Intelligent control system of reduction furnace
By introducing an intelligent control system into the reduction furnace control system and using big data analysis and artificial intelligence algorithms for precise control, the problems of large temperature fluctuations, uncontrollable reaction rates and high energy consumption in the existing technology have been solved, and the output and product quality have been improved and operation and maintenance costs have been reduced.
Patent Information
- Application Number
- CN202411482039.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-23
- Publication Date
- 2025-02-25
AI Technical Summary
The existing reduction furnace control system has problems such as large temperature fluctuations, uncontrollable reaction rate, high energy consumption and unstable product quality, resulting in low production efficiency and high operation and maintenance costs.
An intelligent control system for reducing furnaces is designed, including simulation parameter module, data acquisition module, data processing module and intelligent control execution module. Through big data analysis and artificial intelligence algorithms, predictive models and optimization algorithms are constructed to achieve precise control of the operating status of the reducing furnaces.
Through precise control, the operation time of the reduction furnace is shortened, the output and product quality are improved, the manual intervention and operation and maintenance costs are reduced, and the system automation level is improved.
Smart Images
Figure CN119511782A_ABST
Abstract
Description
Technical Field
[0001] The invention relates to the field of reduction furnace control, and in particular to an intelligent control system for a reduction furnace. Background Art
[0002] The intelligent control system of the reduction furnace is a system for controlling the processing of polysilicon. In the production process of polysilicon, the modified Siemens method is one of the more mature technologies for producing polysilicon. With the development of the polysilicon industry, continuous process optimization, cost reduction and efficiency improvement have gradually become a way to generate competitive advantages. With the continuous development of science and technology, people have higher and higher requirements for the manufacturing process of the intelligent control system of the reduction furnace.
[0003] The existing reduction furnace control system has certain drawbacks when in use. Traditional reduction furnaces are mostly adjusted by manual experience, which is not conducive to the fine adjustment of the reduction furnace. There are problems such as large temperature fluctuations, uncontrollable reaction rate, high energy consumption, and unstable product quality. Intelligent control can improve the stability of the furnace environment, the quality of products, and safe production, effectively ensure the smooth progress of the reaction process in the furnace, and reduce product quality abnormalities. To this end, we propose a reduction furnace intelligent control system. Summary of the invention
[0004] Technical problems solved: In view of the shortcomings of the prior art, the present invention provides an intelligent control system for a reduction furnace, which can shorten the operation time of the reduction furnace and increase the output through precise control; stably control the process parameters, reduce fluctuations, and increase the proportion of dense materials in the product; reduce manual intervention, reduce labor costs, and improve the level of system automation, which can effectively solve the problems in the background technology.
[0005] Technical solution: To achieve the above-mentioned purpose, the technical solution adopted by the present invention is: a reduction furnace intelligent control system, including a simulation parameter module, a data acquisition module, a data processing module and an intelligent control execution module, the simulation parameter module is connected to the data acquisition module, the data acquisition module is connected to the data processing module, the data processing module is connected to the intelligent control execution module, the simulation parameter module includes volt-ampere curve parameters, gas field temperature parameters in the reduction furnace and theoretical power parameters, the data acquisition module includes hydrogen data, TCS real-time data, power curve data, current data, voltage data, exhaust gas temperature data and furnace water temperature data, the data processing module includes a data receiving module, a data calculation module, a central control center, a data summary module, a processing mechanism module and a deep analysis module, the intelligent control execution module includes a data analysis module, an artificial intelligence algorithm, a prediction model optimization, an optimal control strategy, an instruction receiving module and an operation control module.
[0006] As a preferred technical solution of the present application, it also includes a control device, which is connected to a control panel and a data analysis module, an exhaust gas temperature detection module, a logic processing module and an execution module connected to the control panel.
[0007] As a preferred technical solution of the present application, the data analysis module, the exhaust gas temperature detection module, the logic processing module and the execution module are all connected to the data acquisition and processing module, the data acquisition and processing module is connected to the data communication module, the data communication module is connected to the central processing module, and the central processing module is connected to the display module and the intelligent control module.
[0008] As a preferred technical solution of the present application, the simulation parameter module simulates the volt-ampere curve, the gas field temperature in the reduction furnace, and the theoretical power parameters through calculation.
[0009] As a preferred technical solution of the present application, the data acquisition module collects the reduction furnace operating parameters in real time, including hydrogen and TCS real-time data, and also collects process data, including current, voltage, power curve, exhaust gas temperature and furnace water temperature.
[0010] As a preferred technical solution of the present application, the data processing module is responsible for receiving and processing data from the data acquisition module, performing preliminary processing using computing technology, integrating the monitoring data into the central control center, and establishing a data aggregation and processing mechanism for in-depth analysis.
[0011] As a preferred technical solution of the present application, the intelligent control execution module constructs a prediction model and optimization algorithm based on big data analysis and artificial intelligence algorithm, predicts the operating status of the reduction furnace according to real-time data and historical data, and generates an optimal control strategy, receives instructions from the intelligent control layer, and achieves precise control of the operating status of the reduction furnace by adjusting the current, hydrogen, and TCS flow control systems of the reduction furnace.
[0012] As a preferred technical solution of the present application, the control system composed of the simulation parameter module, the data acquisition module, the data processing module and the intelligent control execution module establishes the key parameters of the reduction furnace temperature, power and reaction rate, imports the APC control calculation module, adjusts the current size, hydrogen and trichlorosilane feed amount through PID, and finally forms a logic module on the DCS interface. According to the reaction conditions in the reduction furnace, the APC deposition rate prediction module is adjusted, the APC power calculation module is adjusted, and the control strategy is dynamically adjusted according to the prediction results and real-time data to quickly adjust the operation status of the reduction furnace.
[0013] Beneficial effects: Compared with the prior art, the present invention provides an intelligent control system for a reduction furnace, which has the following beneficial effects: the intelligent control system for a reduction furnace improves production efficiency: through precise control, the operation time of the reduction furnace is shortened and the output is increased; Improve product quality: stabilize and control process parameters, reduce fluctuations, and increase the proportion of dense materials in products; Reduce operation and maintenance costs: reduce manual intervention, reduce labor costs, and improve the level of system automation. The entire reduction furnace intelligent control system has a simple structure, is easy to operate, and has better results than traditional methods. BRIEF DESCRIPTION OF THE DRAWINGS
[0014] Figure 1 The figure is a schematic diagram of the overall structure of an intelligent control system for a reduction furnace according to the present invention.
[0015] Figure 2 The present invention is a schematic diagram of the structure of a control device in an intelligent control system for a reduction furnace.
[0016] Figure 3 The present invention is a schematic diagram of the structure of a control module in an intelligent control system of a reduction furnace.
[0017] Figure 4 The present invention is a schematic flow chart of a control method in an intelligent control system for a reduction furnace. DETAILED DESCRIPTION
[0018] The technical scheme of the present invention will be clearly and completely described below in conjunction with the accompanying drawings and specific embodiments, but it will be understood by those skilled in the art that the following described embodiments are part of embodiments of the present invention, rather than all embodiments, and are only used to illustrate the present invention, and should not be considered as limiting the scope of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without making creative work are within the scope of protection of the present invention. If specific conditions are not specified in the embodiments, they are carried out according to normal conditions or conditions recommended by the manufacturer. If the manufacturer is not specified in the reagents or instruments used, they are all conventional products that can be purchased commercially.
[0019] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.
[0020] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.
[0021] like Figure 1-4 As shown, a reduction furnace intelligent control system includes a simulation parameter module, a data acquisition module, a data processing module and an intelligent control execution module. The simulation parameter module is connected to the data acquisition module, the data acquisition module is connected to the data processing module, and the data processing module is connected to the intelligent control execution module. The simulation parameter module includes volt-ampere curve parameters, gas field temperature parameters in the reduction furnace and theoretical power parameters. The data acquisition module includes hydrogen data, TCS real-time data, power curve data, current data, voltage data, tail gas temperature data and furnace water temperature data. The data processing module includes a data receiving module, a data calculation module, a central control center, a data aggregation module, a processing mechanism module and a deep analysis module. The intelligent control execution module includes a data analysis module, an artificial intelligence algorithm, a prediction model optimization, an optimal control strategy, an instruction receiving module and an operation control module. Through precise control, the operation time of the reduction furnace is shortened and the output is increased; the process parameters are stably controlled, fluctuations are reduced, and the proportion of dense materials in the product is increased; manual intervention is reduced, labor costs are reduced, and the system automation level is improved.
[0022] Furthermore, it also includes a control device, which is connected to a control panel and a data analysis module, an exhaust gas temperature detection module, a logic processing module and an execution module connected to the control panel.
[0023] Furthermore, the data analysis module, the exhaust gas temperature detection module, the logic processing module and the execution module are all connected to the data acquisition processing module, the data acquisition processing module is connected to the data communication module, the data communication module is connected to the central processing module, and the central processing module is connected to the display module and the intelligent control module.
[0024] Furthermore, the simulation parameter module simulates the volt-ampere curve, the gas field temperature in the reduction furnace, and the theoretical power parameters through calculation.
[0025] Furthermore, the data acquisition module collects the reduction furnace operating parameters in real time, including hydrogen and TCS real-time data, and also collects process data, including current, voltage, power curve, tail gas temperature and furnace water temperature.
[0026] Furthermore, the data processing module is responsible for receiving and processing data from the data acquisition module, using computing technology to perform preliminary processing, and integrating the monitoring data into the central control center to establish a data aggregation and processing mechanism for in-depth analysis.
[0027] Furthermore, the intelligent control execution module builds prediction models and optimization algorithms based on big data analysis and artificial intelligence algorithms, predicts the operating status of the reduction furnace according to real-time data and historical data, and generates the optimal control strategy. It receives instructions from the intelligent control layer and adjusts the current, hydrogen, and TCS flow control systems of the reduction furnace to achieve precise control of the operating status of the reduction furnace.
[0028] Furthermore, the control system composed of the simulation parameter module, the data acquisition module, the data processing module and the intelligent control execution module establishes the key parameters of the reduction furnace temperature, power and reaction rate, imports the APC control calculation module, adjusts the current, hydrogen and trichlorosilane feed amount through PID, and finally forms a logic module on the DCS interface. According to the reaction conditions in the reduction furnace, the APC deposition rate prediction module is adjusted, and the APC power calculation module is adjusted. According to the prediction results and real-time data, the control strategy is dynamically adjusted to quickly adjust the operation status of the reduction furnace.
[0029] Working principle: The present invention is mainly composed of a simulation parameter layer, a data acquisition layer, a data processing layer, and an intelligent control execution layer.
[0030] Simulation parameter layer: simulate the volt-ampere curve, gas field temperature in the reduction furnace, theoretical power and other parameters through calculation; Data collection layer: real-time collection of reduction furnace operating parameters (hydrogen, TCS real-time data) and process data (current, voltage, power curve, tail gas temperature, furnace water temperature, etc.); Data processing layer: responsible for receiving and processing data from the data collection layer, using computing technology for preliminary processing, integrating monitoring data into the central control center, and establishing a data aggregation and processing mechanism for in-depth analysis; Intelligent control execution layer: Build prediction models and optimization algorithms based on big data analysis and artificial intelligence algorithms, predict the operating status of the reduction furnace according to real-time data and historical data, and generate the optimal control strategy. It receives instructions from the intelligent control layer and achieves precise control of the operating status of the reduction furnace by adjusting the current, hydrogen, and TCS flow control systems of the reduction furnace.
[0031] The control system includes a control device that cooperates with the reduction furnace, and the control device includes a control panel and a voltage detection module electrically connected to the control panel, an exhaust gas temperature detection module, a logic processing module and an execution module; the control method includes dividing the reduction furnace automatic control process into several stages according to the reaction time, and the control strategy of each stage can be set or adjusted separately; and implementing voltage automatic control, exhaust gas temperature automatic control and exhaust gas temperature maximum limit control for each stage. The present invention can improve the automatic control rate of the reduction furnace, ensure the stability of the production and operation of the polysilicon reduction furnace, and the replicability and reproducibility of the index data.
[0032] Usage: Establish key parameters such as reduction furnace temperature, power, reaction rate, etc., import APC control calculation module, adjust current size, hydrogen and trichlorosilane feed amount through PID, and finally form a logic module on the DCS interface. According to the reaction conditions in the reduction furnace, adjust the APC deposition rate prediction module, adjust the APC power calculation module, and dynamically adjust the control strategy according to the prediction results and real-time data to achieve rapid adjustment of the reduction furnace operation status.
[0033] It should be noted that, in this article, relational terms such as first and second (number one, number two), etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.
[0034] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.
Claims
1. A reduction furnace intelligent control system, comprising a simulation parameter module, a data acquisition module, a data processing module and an intelligent control execution module, characterized in that: The simulation parameter module is connected to the data acquisition module, the data acquisition module is connected to the data processing module, the data processing module is connected to the intelligent control execution module, the simulation parameter module includes volt-ampere curve parameters, gas field temperature parameters in the reduction furnace and theoretical power parameters, the data acquisition module includes hydrogen data, TCS real-time data, power curve data, current data, voltage data, tail gas temperature data and furnace water temperature data, the data processing module includes a data receiving module, a data calculation module, a central control center, a data summary module, a processing mechanism module and a deep analysis module, and the intelligent control execution module includes a data analysis module, an artificial intelligence algorithm, a prediction model optimization, an optimal control strategy, an instruction receiving module and an operation control module.
2. The reduction furnace intelligent control system according to claim 1, characterized in that: It also includes a control device, which is connected to a control panel and a data analysis module, an exhaust gas temperature detection module, a logic processing module and an execution module connected to the control panel.
3. The reduction furnace intelligent control system according to claim 2 is characterized in that: The data analysis module, exhaust gas temperature detection module, logic processing module and execution module are all connected to the data acquisition processing module, the data acquisition processing module is connected to the data communication module, the data communication module is connected to the central processing module, and the central processing module is connected to the display module and the intelligent control module.
4. The reduction furnace intelligent control system according to claim 1, characterized in that: The simulation parameter module simulates the volt-ampere curve, the gas field temperature in the reduction furnace, and the theoretical power parameters through calculation.
5. The reduction furnace intelligent control system according to claim 1 is characterized in that: The data acquisition module collects the reduction furnace operating parameters in real time, including hydrogen and TCS real-time data, and also collects process data, including current, voltage, power curve, tail gas temperature and furnace water temperature.
6. The reduction furnace intelligent control system according to claim 1, characterized in that: The data processing module is responsible for receiving and processing data from the data acquisition module, using computing technology for preliminary processing, integrating the monitoring data into the central control center, and establishing a data aggregation and processing mechanism for in-depth analysis.
7. The reduction furnace intelligent control system according to claim 1 is characterized in that: The intelligent control execution module builds a prediction model and optimization algorithm based on big data analysis and artificial intelligence algorithms, predicts the operating status of the reduction furnace according to real-time data and historical data, and generates an optimal control strategy. It receives instructions from the intelligent control layer and adjusts the current, hydrogen, and TCS flow control systems of the reduction furnace to achieve precise control of the operating status of the reduction furnace.
8. The reduction furnace intelligent control system according to claim 1 is characterized in that: The control system composed of the simulation parameter module, the data acquisition module, the data processing module and the intelligent control execution module establishes the key parameters of the reduction furnace temperature, power and reaction rate, imports the APC control calculation module, adjusts the current size, hydrogen and trichlorosilane feed amount through PID, and finally forms a logic module on the DCS interface. According to the reaction conditions in the reduction furnace, the APC deposition rate prediction module is adjusted, the APC power calculation module is adjusted, and the control strategy is dynamically adjusted according to the prediction results and real-time data to quickly adjust the operation status of the reduction furnace.