystem, an IoT connection and remote control subsystem, a deep learning optimization subsystem, a quantum computing-assisted decision-making subsystem, and a micro-nano material application subsystem. The AI-based fault prediction subsystem uses AI algorithms to analyze system operation data and predict possible failures in advance, which can help achieve preventive maintenance, reduce unexpected downtime, and improve equipment reliability and availability. The intelligent adaptive adjustment subsystem automatically adjusts the system's operating parameters based on real-time data and preset rules, enabling the system to quickly adapt to different working scenarios and changes in conditions, optimize performance, and improve finalization quality and efficiency. The IoT connection and remote control subsystem enables the connection between equipment and the Internet. It supports remote control and monitoring, which is convenient for operators to manage and operate remotely, improves the convenience and flexibility of management, and is also conducive to centralized monitoring and data analysis. The deep learning optimization subsystem further optimizes and improves the system through deep learning algorithms, explores deeper data features and laws, and improves the intelligence level and performance of the system. The quantum computing-assisted decision-making subsystem uses the powerful computing power of quantum computing to assist in complex decision-making, can quickly process large amounts of data and complex calculations, and provide more efficient and accurate support for system decision-making. The micro-nano material application subsystem is combined with the relevant parts of the steam setting machine, and the characteristics of micro-nano materials are used to bring better performance, such as improving the adaptability of materials and enhancing certain functions.
[0031] The basic subsystem and the new technology subsystem are connected through the data bus to achieve high-speed data transmission and sharing.
[0032] The steam supply subsystem determines the steam supply according to the formula Q=kP, where Q represents the steam supply, P represents the steam pressure, and k is the supply coefficient. It clarifies the quantitative relationship between the steam supply and the steam pressure, and provides a method for accurately calculating the steam supply according to the pressure, which can achieve precise control of the steam supply. By adjusting the steam pressure, the corresponding steam supply can be accurately obtained according to the formula, ensuring the accuracy and stability of the supply, which helps to improve the steam utilization efficiency. The steam supply is reasonably determined according to actual needs to avoid excessive or insufficient supply, thereby achieving the purpose of energy saving and optimizing production, and ensuring the consistency and reliability of the production process. Establish a clear relationship between the steam supply and pressure to reduce the adverse effects of unstable steam supply on product quality and production process.
[0033] The steam flow regulation subsystem adopts PID algorithm to accurately regulate the flow, and the formula is u(t)=Kp[e(t)+1 / Ti∫e(t)dt+Td*de(t) / dt], where u(t) is the regulation output, Kp is the proportional coefficient, Ti is the integral time constant, Td is the differential time constant, and e(t) is the deviation. The calculation model of the PID algorithm is used to determine the regulation amount of the steam flow, and the appropriate output is calculated according to the real-time deviation and other information to achieve accurate adjustment of the flow and improve the precision and accuracy of the flow regulation. The PID algorithm can comprehensively consider multiple factors such as the current deviation, historical deviation accumulation, and deviation change trend, so that the flow adjustment is more in line with actual needs, achieve a more accurate control effect, and enhance the stability and reliability of the system. Through timely and accurate flow regulation, the operation of the steam setting machine is more stable, the occurrence of fluctuations and abnormal situations is reduced, and adaptive regulation is achieved. The parameters can be automatically adjusted according to different working conditions and needs to better adapt to the changes in various operating conditions, ensure that the system is always in a good operating state, and improve product quality. Precise flow control helps ensure a consistent and stable steam setting process, improving product quality and performance.
[0034] The pressure monitoring subsystem monitors the pressure value in real time, and calculates the force of pressure on the equipment according to the formula F=m*g / S, where F represents the force, m is the mass of the monitoring point, g is the acceleration of gravity, and S is the pressure area. The pressure value in the steam system is continuously monitored, and the pressure data is converted into a specific force on the equipment using the formula to ensure the safety of the equipment. By understanding the magnitude of the force generated by the pressure in real time, it is possible to promptly discover excessive force that may cause damage to the equipment, so as to take corresponding measures to avoid equipment damage or failure, and optimize equipment design and operation. It provides a basis for the structural design and improvement of the equipment, helps to reasonably arrange the strength and size of the pressure-bearing parts to better adapt to the actual pressure situation, ensure the long-term stable operation of the equipment, and assist in fault diagnosis. When the force is abnormal, it can help determine whether there is a pressure-related fault or abnormal situation, provide direction for troubleshooting and maintenance, and accurately control and adjust. According to the magnitude of the force, it can work in conjunction with other subsystems to more accurately control and adjust the steam supply, flow, etc. to achieve the best operating state and performance.
[0035] The temperature monitoring subsystem obtains the temperature value through the thermal resistor temperature measurement formula Rt=R0[1+A(T-T0)], where Rt is the resistance value at temperature T, R0 is the resistance value at reference temperature T0, and A is the resistance temperature coefficient. According to the relationship between the resistance value change of the thermal resistor and the temperature, the current temperature is accurately calculated by measuring the resistance value to achieve accurate temperature measurement. The specific formula can accurately convert the resistance value into the corresponding temperature value, provide reliable temperature data, and ensure the quality of the production process. Accurate temperature monitoring helps to ensure that the steam shaping process is carried out under appropriate temperature conditions, thereby ensuring that the quality and performance of the product meet the requirements and providing a basis for the intelligent control of the system. Accurate temperature information can be used by other subsystems (such as the intelligent adaptive adjustment subsystem, etc.) to make more reasonable temperature adjustment and control strategy formulation, which is helpful for fault diagnosis and early warning. When the temperature fluctuates abnormally or exceeds the reasonable range, it can be discovered and handled in time to prevent possible failures or adverse consequences.
[0036] The data acquisition and processing subsystem uses the Kalman filter algorithm to process the collected data. The formula is X(k|k)=X(k|k-1)+Kg(k)[Z(k)-HX(k|k-1)], and performs optimal estimation and filtering on the collected data to improve the accuracy and reliability of the data. It can effectively remove noise and interference, so that the processed data can better reflect the actual situation and realize real-time dynamic data correction. With the continuous input of new data, the estimated values are continuously updated and optimized to enhance the adaptability and stability of the system. Even in the presence of measurement errors and uncertainties, it can provide more accurate processing results, which helps the entire system to operate stably and provide better data support for other subsystems. The accurate data processed by the Kalman filter can better serve other subsystems such as fault prediction and adaptive adjustment, and improve the performance and decision-making accuracy of the entire intelligent control system.
[0037] The fault prediction subsystem based on artificial intelligence uses a neural network algorithm to predict faults. The prediction model is y=f(w*x+b), where y is the prediction result, w is the weight matrix, x is the input feature vector, and b is the bias term. The fault analysis and prediction based on the input feature data can detect potential fault hazards in advance. By analyzing and learning various operating data, an early warning is given before the fault actually occurs, thereby improving the accuracy and reliability of fault prediction. The neural network algorithm can automatically learn the complex patterns and relationships in the data, so as to make fault judgments more accurately and adapt to different working conditions and complex environments. The weights and biases can be continuously adjusted according to the actual situation to better adapt to the fault prediction needs of the steam setting machine under different conditions, which is helpful to formulate a reasonable maintenance plan. Knowing the possible faults in advance facilitates the reasonable arrangement of maintenance time and resources, reduces downtime and losses caused by faults, and promotes intelligent operation and maintenance. Work in collaboration with other subsystems to achieve more intelligent and efficient equipment operation and management.
[0038] The intelligent adaptive adjustment subsystem performs adaptive adjustment according to the fitness function F=f(x1,x2,...xn), where x1,x2,...xn are relevant parameters. The fitness function is used as an evaluation standard to determine the optimal adjustment direction and degree of the system, and realize automatic optimization and adjustment of the system. According to different parameter combinations, the operating state that best suits the current working conditions is found to improve the performance and efficiency of the system and enhance the flexibility and adaptability of the system. It can be dynamically adjusted according to changes in various factors to maintain the good operation of the system and improve resource utilization efficiency. Through precise adaptive adjustment, resources such as steam and energy can be more reasonably allocated and utilized to ensure the stability and reliability of the system. Continuously adapting to changes in the environment and operating conditions, reducing instability caused by external factors, and helping to achieve personalized settings and customization. Specific operating effects can be achieved by adjusting relevant parameters according to specific needs and preferences.
[0039] The IoT connection and remote control subsystem ensures data transmission efficiency based on the communication protocol formula C=L / D, where C represents transmission efficiency, L represents data volume, and D represents transmission time, which is used to measure and optimize the efficiency of data transmission, and clearly quantifies the data transmission efficiency, so that there is an intuitive evaluation index for transmission performance. By monitoring the changes in data volume and transmission time, problems that may affect transmission efficiency can be discovered and solved in a timely manner, which helps to optimize the communication settings and resource allocation of the system. According to the requirements of transmission efficiency, the data volume or transmission time can be reasonably adjusted to achieve the best transmission effect and ensure the real-time and accuracy of remote control. Ensure that data can be transmitted in a timely and efficient manner during remote control, so that remote operations can be performed accurately and quickly, and the coordination and responsiveness of the entire intelligent control system can be improved. Make data exchange between different parts smoother, enhance the system's response speed to remote commands, and provide a basis for system expansion and upgrading. When it is necessary to increase the amount of data transmitted or increase the response requirements, the communication protocol and related settings can be evaluated and improved based on this formula.
[0040] The deep learning optimization subsystem uses the loss function formula Loss = 1 / 2*sum((y_pred-y_true)^2) to measure the optimization effect, where y_pred is the predicted value and y_true is the true value, which quantifies the difference between the model prediction result and the true result, and provides a clear indicator to evaluate the performance and optimization degree of the model. By calculating the size of the loss value, the accuracy and deviation of the model can be intuitively understood, guiding the training and improvement of the model. According to the value of the loss function, the parameters of the model are adjusted to reduce the gap between the predicted value and the true value, thereby improving the accuracy of the model and helping to determine whether the model has achieved the desired optimization effect. When the loss value gradually decreases and tends to be stable, it can be judged that the optimization work of the model has achieved good results, which is convenient for comparing the advantages and disadvantages of different models or different training methods. By observing the performance of the loss function in different situations, a more suitable model structure or training strategy can be selected to provide a basis for further optimization and adjustment. Based on the analysis of the loss function, targeted algorithm improvement, data enhancement and other operations can be performed to continuously improve the performance of the deep learning optimization subsystem.
[0041] It covers the integration of multiple advanced technologies and subsystems, and demonstrates unique innovative concepts, such as the architecture design of the steam intelligent control system, the unique algorithms and formula applications of each subsystem, etc. Through the formula of the steam supply subsystem and the PID algorithm of the steam flow regulation subsystem, etc., it can achieve precise control of steam supply and flow, thereby improving the performance and working quality of the steam setting machine. The fault prediction subsystem based on artificial intelligence and the intelligent adaptive adjustment subsystem enable the system to have the ability of intelligent monitoring, prediction and self-adjustment, increase the intelligence level and reliability of the equipment, and the Kalman filter algorithm of the data acquisition and processing subsystem helps to improve the accuracy and efficiency of data processing and ensure that the system runs based on reliable data. The design and technology of this system can be applied to different types of steam setting machines and has a wide range of applications. The unique technical solution can enhance the competitiveness of related products in the market and bring competitive advantages to enterprises. It can provide new technical ideas and development directions for the steam setting machine industry, promote technological progress in the entire industry, and help develop products with higher performance and added value, creating higher commercial value and economic benefits.
[0042] Finally, it should be pointed out that the above embodiments are only representative examples of the present invention. Obviously, the present invention is not limited to the above embodiments, and there are many variations. Any simple modification, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention should be considered to belong to the protection scope of the present invention.
Claims
1. A steam intelligent control system for a steam setting machine, characterized in that: The steam intelligent control system of the steam setting machine includes a basic subsystem and a new technology subsystem; Among them, the basic subsystem includes steam supply subsystem, steam flow regulation subsystem, pressure monitoring subsystem, temperature monitoring subsystem, and data acquisition and processing subsystem; The new technology subsystems include an artificial intelligence-based fault prediction subsystem, an intelligent adaptive adjustment subsystem, an Internet of Things connection and remote control subsystem, a deep learning optimization subsystem, a quantum computing-assisted decision-making subsystem, and a micro-nano material application subsystem; The basic subsystem and the new technology subsystem are connected through the data bus to achieve high-speed data transmission and sharing.
2. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The steam supply subsystem determines the steam supply amount according to the formula Q=kP, where Q represents the steam supply amount, P represents the steam pressure, and k is the supply coefficient.
3. The steam intelligent control system of a steam setting machine according to claim 1, characterized in that: The steam flow regulation subsystem adopts PID algorithm to perform precise flow regulation, and the formula is u(t)=Kp[e(t)+1 / Ti∫e(t)dt+Td*de(t) / dt], where u(t) is the regulation output, Kp is the proportional coefficient, Ti is the integral time constant, Td is the differential time constant, and e(t) is the deviation.
4. The steam intelligent control system of a steam setting machine according to claim 1, characterized in that: The pressure monitoring subsystem monitors the pressure value in real time and calculates the force exerted by the pressure on the equipment according to the formula F=m*g / S, where F represents the force, m is the mass of the monitoring point, g is the acceleration of gravity, and S is the pressure area.
5. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The temperature monitoring subsystem obtains the temperature value through the thermal resistor temperature measurement formula Rt=R0[1+A(T-T0)], where Rt is the resistance value at temperature T, R0 is the resistance value at reference temperature T0, and A is the resistance temperature coefficient.
6. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The data acquisition and processing subsystem uses a Kalman filter algorithm to process the collected data, and the formula is X(k|k)=X(k|k-1)+Kg(k)[Z(k)-HX(k|k-1)].
7. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The artificial intelligence-based fault prediction subsystem uses a neural network algorithm to perform fault prediction, and the prediction model is y=f(w*x+b), where y is the prediction result, w is the weight matrix, x is the input feature vector, and b is the bias term.
8. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The intelligent adaptive adjustment subsystem performs adaptive adjustment according to the fitness function F=f(x1, x2, ... xn), wherein x1, x2, ... xn are relevant parameters.
9. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The IoT connection and remote control subsystem ensures data transmission efficiency based on the communication protocol formula C=L / D, where C represents transmission efficiency, L represents data volume, and D represents transmission time.
10. The intelligent steam control system for a steam setting machine according to claim 1, characterized in that: The deep learning optimization subsystem uses the loss function formula Loss=1 / 2*sum((y_pred-y_true)^2) to measure the optimization effect, where y_pred is the predicted value and y_true is the true value.