DCS embedded reduction furnace control method and related device

Abstract

The invention discloses a DCS (Distributed Control System) embedded reduction furnace control method, a DCS embedded reduction furnace control device, DCS embedded reduction furnace control equipment and a computer readable storage medium. The method comprises the following steps: acquiring an input reduction furnace control material table by a DCS system through an operation interface; executing detection before furnace starting based on a preset detection execution table; when the safety detection before furnace starting is completed, a purging program is executed; when the execution of the purging program is completed, acquiring a process parameter set value from the reduction furnace control material table; executing furnace starting operation on the basis of the process parameter set value; when the furnace starting operation is completed, deposition operation is executed based on the parameter curve of each stage in the reduction furnace control material table; and when the furnace shutdown conditions in the reduction furnace control charge list are met, furnace shutdown operation is executed. The integration level and the operation efficiency of the control process of the polycrystalline silicon reduction furnace are improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of industrial control, and more particularly relates to a DCS embedded reduction furnace control method, a DCS embedded reduction furnace control device, a DCS embedded reduction furnace control equipment and a computer readable storage medium. BACKGROUND

[0002] As a core basic material for the photovoltaic and semiconductor industries, the production of polycrystalline silicon, the control level of the reduction furnace as the core equipment, directly affects the product quality, energy consumption and production cost.

[0003] In the related art, there are two schemes for polycrystalline silicon reduction furnace control: one is that DCS and electrical control system run independently, DCS controls materials and electrical system controls power. This scheme only guarantees basic operation, lacks optimization and intelligent abnormal handling capability, resulting in high operation intensity, more manual intervention and difficult performance improvement. The second is to externally hang a third-party optimization system based on independent systems, which can automatically import the material table and partially optimize, but has significant defects: the "three-system" architecture is complex, communication is unstable and prone to failure; the core optimization technology is subject to third parties and cannot be independently changed and upgraded; there is a lack of closed-loop continuous optimization means based on data. The existing technology generally has the problems of complex operation and reliability risk caused by system fragmentation, dependence on external and uncontrollable core optimization capability, and inability to realize process parameter closed-loop self-optimization.

[0004] Therefore, how to improve the integration and operation efficiency of the control process of the polycrystalline silicon reduction furnace is an important issue for those skilled in the art. SUMMARY

[0005] The purpose of the present application is to provide a DCS embedded reduction furnace control method, a DCS embedded reduction furnace control device, a DCS embedded reduction furnace control equipment and a computer readable storage medium to improve the integration and operation efficiency of the control process of the polycrystalline silicon reduction furnace.

[0006] In view of the above defects or improvement needs of the prior art, the present application provides a DCS embedded reduction furnace control method, comprising: The DCS system obtains the input reduction furnace control material table through an operation interface; Perform pre-start detection based on a preset detection execution table; When the pre-start safety detection is completed, perform a purging program; When the purging program is executed, obtain the process parameter set value from the reduction furnace control material table; Perform start-up operation based on the process parameter set value; When the start-up operation is completed, perform deposition operation based on the parameter curve of each stage in the reduction furnace control material table; When reaching the shutdown condition in the reduction furnace control table, a shutdown operation is performed.

[0007] Optionally, the method further comprises: When the shutdown operation is completed, the DCS system generates batch production data; wherein the batch production data comprises instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate. The batch production data is analyzed based on a big data anomaly analysis model to obtain an optimized reduction furnace control table.

[0008] Optionally, pre-startup detection is performed based on a preset detection execution table, comprising: The DCS system performs pre-startup safety inspection; wherein the pre-startup safety inspection comprises confirming that the cooling water system is normal, the tail gas system is ready, the protective gas is qualified, all valves are in a safe position, and there is no major alarm. Silicon core resistance detection is performed through an embedded power control module.

[0009] Optionally, the startup operation is performed based on the process parameter set value, comprising: The silicon core is heated to a preset temperature based on the process parameter set value. Gas flow, mixing ratio, and inlet pressure are controlled based on the process parameter set value.

[0010] Optionally, the method further comprises: Real-time key parameters are obtained for the deposition operation; wherein the key parameters comprise power fluctuation, temperature deviation, deposition rate change, pressure anomaly, and tail gas anomaly. When the key parameters trigger a first preset condition, a slight anomaly message is sent, and a preset fine-tuning strategy is executed. When the key parameters trigger a second preset condition, a serious anomaly message is sent, a preset safety interlock operation is executed, an audible and visual alarm is issued, and the failure cause and the executed protection action are displayed on the operation interface.

[0011] Optionally, the deposition operation is performed based on the parameter curves of each stage in the reduction furnace control table, comprising: A feed curve, a temperature curve, and a power curve are obtained from the reduction furnace control table. The deposition operation is performed based on the feed curve, the temperature curve, the power curve, and running stage data.

[0012] The application also provides a DCS embedded reduction furnace control device, comprising: A table acquisition module is configured to obtain an input reduction furnace control table through an operation interface. The pre-start-up detection module is configured to perform pre-start-up detection based on a preset detection execution table; The purging execution module is configured to perform a purging program when the pre-start-up safety detection is completed. The parameter acquisition module is configured to acquire process parameter set values from the reduction furnace control recipe when the purging program is completed. The start-up operation module is configured to perform start-up operation based on the process parameter set values. The deposition operation module is configured to perform deposition operation based on parameter curves of each stage in the reduction furnace control recipe when the start-up operation is completed. The shutdown operation module is configured to perform shutdown operation when a shutdown condition in the reduction furnace control recipe is reached.

[0013] Optionally, the method further comprises: The abnormality analysis module is configured to generate batch production data when the shutdown operation is completed, wherein the batch production data comprises instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate; and the batch production data is analyzed based on a big data abnormality analysis model to obtain an optimized reduction furnace control recipe.

[0014] The application also provides a DCS embedded reduction furnace control device, comprising: A memory is configured to store a computer program. A processor is configured to execute the computer program to implement the steps of the DCS embedded reduction furnace control method.

[0015] The application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the DCS embedded reduction furnace control method.

[0016] The DCS embedded reduction furnace control method provided by the application comprises the following steps: a DCS system acquires an input reduction furnace control recipe through an operation interface; pre-start-up detection is performed based on a preset detection execution table; a purging program is executed when the pre-start-up safety detection is completed; process parameter set values are acquired from the reduction furnace control recipe when the purging program is completed; start-up operation is performed based on the process parameter set values; deposition operation is performed based on parameter curves of each stage in the reduction furnace control recipe when the start-up operation is completed; and shutdown operation is performed when a shutdown condition in the reduction furnace control recipe is reached.

[0017] The DCS embedded reduction furnace control method has the following beneficial effects: The DCS system obtains the reduction furnace control table, and performs pre-starting detection, purging, starting, deposition and stopping and the like according to the control table, realizes full-process automatic control, improves operation efficiency, guarantees accurate execution of parameters in each stage, reduces manual intervention, and improves the operation stability and production safety of the reduction furnace. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description only relate to the embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of the provided drawings.

[0019] Figure 1 A flow chart of a DCS embedded reduction furnace control method provided by an embodiment of the present application; Figure 2 A structural schematic diagram of a DCS embedded reduction furnace control device provided by an embodiment of the present application; Figure 3 A structural schematic diagram of a DCS embedded reduction furnace control device provided by an embodiment of the present application; DETAILED DESCRIPTION

[0020] The purpose of the present application is to provide a DCS embedded reduction furnace control method, a DCS embedded reduction furnace control device, a DCS embedded reduction furnace control equipment and a computer readable storage medium, so as to improve the integration and operation efficiency of the control process of the polysilicon reduction furnace.

[0021] In order to make the purpose, technical solutions and advantages of the present application more clear, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application. In addition, the technical features involved in each embodiment of the present application described below can be combined with each other as long as there is no conflict.

[0022] In the following, an embodiment of the DCS embedded reduction furnace control method provided by the present application will be described.

[0023] Reference is made to Figure 1 , Figure 1 A flow chart of a DCS embedded reduction furnace control method provided by an embodiment of the present application.

[0024] In the embodiment, the method can include: S101, the DCS system obtains the input reduction furnace control table through the operation interface; In this step, the DCS (Distributed Control System) system obtains the input reduction furnace control table through the operation interface. The reduction furnace control table is a core data carrier containing the entire production process parameters (which can include: temperature, gas flow, power curve, etc.), and is the basis for all subsequent operations. Obtaining the table can make the DCS system clear the production target parameters and ensure that each stage of operation is performed according to the preset process logic.

[0025] Further, a unified operation interface is developed on the DCS operator station, which supports the operator to manually input table parameters through the interface, or import preset tables from the DCS historical database or external file system. After the table data is parsed, it is stored in the DCS controller memory for subsequent steps to call.

[0026] As can be seen, this step realizes standardized management of process parameters through a unified interface to avoid manual input errors, and the automatic table import function improves operational efficiency and lays a data foundation for full-process automatic control.

[0027] S102, performing pre-start detection based on a preset detection execution table; Based on S101, this step aims to perform pre-start detection based on a preset detection execution table. The pre-start detection is a necessary step to ensure the safe start of the reduction furnace. By checking the status of key systems (such as cooling water, tail gas treatment) and equipment (valves, silicon core resistance), potential faults and hazards are eliminated to prevent damage to equipment or production accidents caused by starting with faults.

[0028] Optionally, this step can include: Step 1, the DCS system performs pre-start safety checks; wherein the pre-start safety checks include: confirming that the cooling water system is normal, the tail gas system is ready, the protection gas is qualified, all valves are in a safe position, and there are no major alarms; Step 2, performing silicon core resistance detection through an embedded power control module.

[0029] Further, the DCS system performs pre-start safety checks: through the DCS I / O module, real-time acquisition of cooling water system pressure, flow sensor data is performed to confirm that the system is normal; the tail gas system fan operating state and pipeline pressure are detected to ensure readiness; the purity of the protection gas (such as argon) is verified through a gas analyzer to ensure that it is qualified; the opening and closing feedback signals of all valves are scanned to confirm that they are in a safe position; the DCS alarm database is queried to confirm that there are no major alarms.

[0030] Further, the embedded power control module performs silicon core resistance detection: the DCS sends instructions to the power module, the module applies a low voltage to the silicon core, measures the loop current, calculates the silicon core resistance value through Ohm's law, and judges whether the silicon core has abnormality such as broken rod or poor contact.

[0031] It can be seen that through systematic pre-starting detection, this step can find and eliminate equipment hazards in advance, minimize the risk of failure in the starting stage, and ensure the safety and stability of the production process.

[0032] S103, when the pre-starting safety detection is completed, a purging program is executed; On the basis of S102, this step aims to execute a purging program when the pre-starting safety detection is completed. The purging program purges the inside of the reduction furnace with inert gas (such as nitrogen) to remove residual air, impurity gas or dust in the furnace, so as to avoid adverse reactions of these substances with reaction gas after starting, affecting the deposition quality or causing safety accidents.

[0033] Further, the DCS system controls the opening of related valves according to the preset purging process, and introduces a certain flow of nitrogen into the furnace. The purging time and flow parameters are set by the material table. During the purging process, the DCS monitors the pressure and gas flow in the furnace in real time to ensure the purging effect. After the purging is completed, the gas analyzer is used to confirm that the oxygen content and other indicators in the furnace meet the standards.

[0034] It can be seen that through the purging program, the environment in the furnace can be effectively purified to provide a pure reaction space for the subsequent deposition process, improve the quality and purity of polysilicon deposition, and reduce product defects caused by the introduction of impurities.

[0035] S104, when the purging program is executed, obtaining the process parameter set value from the reduction furnace control material table; On the basis of S103, this step aims to obtain the process parameter set value from the reduction furnace control material table when the purging program is executed. The process parameter set value is the specific control basis for starting and deposition operations, including: silicon core heating temperature, gas flow, mixing ratio and other key parameters. Obtaining these parameters after purging can ensure that the starting operation is based on the latest process requirements, and avoid control deviation caused by parameter lag.

[0036] Further, the DCS controller reads the imported reduction furnace control material table from the memory, parses the process parameters in the starting stage (such as initial heating temperature, initial gas flow, etc.), and sends these parameters to the corresponding control module (such as the power control module, the material control module) as the set value for the execution of control actions by each module.

[0037] It can be seen that, by timely acquiring the process parameter setting value, the accuracy and consistency of the start-up operation are ensured, the reduction furnace can be started smoothly according to the preset process curve, and conditions are created for stable operation of the subsequent deposition process.

[0038] S105, performing start-up operation based on the process parameter setting value; On the basis of S104, the step aims to perform start-up operation based on the process parameter setting value. The core of the start-up operation is to heat the silicon core to the required reaction temperature and accurately control the flow rate, mixing ratio and inlet pressure of the reaction gas, so that the reduction furnace reaches the appropriate reaction conditions and prepares for the deposition of polysilicon. Through the process parameter setting value, the control modules work cooperatively to achieve precise control of the start-up process.

[0039] Optionally, the step can include: Step 1, heating the silicon core to a preset temperature based on the process parameter setting value; Step 2, controlling the gas flow rate, mixing ratio and inlet pressure based on the process parameter setting value.

[0040] Further, based on the process parameter setting value, the silicon core is heated to a preset temperature: the embedded power control module adjusts the current / voltage of the silicon core in stages according to the temperature setting value in the table, and the silicon core is uniformly heated through the principle of resistance heating. The built-in power balance algorithm ensures that the heating power of multiple silicon cores is consistent, avoiding temperature deviation. Based on the process parameter setting value, the gas flow rate, mixing ratio and inlet pressure are controlled: the material control system of the DCS adjusts the mass flow meter (MFC) and pressure regulating valve through the PID control loop to accurately control the flow ratio of silane (or trichlorosilane) and hydrogen and the gas inlet pressure, so that the gas parameters are stable at the set value.

[0041] It can be seen that, through precise start-up operation, the reduction furnace can quickly and stably reach the reaction conditions, shorten the start-up time and reduce energy consumption; at the same time, uniform heating of the silicon core and accurate gas control lay a foundation for uniform growth of polysilicon in the subsequent deposition process and improve the consistency of product quality.

[0042] S106, when the start-up operation is completed, performing deposition operation based on the parameter curves of each stage in the reduction furnace control table; On the basis of S105, the step aims to perform deposition operation based on the parameter curves of each stage in the reduction furnace control table when the start-up operation is completed. The deposition operation is the core link of polysilicon production, and different stages require different process parameters (such as feed amount, temperature, power) to control the deposition rate and crystal quality of silicon. Based on the parameter curves in the table, the process parameters are dynamically adjusted during the deposition process to meet the needs of different stages of polysilicon growth.

[0043] Optionally, this step can include: Step 1: Obtain the feed curve, temperature curve, and power curve from the reduction furnace control table; Step 2: Perform deposition operation based on the feed curve, temperature curve, power curve, and running stage data.

[0044] Further, obtain the feed curve, temperature curve, and power curve from the reduction furnace control table: the DCS controller parses the time-parameter correspondence of each stage in the table to generate real-time executable curve data.

[0045] Perform deposition operation based on the feed curve, temperature curve, power curve, and running stage data: the DCS system retrieves the parameter curve of the corresponding stage in real time according to the current deposition stage (such as initial deposition, main deposition, and finishing stage), adjusts the feed flow through the material control module, adjusts the silicon core power through the power control module, and then controls the temperature in the furnace, so that each parameter changes dynamically according to the preset curve. At the same time, the system collects feedback data such as deposition rate and silicon core diameter in real time, compares it with the parameter curve, and adjusts the parameters through closed-loop control to ensure that the deposition process proceeds according to the plan.

[0046] As can be seen, the deposition operation based on the parameter curve in this step realizes dynamic and accurate control of the process, and can automatically adjust the parameters according to the growth state of the polysilicon, improve the deposition rate and the growth rate of the silicon rod diameter, and at the same time ensure the uniformity and consistency of the crystal quality, reduce energy consumption and production cost.

[0047] S107: When the shutdown condition in the reduction furnace control table is reached, perform the shutdown operation.

[0048] Based on S106, this step aims to perform the shutdown operation when the shutdown condition in the reduction furnace control table is reached. The shutdown condition is a key indicator for determining whether the production process is complete. When the shutdown condition is reached, the shutdown operation is performed to ensure that the polysilicon product meets the expected quality standards, and to avoid energy waste and equipment damage caused by overproduction.

[0049] Further, the DCS system continuously monitors the shutdown conditions set in the table. The shutdown condition can be that the silicon rod diameter is measured in real time by a laser diameter measuring instrument and compared with the target diameter set in the table; or it can be that the deposition time is recorded and compared with the preset time threshold. When any condition is met, the DCS triggers the shutdown sequence: the feed gas is cut off in sequence, the embedded power module gradually reduces the silicon core power according to the preset curve until it is cut off, the protection gas is switched to perform purging, the cooling water flow is adjusted by the DCS to adjust the cooling rate of the furnace body, and the equipment is cooled down safely.

[0050] It can be seen that the shutdown operation is performed according to the preset condition in this step, which can ensure the consistency and stability of the polysilicon product quality, avoid manual judgment errors, reduce the thermal stress impact of the equipment, prolong the service life of the equipment, and reduce the safety risk in the shutdown process.

[0051] In summary, the embodiment realizes full-process automatic control by obtaining the reduction furnace control table through the DCS system and performing pre-starting detection, purging, starting, deposition and shutdown operations according to the control table, improves operation efficiency, ensures accurate execution of parameters at each stage, reduces manual intervention, and improves the operation stability and production safety of the reduction furnace.

[0052] Optionally, the embodiment further comprises: Step 1, when the shutdown operation is completed, the DCS system generates batch production data; wherein the batch production data includes: instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate; Step 2, analyzing the batch production data based on a big data anomaly analysis model to obtain an optimized reduction furnace control table.

[0053] The batch production data is a quantitative feedback of the production process, and by analyzing key indicators such as power consumption and deposition rate, the rationality and abnormal points of process parameters can be identified. The big data anomaly analysis model can mine the rules in historical data to form a closed-loop optimization and solve the lag problem of adjusting the table based on manual experience in the traditional method.

[0054] Furthermore, the optional scheme realizes iteration of “production-analysis-optimization” by generating the production data back to the table, improves the adaptability of process parameters, reduces energy consumption and improves product quality.

[0055] Further, the DCS system collects parameters such as power consumption (calculated from current and voltage data feedback by the power module), deposition rate (silicon core diameter change amount / time), and silicon core diameter growth rate (real-time measurement by a laser diameter gauge) in real time through an embedded big data module, and automatically generates a batch report after shutdown. The model is based on historical successful batch data, uses regression analysis and machine learning algorithms to establish a parameter correlation model, identifies the root cause of abnormal data, and recommends the optimal parameter combination.

[0056] The machine learning algorithm can be a random forest or a neural network.

[0057] The abnormal data can be a sudden increase in power consumption or a sudden decrease in deposition rate.

[0058] The optimal parameter combination can also be an adjustment of the power ramp-up curve or an adjustment of the feed temperature set point.

[0059] Optionally, the optional scheme realizes continuous iteration of process parameters through automatic batch data analysis and meter optimization, which can reduce power consumption by 10%-15% and increase deposition rate by 5%-8% compared with traditional manual adjustment of the meter; eliminates the dependence on third-party optimization system, and the enterprise can independently optimize the process based on production data, thereby enhancing the technical independence and cost control ability.

[0060] Optionally, the embodiment can further include: Step 1, obtaining real-time key parameters for the deposition operation; wherein the key parameters include: power fluctuation, temperature deviation, deposition rate change, pressure anomaly, tail gas anomaly; Step 2, when the key parameters trigger the first preset condition, a slight abnormality message is sent, and a preset fine-tuning strategy is executed; Step 3, when the key parameters trigger the second preset condition, a serious abnormality message is sent, a preset safety interlock operation is executed, an audible and visual alarm is issued, and the failure cause and the executed protection action are displayed on the operation interface.

[0061] Mainly considering that parameter fluctuations in the deposition process may be caused by equipment failure, raw material change, etc., through hierarchical early warning and disposal, the interference can be quickly eliminated, the fault expansion can be avoided, and the production continuity and safety can be ensured.

[0062] Among them, the DCS collects power (feedback through the power module), temperature (measured by a thermocouple), deposition rate (measured by a laser diameter gauge), pressure (measured by a pressure transmitter), and tail gas composition (mass spectrometer) in real time through sensors, and the sampling frequency is ≥10Hz.

[0063] Among them, the first preset condition (slight abnormality): such as temperature deviation ±10℃, power fluctuation ±5%, triggering the fine-tuning strategy of the embedded optimization module, automatically compensating for the deviation; Among them, the second preset condition (serious abnormality): such as broken rod, temperature jump ±50℃, triggering the safety interlock, and displaying the failure cause through the audible and visual alarm and the operation interface.

[0064] Among them, the safety interlock can include emergency shutdown and cutting off the feed.

[0065] Among them, the failure cause can be "silicon rod broken, power cut off".

[0066] As can be seen, through the abnormal response time in the optional scheme, which is shortened from 10-30 minutes in traditional manual inspection to seconds, the silicon rod scrap rate caused by parameter abnormalities is reduced by more than 70%; the safety interlock mechanism avoids major equipment accidents, ensures personnel safety, and automatically records fault data, providing a basis for subsequent process optimization.

[0067] A DCS embedded reduction furnace control device provided by an embodiment of the present application is introduced below, and the DCS embedded reduction furnace control device described below can correspond to the DCS embedded reduction furnace control method described below.

[0068] Please refer to Figure 2 , Figure 2 A structure diagram of a DCS embedded reduction furnace control device provided by an embodiment of the present application.

[0069] In the embodiment, the device can include: The material table acquisition module 100 is configured to acquire the input reduction furnace control material table through the operation interface. The pre-start detection module 200 is configured to perform pre-start detection based on a preset detection execution table. The purge execution module 300 is configured to execute a purge program when the pre-start safety detection is completed. The parameter acquisition module 400 is configured to acquire process parameter set values from the reduction furnace control material table when the purge program is executed. The start operation module 500 is configured to execute start operation based on the process parameter set values. The deposition operation module 600 is configured to execute deposition operation based on the parameter curves of each stage in the reduction furnace control material table when the start operation is completed. The stop operation module 700 is configured to execute stop operation when a stop condition in the reduction furnace control material table is reached.

[0070] Optionally, the device further includes: The abnormality analysis module is configured to generate batch production data when the stop operation is completed, wherein the batch production data includes instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate; and the batch production data is analyzed based on a big data abnormality analysis model to obtain an optimized reduction furnace control material table.

[0071] The present application further provides a DCS embedded reduction furnace control device, please refer to Figure 3 , Figure 3 A structure diagram of a DCS embedded reduction furnace control device provided by an embodiment of the present application, the DCS embedded reduction furnace control device can include: The memory is configured to store a computer program. The processor is configured to execute the computer program to implement the steps of any one of the DCS embedded reduction furnace control methods described above.

[0072] As Figure 3As shown in the figure, it is a schematic diagram of the composition structure of a DCS embedded reduction furnace control device. The DCS embedded reduction furnace control device can include a processor 10, a memory 11, a communication interface 12 and a communication bus 13. The processor 10, the memory 11 and the communication interface 12 can communicate with each other through the communication bus 13.

[0073] In the embodiment of the present application, the processor 10 can be a central processing unit (CPU), an application specific integrated circuit, a digital signal processor, a field programmable gate array or other programmable logic device, etc.

[0074] The processor 10 can call the program stored in the memory 11. Specifically, the processor 10 can perform the operations in the embodiments of the abnormal IP identification method.

[0075] The memory 11 is used to store one or more programs. The program can include program code, and the program code includes computer operation instructions. In the embodiment of the present application, the memory 11 at least stores a program for implementing the following functions: The DCS system obtains the input reduction furnace control table through the operation interface; Perform pre-start detection based on the preset detection execution table; When the pre-start safety detection is completed, execute the purging program; When the purging program is executed, obtain the process parameter set value from the reduction furnace control table; Perform start-up operation based on the process parameter set value; When the start-up operation is completed, perform deposition operation based on the parameter curve of each stage in the reduction furnace control table; When the shutdown condition in the reduction furnace control table is reached, perform shutdown operation.

[0076] In a possible implementation, the memory 11 can include a program storage area and a data storage area. The program storage area can store an operating system and at least one application required by a function; and the data storage area can store data created during use.

[0077] In addition, the memory 11 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device or other volatile solid-state storage device.

[0078] The communication interface 12 can be an interface of a communication module, used for connecting with other devices or systems.

[0079] Of course, it should be noted that, Figure 3The structure shown does not constitute a limitation on the DCS embedded reduction furnace control device in the embodiments of the present application, and in actual applications, a DCS embedded reduction furnace control device can include more or fewer components than those shown, or some components can be combined. Figure 3

[0080] The present application also provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of any one of the above DCS embedded reduction furnace control methods.

[0081] The computer readable storage medium can include a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage medium that can store program codes.

[0082] For the computer readable storage medium provided by the present application, refer to the above method embodiments, which will not be described here.

[0083] The embodiments in the description are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts of each embodiment can be referred to each other. For the device disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple, and the related parts can be referred to the method part.

[0084] The skilled person can further realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware, computer software or a combination of the two. In order to clearly show the interchangeability of hardware and software, the components and steps of each example have been described in the above description. Whether the functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. The skilled person can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0085] The steps of the method or algorithm described in combination with the embodiments disclosed herein can be directly implemented by hardware, a software module executed by a processor, or a combination of the two. The software module can be placed in a random access memory (RAM), a memory, a read-only memory (ROM), an electrically programmable ROM, an electrically erasable programmable ROM, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0086] ​The above describes in detail the DCS embedded reduction furnace control method, the DCS embedded reduction furnace control device, the DCS embedded reduction furnace control equipment, and the computer readable storage medium provided by the application. The principles and implementation manners of the application are described by applying specific examples, and the above description of the examples is only used to help understand the method and the core idea of the application. It should be pointed out that, for those skilled in the art, some improvements and modifications can be made to the application without departing from the principles of the application, and these improvements and modifications also fall within the protection scope of the claims of the application.

Claims

1. A DCS embedded reduction furnace control method, characterized in that, include: The DCS system obtains the input reduction furnace control material list through the operation interface; Pre-start inspection is performed based on a preset inspection execution table; Once the pre-start-up safety inspection is completed, the purging procedure is executed; When the purging procedure is completed, the process parameter setting values ​​are obtained from the reduction furnace control material table; The furnace start-up operation is performed based on the set values ​​of the process parameters; When the furnace start-up operation is completed, the deposition operation is performed based on the parameter curves of each stage in the reduction furnace control bill. When the shutdown conditions in the reduction furnace control list are met, the shutdown operation is performed.

2. The DCS embedded reduction furnace control method according to claim 1, characterized in that, Also includes: When the furnace shutdown operation is completed, the DCS system generates batch production data; wherein, the batch production data includes: instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate; The batch production data was analyzed using a big data anomaly analysis model to obtain an optimized control material list for the reduction furnace.

3. The DCS embedded reduction furnace control method according to claim 2, characterized in that, Pre-start inspections are performed based on a preset inspection execution table, including: The DCS system performs a pre-start safety check; the pre-start safety check includes: confirming that the cooling water system is normal, the exhaust gas system is ready, the protective gas is qualified, all valves are in the safe position, and there are no major alarms; Silicon core resistance detection is performed via an embedded power control module.

4. The DCS embedded reduction furnace control method according to claim 3, characterized in that, Performing a furnace start-up operation based on the aforementioned process parameter settings includes: The silicon core is heated to a preset temperature based on the process parameter settings. The gas flow rate, mixing ratio, and inlet pressure are controlled based on the set values ​​of the process parameters.

5. The DCS embedded reduction furnace control method according to claim 4, characterized in that, Also includes: Real-time key parameters are obtained for the deposition operation; wherein, the key parameters include: power fluctuation, temperature deviation, deposition rate change, pressure anomaly, and exhaust gas anomaly; When the key parameter is detected to trigger the first preset condition, a minor abnormality message is sent and a preset fine-tuning strategy is executed; When the critical parameter is detected to trigger the second preset condition, a serious abnormality message is sent, and a preset safety interlock operation is executed, an audible and visual alarm is issued, and the cause of the fault and the executed protection actions are displayed on the operation interface.

6. The DCS embedded reduction furnace control method according to claim 5, characterized in that, The deposition operation is performed based on the parameter curves of each stage in the reduction furnace control bill, including: The feed curve, temperature curve, and power curve are obtained from the control feed table of the reduction furnace. The deposition operation is performed based on the feed curve, the temperature curve, the power curve, and the operation phase data.

7. A DCS embedded reduction furnace control device, characterized in that, include: The material list acquisition module is used to acquire the input reduction furnace control material list through the operation interface; The pre-start detection module is used to perform pre-start detection based on a preset detection execution table; The purging execution module is used to execute the purging procedure when the pre-start-up safety test is completed; The parameter acquisition module is used to acquire the process parameter setting values ​​from the reduction furnace control material table when the purging procedure is completed. The furnace start-up operation module is used to perform the furnace start-up operation based on the process parameter set values; The deposition operation module is used to perform the deposition operation based on the parameter curves of each stage in the control bill of the reduction furnace when the furnace start-up operation is completed. The furnace shutdown operation module is used to execute a furnace shutdown operation when the shutdown conditions in the reduction furnace control material list are met.

8. The DCS embedded reduction furnace control device according to claim 7, characterized in that, Also includes: An anomaly analysis module is used to generate batch production data when the furnace shutdown operation is completed. The batch production data includes instantaneous power consumption, average power consumption, deposition rate, and silicon core diameter growth rate. The batch production data is analyzed based on a big data anomaly analysis model to obtain an optimized reduction furnace control material list.

9. A DCS embedded reduction furnace control device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the steps of the DCS embedded reduction furnace control method as described in any one of claims 1 to 6 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the steps of the DCS embedded reduction furnace control method as described in any one of claims 1 to 6.

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