A control system and method for a high-purity fused silica crucible sintering furnace

Abstract

This invention relates to the field of sintering process control technology, specifically to a control system and method for a high-purity fused silica crucible sintering furnace. This invention not only accurately identifies the influence of structural defects and raw material phase changes on the temperature field, but also selects targeted compensation strategies based on the characteristics of each sintering process stage, ultimately ensuring a uniform and stable temperature field through closed-loop control. It effectively solves the problem caused by the coupling between structural thermal defects and raw material phase changes, enabling the entire sintering process to maintain a highly uniform and stable temperature environment, thereby improving the sintering quality of the high-purity fused silica crucible.

Description

Technical Field

[0001] This invention relates to the field of sintering process control technology, specifically to a control system and method for a high-purity fused silica crucible sintering furnace. Background Technology

[0002] High-purity fused silica crucibles are widely used in semiconductor, photovoltaic and other manufacturing fields. Their performance mainly depends on the uniformity and stability of the temperature field during sintering.

[0003] In the actual sintering process of quartz crucibles, long-term operation of the kiln can easily lead to structural defects such as loose insulation layers and localized failure of heating elements. These defects cause changes in localized thermal conductivity within the furnace, resulting in uneven distribution of the firing temperature field and common defects such as uneven wall thickness and excessive hydroxyl content in the quartz crucibles. Simultaneously, the quartz raw material undergoes multiple physicochemical phase transitions during heating, which are often accompanied by significant endothermic or exothermic reactions, causing instantaneous temperature fluctuations and similarly leading to uneven distribution of the firing temperature field.

[0004] Existing technologies, such as Chinese invention patent publication number CN116518722A, disclose a temperature control system for a semiconductor ceramic sintering furnace. This system uses an infrared camera to acquire real-time video and temperature values ​​of the ceramic inside the furnace. Combined with an image processing and data analysis module, it identifies ceramic cracks and abnormal brightness. Based on a preset temperature range, it triggers the heating or cooling module to achieve closed-loop control of the sintering temperature.

[0005] However, after in-depth analysis, the existing technology still has the following limitations: the system only relies on local temperature thresholds and image brightness to make judgments, lacks quantitative analysis and dynamic compensation for the uniformity of temperature field distribution in the furnace, and lacks feedforward compensation for phase change heat effect, resulting in lag in control response.

[0006] Existing technologies, such as Chinese invention patent application number 202410995850.3, disclose a temperature control method for a solar cell sintering furnace and a solar cell sintering furnace. By monitoring the empty furnace state and raising the set temperature of the high-temperature zone to the compensation temperature when the cells are fed, and then restoring it to the process temperature after a certain period of time, the method can address the problem of temperature drop caused by heat absorption by the cells in the early stage of restarting the machine.

[0007] However, after in-depth analysis, the existing technology still has the following limitations: it cannot solve the problem of continuous temperature anomalies caused by defects in the kiln structure and the impact of raw material phase change on the temperature field, and it lacks the ability to dynamically adjust according to the temperature change trend. Summary of the Invention

[0008] The purpose of this invention is to overcome the shortcomings of the prior art by dynamically identifying the influence of kiln structural defects and raw material phase changes on the temperature field, and implementing targeted power compensation according to different stages of the sintering process, thereby achieving high uniformity and high stability of the temperature field during sintering.

[0009] The technical solution adopted by the present invention to solve its technical problem is: a control system for a high-purity fused silica crucible sintering furnace, comprising: an acquisition and analysis module, used to acquire the current heating power and temperature data of multiple monitoring points in the furnace, construct a temperature distribution map, and analyze the temperature distribution map to obtain the temperature change rate, temperature non-uniformity, average temperature and average temperature rise rate.

[0010] The structural compensation module is used to compare the temperature distribution maps of adjacent monitoring times. When an abnormal temperature zone in the kiln body is identified, the structural compensation power is obtained based on the temperature non-uniformity and temperature change rate.

[0011] The phase change compensation module is used to combine the average temperature rise rate and average temperature analysis to obtain the predicted temperature. When the predicted temperature falls into the phase change temperature range, it analyzes the temperature rise trend and calculates the trend deviation. Then, it combines the temperature non-uniformity and temperature change rate to obtain the phase change compensation power.

[0012] The coordination and execution module is used to determine the compensation strategy based on the current sintering process stage and send it to the heating execution end for execution.

[0013] The feedback monitoring module is used to update the temperature distribution map after the compensation strategy is executed and to determine whether the compensation strategy needs to be redefined.

[0014] Compared with existing technologies, this invention has the following advantages: 1. This invention can not only accurately identify the influence of structural defects and raw material phase transformation on the temperature field, but also select targeted compensation strategies according to the characteristics of each sintering process stage, and finally ensure a uniform and stable temperature field through closed-loop control. It effectively solves the problem caused by the coupling between structural thermal defects and raw material phase transformation, enabling the entire sintering process to maintain a highly uniform and stable temperature environment, thereby improving the sintering quality of high-purity fused silica crucibles.

[0015] 2. This invention can identify temperature anomaly zones with fixed spatial locations caused by defects in the kiln structure, and actively counteract their effects through structural compensation power, thereby avoiding uneven temperature caused by loose insulation layers or local failure of heating elements.

[0016] 3. This invention predicts the temperature and triggers phase change compensation in advance, and actively uses the phase change compensation power to adjust the heating power, so as to prevent instantaneous temperature fluctuations caused by phase change heat absorption or release, which would lead to uneven distribution of the firing temperature field. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the system module connections of the present invention.

[0019] Figure 2 This is a schematic diagram of the control method of the present invention.

[0020] Figure 3 This is a schematic diagram of the process for identifying temperature anomaly zones according to the present invention.

[0021] Figure 4 This is a schematic diagram of the process for obtaining the predicted temperature according to the present invention. Detailed Implementation

[0022] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the invention. Furthermore, it should be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale.

[0023] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use. Techniques, methods, and apparatus known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and apparatus should be considered part of the specification.

[0024] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0026] The following description, in conjunction with the accompanying drawings, details a specific scheme for a high-purity fused silica crucible sintering furnace control system provided by the present invention.

[0027] Please see Figure 1 The diagram shows a schematic of the module connection of a high-purity fused silica crucible sintering furnace control system provided by the present invention, which specifically includes: a data acquisition and analysis module, a structural compensation module, a phase change compensation module, a coordinated execution module, and a feedback monitoring module.

[0028] The data acquisition and analysis module is connected to the structural compensation module, the phase transformation compensation module, and the feedback monitoring module. Data starts from the data acquisition and analysis module and is transmitted to the structural compensation module and the phase transformation compensation module respectively. The structural compensation module and the phase transformation compensation module are both connected to the coordination execution module, which is connected to the feedback monitoring module. The execution result data is fed back to the data acquisition and analysis module by the feedback monitoring module, thus realizing the dynamic optimization and closed-loop control of the crucible melting temperature.

[0029] The data acquisition and analysis module first collects the current heating power and temperature data from multiple monitoring points inside the kiln, and then constructs a temperature distribution map.

[0030] In this process, a spatial coordinate system is first established: with the geometric center of the kiln as the origin, the height of the kiln as the Z-axis, and the horizontal radial direction as the X-axis and Y-axis.

[0031] Because during the sintering process of high-purity fused silica crucibles, heat is mainly transferred to the raw materials through radiation and conduction from the furnace wall, and the temperature gradient is often most significant in the height direction. Therefore, based on this spatial coordinate system, several horizontal sections are set at equal intervals along the Z-axis, with at least three horizontal sections.

[0032] Data collection points are set up within each horizontal cross-section, with each point evenly distributed in a ring shape. Furthermore, the collection points at different horizontal cross-sections correspond one-to-one radially. This point arrangement allows the system to effectively acquire temperature data from different spatial locations within the kiln.

[0033] After the collection points are set up, the collection and analysis module synchronously collects the temperature data and corresponding heating power of each point, and records the spatial coordinates and temperature values ​​of each collection point.

[0034] Next, a spatial interpolation algorithm is used to process the discrete acquisition point data to generate a continuous temperature distribution surface.

[0035] It should be noted that the spatial interpolation algorithm can be the inverse distance weighting method. Its basic principle is that the temperature value of any unmeasured point is obtained by the weighted average of the temperatures of its neighboring measured points, and the weight is inversely proportional to the distance. This is an existing technical method, and will not be elaborated on in this invention.

[0036] Finally, all the temperature distribution surfaces of the horizontal sections are stacked along the Z-axis, and then connected and smoothed along the Z-axis using a three-dimensional interpolation method to construct a temperature distribution map covering the entire kiln monitoring area. This temperature distribution map provides the temperature value corresponding to the spatial coordinates of any acquisition point, facilitating subsequent temperature analysis.

[0037] Based on the completion of the temperature distribution map, the data acquisition and analysis module further calculates four key temperature-related parameters to reflect the current state and trend of the temperature field.

[0038] First, for each collection point, the temperature difference between the current monitoring time and the previous monitoring time is calculated. Combined with the time interval between the current monitoring time and the previous monitoring time, the ratio is calculated to obtain the temperature change rate. The temperature change rate reflects the instantaneous temperature change trend of each collection point.

[0039] Simultaneously, the standard deviation of temperature values ​​at all sampling points in the temperature distribution map is calculated as the temperature non-uniformity, which is used to quantify the overall uniformity of temperature inside the kiln. In addition, the temperature values ​​at all sampling points in the temperature distribution map are extracted and their arithmetic mean is calculated to obtain the average temperature, which reflects the overall temperature level of the kiln.

[0040] Finally, the difference between the average temperature at the current monitoring time and the average temperature at the previous monitoring time is calculated. Combined with the time interval, the ratio is calculated to obtain the average temperature rise rate, which lays the foundation for subsequent prediction of temperature development trends.

[0041] After the data acquisition and analysis module completes basic data processing, the structural compensation module then intervenes. This module identifies and addresses persistent temperature anomalies caused by structural defects in the kiln, such as loose insulation, changes in the density of the kiln wall, or localized aging of heating elements.

[0042] The reason for considering kiln structural defects is that changes in the kiln wall structure directly alter its heat conduction. For example, areas with increased porosity exhibit decreased thermal conductivity, forming localized insulation layers and consequently resulting in lower temperatures for the raw materials inside; while denser areas may accumulate heat, forming hotspots. Ultimately, this manifests as a relatively fixed and persistent non-uniform temperature field, i.e., a temperature anomaly zone.

[0043] Please see Figure 3 To accurately identify temperature anomaly zones, a temperature fluctuation range is first set. The upper boundary of this temperature fluctuation range is the sum of the average temperature and the preset anomaly threshold, and the lower boundary is the difference between the average temperature and the preset anomaly threshold.

[0044] In one example of the present invention, the preset abnormality threshold can be set to 8 degrees Celsius. When the kiln ages rapidly or its insulation performance generally declines, the preset abnormality threshold can be appropriately increased; for new kilns or to achieve high-precision control, the preset abnormality threshold can be appropriately decreased.

[0045] Then, the temperature values ​​and spatial coordinates of all collection points are obtained from the temperature distribution maps of the current and previous monitoring times. Subsequently, collection points that exceed the specified range for two consecutive monitoring times are selected as candidate anomalies.

[0046] Next, a circular neighborhood with a radius equal to half the distance between adjacent collection points is constructed, centered on each candidate anomaly point. The union of all neighborhoods is then used to generate a closed continuous region through contour extraction algorithms such as MarchingSquares, thus obtaining the candidate anomaly region at the current monitoring time and the candidate anomaly region at the previous monitoring time.

[0047] Then, the area of ​​the intersection of the two candidate anomaly regions is calculated as the proportion of the area of ​​the candidate anomaly region at the current time.

[0048] It should be noted that the above-mentioned calculation process can be implemented by standard computational geometry libraries, which is an existing technical means, and will not be elaborated upon in this invention.

[0049] If the ratio is greater than or equal to the preset overlap limit, the overlapping area is determined to be a temperature anomaly zone. If the ratio is less than the preset overlap limit, it is determined to be transient interference and no compensation is given.

[0050] Through the dual verification of the temperature fluctuation range and the preset overlap extreme value, structural defects and random fluctuation interference can be effectively distinguished.

[0051] In one example of the present invention, the preset overlap degree extreme value can be 0.7. If the kiln operating environment is stable, the preset overlap degree extreme value can be increased, such as to 0.8. If the kiln operating conditions are complex, such as large vibration in the operating environment, the preset overlap degree extreme value can be decreased, such as to 0.6.

[0052] After accurately identifying the temperature anomaly zone, the structural compensation module enters the structural compensation power calculation stage. The specific calculation process is as follows: First, the temperature change rate of all sampling points in the temperature anomaly zone is extracted, and the arithmetic mean is calculated to obtain the current average temperature change rate.

[0053] Then, the temperature non-uniformity corresponding to all sampling points in the temperature distribution map is multiplied by the absolute value of the current average temperature change rate to calculate the basic compensation range; the more non-uniform the temperature and the faster the change, the higher the structural compensation strength.

[0054] To ensure the accuracy of the structural compensation direction, the compensation direction is also determined based on the sign of the average temperature change rate: when the average temperature change rate is negative, it indicates that the temperature is decreasing and the heating power needs to be increased; conversely, the heating power needs to be reduced.

[0055] The actual temperature rise effect of compensation power in areas of temperature anomalies dynamically changes due to factors such as kiln aging, decreased insulation performance, or varying overall furnace temperature. Calculating structural compensation power solely based on the current temperature field is insufficient to accommodate this dynamic characteristic. Therefore, this invention introduces a compensation efficiency factor to quantify the actual temperature rise effect of historical structural compensation. This allows the system to adaptively adjust the current compensation intensity based on historical compensation results, improving temperature control accuracy.

[0056] The formula for calculating the compensation effectiveness factor is: . The larger the value, the more significant the temperature rise per unit power.

[0057] in, It is the average temperature difference between the monitoring time corresponding to the current adjacent structural compensation power in the historical compensation data and the temperature anomaly zone at the current monitoring time; This is the absolute value of the compensation power for the currently adjacent structures.

[0058] The final structural compensation power is the product of the basic compensation amplitude and the compensation efficiency factor. Through structural compensation power, the system can actively offset the influence of structural defects on the temperature field without repairing the kiln structure.

[0059] While the structural compensation module is operating, the phase change compensation module addresses the impact of the heat absorption and release during the phase change of the raw materials on the temperature field. The phase change process is characterized by its suddenness, intense thermal effects, and short duration. If not intervened in time, it can easily cause the heating curve to deviate from the process requirements, or even lead to local temperature collapse.

[0060] Please see Figure 4 Therefore, the probability of a phase transition is first predicted by forecasting the temperature. The specific process is as follows: taking the current monitoring time as the origin, and using the current average temperature... Initial value, average temperature rise rate Using the slope, construct a temperature prediction function: .in, This refers to future time starting from the present.

[0061] Based on the sintering process, a target time is preset from the current moment until the phase transformation reaction occurs. .Will Substituting the values ​​into the temperature prediction function yields the predicted temperature. .

[0062] During the sintering process of high-purity fused silica crucibles, the main phase transformation types involved include dehydroxylation reaction and cristobalite crystal transformation. The dehydroxylation reaction mainly occurs at 1000-1100 degrees Celsius, while the cristobalite crystal transformation mainly occurs at two temperature points: 268 degrees Celsius and 573 degrees Celsius.

[0063] The target duration for different phase transitions is set based on their theoretical arrival time at the current average heating rate. For example, if the current average temperature rise rate is 5 degrees Celsius per minute, the target phase transition is a dehydroxylation reaction at 1050 degrees Celsius, and the current average temperature is 900 degrees Celsius, then... = (1050-900) ÷ 5 = 30 minutes.

[0064] It is important to note that before reaching the target duration, the system will dynamically update the origin, initial value, and slope based on subsequent monitoring times, continuously correcting the temperature prediction function, and iteratively updating the predicted temperature to ensure the accuracy of the prediction results.

[0065] when When the temperature falls within the preset phase transition temperature range, the phase transition compensation module immediately performs a temperature rise trend analysis. The preset phase transition temperature range can be determined based on the material properties of the high-purity fused silica raw material. For example, the dehydroxylation temperature range is typically set to 1000–1100℃, and the cristobalite crystal transformation temperature range is typically set to 560–590℃.

[0066] The temperature rise trend analysis process is as follows: First, the average temperature rise rate of multiple consecutive monitoring times before the current monitoring time is extracted to form a time series. .

[0067] Next, linear regression analysis is performed on the time series. This process can be achieved by using the least squares method to fit a fitted line representing the temperature rise trend, i.e.: The specific fitting process is already known from existing technology and will not be described in detail here.

[0068] in, For the first The average temperature rise rate at each historical monitoring point; For time sequence number, , The number of historical monitoring moments selected. At least 5.

[0069] The slope represents the trend of temperature rise rate, reflecting the speed and direction of the average temperature rise rate as a function of time. This is the intercept. It indicates when... The theoretical rate of temperature rise at that time.

[0070] Set the current monitoring time as The next monitoring time is ,Will Substituting into the above formula, we get .

[0071] This is the expected average rate of temperature rise over the next monitoring period, i.e., the trend forecast.

[0072] Subsequently, the absolute value of the difference between the average temperature rise rate at the current monitoring time and the trend prediction value is calculated to obtain the deviation. Finally, the ratio of the deviation to the absolute value of the trend prediction value is used as the trend deviation degree, which measures the degree of abnormality in the temperature rise rate when the phase transition occurs.

[0073] After confirming the occurrence of a phase change, the phase change compensation module immediately calculates the phase change compensation power. The calculation process is as follows: First, the temperature change rate of all sampling points in the temperature distribution map is extracted, and the standard deviation is calculated to obtain the spatial fluctuation coefficient, which can reflect the local characteristics of temperature changes.

[0074] Next, the trend deviation, temperature non-uniformity, and spatial fluctuation coefficient are multiplied to obtain the phase change compensation reference quantity, which is directly used as the amplitude of the phase change compensation power.

[0075] It should be noted that, since the phase transition process of the quartz crucible raw material is mainly determined by the intrinsic properties of the material, its occurrence and the corresponding temperature range are basically predictable and deterministic under the same process conditions. Therefore, the core of this invention lies in predicting the timing of the phase transition and directly using the phase transition compensation benchmark as the amplitude of the phase transition compensation power, without introducing a compensation efficiency factor similar to that in structural compensation power. This ensures that the system responds quickly when the phase transition occurs and avoids compensation lag.

[0076] When determining the direction of phase change compensation, the positive or negative value of the difference between the current average temperature rise rate and the trend prediction value is used. When the difference is negative, it indicates that the phase change heat absorption is insufficient and the heating power needs to be increased. Conversely, the heating power needs to be reduced.

[0077] It is important to note that although structural compensation power and phase change compensation power can be calculated in parallel, which compensation power to execute and the order of execution must be determined based on the current sintering process stage to avoid control conflicts or resource waste. Therefore, the coordinated execution module first identifies the current stage.

[0078] If the current stage is the preheating stage, which is the dynamic heating process of rapidly and uniformly heating the raw materials from room temperature to the sintering temperature, this stage is both the period when structural defects are exposed and the period when the raw materials undergo various physical changes such as moisture evaporation and crystal transformation, that is, when multiple phase transformations occur simultaneously.

[0079] Therefore, when both structural compensation power and phase change compensation power are present, the system will preferentially use phase change compensation power as the compensation strategy because the heat absorption of phase change will drastically reduce the rate of temperature rise; then structural compensation power will be used. When only structural compensation power or phase change compensation power is present, it will be used directly as the compensation strategy.

[0080] If the current stage is the high-temperature sintering stage, i.e., the isothermal holding stage, then since the main phase transformation of the raw materials has been largely completed, the core objective of this stage is to maintain an extremely uniform and stable temperature field at high temperatures. Therefore, the system only uses the existing structural compensation power as a compensation strategy to correct heat loss or overheating caused by structural defects in the kiln body.

[0081] When the system is in the phase transition stage, i.e., when the predicted temperature has fallen into the phase transition temperature range, the system will only use the existing phase transition compensation power as the compensation strategy.

[0082] This is because, at the critical sintering stage of phase transformation, if structural compensation and phase transformation compensation work simultaneously, it may lead to the issuance of instructions that contradict phase transformation compensation.

[0083] For example, a region is cooling down due to heat absorption during phase change, and the phase change compensation module is increasing its heating power. At the same time, the structural compensation module may also increase its heating power because it recognizes the cooling down. The superposition of the two may cause the heating power in that region to be too high, resulting in a temperature surge after the phase change ends, causing new temperature unevenness problems and disrupting the stability of the temperature field.

[0084] By employing the aforementioned temperature control methods tailored to different stages of the sintering process, it can be ensured that the system remains focused on the primary issue under various operating conditions.

[0085] Once the compensation strategy is determined, it is sent to the heating actuator via the coordination and execution module. To verify the temperature control effect and achieve closed-loop optimization control, the feedback monitoring module starts running.

[0086] After the compensation strategy is completed, the feedback monitoring module re-collects the current heating power and temperature data, updates the temperature distribution map, and evaluates the temperature control effect.

[0087] If the temperature anomaly zone still exists or the predicted temperature still falls within the phase transition temperature zone, it indicates insufficient power compensation, and the system will re-trigger the acquisition and analysis module to start a new control cycle. If the temperature anomaly zone does not exist and the predicted temperature does not fall within the phase transition temperature zone, the system will continue monitoring.

[0088] In summary, this invention achieves intelligent temperature control during the sintering process of high-purity fused silica crucibles through the coordinated operation of a data acquisition and analysis module, a structural compensation module, a phase transformation compensation module, a coordinated execution module, and a feedback monitoring module. This invention not only accurately identifies the impact of structural defects and raw material phase transformations on the temperature field, but also selects targeted compensation strategies based on the characteristics of each sintering process stage, ultimately ensuring a uniform and stable temperature field through closed-loop control. It effectively solves the problem caused by the coupling between structural thermal defects and raw material phase transformations, enabling the entire sintering process to maintain a highly uniform and stable temperature environment, thereby improving the sintering quality of high-purity fused silica crucibles.

[0089] Please see Figure 2 A control method for a high-purity fused silica crucible sintering furnace includes the following steps: S1, collecting heating power and temperature data, constructing a temperature distribution map, and calculating the temperature change rate, temperature non-uniformity, average temperature, and average temperature rise rate.

[0090] S2. Compare the temperature distribution maps of adjacent monitoring times to identify abnormal temperature zones in the kiln body, and generate structural compensation power based on temperature non-uniformity and temperature change rate.

[0091] S3. Calculate the predicted temperature. When it falls into the phase change temperature zone, analyze the temperature rise trend and calculate the trend deviation. Then, combine the temperature non-uniformity and temperature change rate to generate the phase change compensation power.

[0092] S4. Determine the compensation strategy based on the current sintering process stage and issue it to the heating execution end for execution.

[0093] S5. After the compensation strategy is executed, update the temperature distribution map and determine whether the compensation strategy needs to be redefined.

[0094] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0095] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0096] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0097] In addition, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0098] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0099] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A control system for a high-purity fused silica crucible sintering furnace, characterized in that, include: The data acquisition and analysis module is used to collect the current heating power and temperature data of multiple monitoring points in the kiln, construct a temperature distribution map, and analyze the temperature distribution map to obtain the temperature change rate, temperature non-uniformity, average temperature and average temperature rise rate. The structural compensation module is used to compare the temperature distribution maps of adjacent monitoring times. When an abnormal temperature zone in the kiln body is identified, the structural compensation power is obtained based on the temperature non-uniformity and temperature change rate. The phase change compensation module is used to combine the average temperature rise rate and average temperature analysis to obtain the predicted temperature. When the predicted temperature falls into the phase change temperature zone, it analyzes the temperature rise trend and calculates the trend deviation. Then, it combines the temperature non-uniformity and temperature change rate to obtain the phase change compensation power. The coordination and execution module is used to determine the compensation strategy based on the current sintering process stage and send it to the heating execution end for execution; The feedback monitoring module is used to update the temperature distribution map after the compensation strategy is executed and to determine whether the compensation strategy needs to be redefined. The process of obtaining the structural compensation power is as follows: Extract the temperature change rate of all collection points in the temperature anomaly area, calculate the arithmetic mean, and obtain the current average temperature change rate. The basic compensation range is calculated by multiplying the temperature non-uniformity corresponding to all sampling points in the temperature distribution map with the absolute value of the current average temperature change rate. The direction of the reference compensation is determined based on the sign of the average temperature change rate. If it is negative, the heating power is increased; otherwise, the heating power is decreased. Extract the compensation power of the structure adjacent to the current one and its corresponding monitoring time from the historical compensation data; calculate the average temperature difference between the temperature anomaly zone at the monitoring time and the current monitoring time; divide the difference by the absolute value of the compensation power of the structure adjacent to the current one to obtain the compensation efficiency factor; The product of the basic compensation magnitude and the compensation effectiveness factor is taken as the structural compensation power; The process of analyzing the temperature rise trend and calculating the trend deviation is as follows: Extract the average temperature rise rate from multiple consecutive monitoring times preceding the current monitoring time to form a time series; Linear regression analysis was performed on the time series to obtain a fitted line representing the temperature rise trend; Calculate the corresponding value of the average temperature rise rate at the current monitoring moment on the fitted line, and use it as the trend prediction value; Calculate the absolute value of the difference between the average temperature rise rate at the current monitoring time and the trend prediction value to obtain the deviation. The ratio of the deviation to the absolute value of the trend forecast is used as the trend deviation.

2. The control system for a high-purity fused silica crucible sintering furnace according to claim 1, characterized in that, The process of constructing a temperature distribution map is as follows: A spatial coordinate system is established with the geometric center of the kiln body as the origin, the height direction of the kiln body as the Z-axis, and the horizontal radial direction as the X-axis and Y-axis. Several horizontal sections are set at equal intervals along the Z-axis, and sampling points are set in a ring evenly distributed within each horizontal section; Simultaneously collect temperature data, heating power, and spatial coordinates at each collection point at the current moment; A spatial interpolation algorithm is used to process discrete data collection points and generate a continuous temperature distribution surface. Integrate the temperature distribution surfaces of all horizontal sections to construct a temperature distribution map covering the kiln monitoring area.

3. The control system for a high-purity fused silica crucible sintering furnace according to claim 1, characterized in that, The process for obtaining the temperature change rate, temperature non-uniformity, average temperature, and average temperature rise rate is as follows: Calculate the temperature difference between the current monitoring time and the previous monitoring time at each collection point, and combine this time interval to calculate the ratio and obtain the temperature change rate; The standard deviation of temperature values ​​at all sampling points in the temperature distribution map is calculated as the temperature non-uniformity. Extract the temperature values ​​of all collection points in the temperature distribution map, calculate the arithmetic mean, and obtain the average temperature. Calculate the difference between the average temperature at the current monitoring time and the average temperature at the previous monitoring time, and then combine this with the time interval to calculate the ratio and obtain the average temperature rise rate.

4. The control system for a high-purity fused silica crucible sintering furnace according to claim 2, characterized in that, The process for identifying the temperature anomaly zone is as follows: Extract the temperature distribution map between the current monitoring time and the previous monitoring time, and obtain the temperature value and spatial coordinates of all collection points from it; The sum of the average temperature and the preset abnormal threshold is used as the upper boundary, and the difference is used as the lower boundary. The upper and lower boundaries form the temperature fluctuation range. Based on the temperature distribution maps of the current monitoring time and the previous monitoring time, the collection points whose temperature values ​​continuously exceed the temperature fluctuation range for two consecutive monitoring times are selected as candidate anomalies. The spatial distribution regions of all candidate anomalies are fitted into a continuous region to obtain the candidate anomaly region at the current monitoring time and the candidate anomaly region at the previous monitoring time. Calculate the proportion of the area of ​​the intersection of two candidate anomaly regions to the area of ​​the candidate anomaly region at the current time. If the ratio is greater than or equal to the preset overlap extreme value, the intersection is determined to be a temperature anomaly zone.

5. The control system for a high-purity fused silica crucible sintering furnace according to claim 3, characterized in that, The process of obtaining the predicted temperature is as follows: A temperature prediction function is constructed using the current monitoring time as the origin, the current average temperature as the initial value, and the average temperature rise rate as the slope. Based on the sintering process, a target time is preset from the current moment until the phase change reaction occurs; Substitute the target duration into the temperature prediction function, and the resulting temperature value is the predicted temperature. Furthermore, before reaching the target duration, the origin, initial value, and slope are updated based on subsequent monitoring times, thereby iteratively updating the predicted temperature.

6. The control system for a high-purity fused silica crucible sintering furnace according to claim 1, characterized in that, The process of obtaining the phase change compensation power is as follows: Extract the temperature change rate of all sampling points in the temperature distribution map, calculate the standard deviation, and obtain the spatial fluctuation coefficient; Multiply the trend deviation, temperature non-uniformity, and spatial fluctuation coefficient to obtain the phase change compensation reference quantity; The phase change compensation reference value is used as the amplitude of the phase change compensation power; Based on the sign of the difference between the current average temperature rise rate and the trend prediction value, the compensation direction of the phase change compensation power is determined. If it is negative, the heating power is increased; otherwise, the heating power is decreased.

7. The control system for a high-purity fused silica crucible sintering furnace according to claim 1, characterized in that, The process of determining the compensation strategy based on the current sintering process stage is as follows: Identify the current sintering process stage, including the preheating stage, high-temperature sintering stage, and phase transformation stage; Preheating stage: If both structural compensation power and phase change compensation power exist, phase change compensation power shall be used as the compensation strategy; if only one of them exists, it shall be used directly as the compensation strategy. High-temperature sintering stage: Only the existing structural compensation power is used as the compensation strategy; Phase transition stage: Only the existing phase transition compensation power is used as the compensation strategy.

8. A method for controlling a high-purity fused silica crucible sintering furnace, characterized in that, The following steps are performed by the high-purity fused silica crucible sintering furnace control system as described in any one of claims 1-7: S1. Collect heating power and temperature data, construct a temperature distribution map, and calculate the temperature change rate, temperature non-uniformity, average temperature, and average temperature rise rate. S2. Compare the temperature distribution maps of adjacent monitoring times to identify abnormal temperature zones in the kiln body, and generate structural compensation power based on temperature non-uniformity and temperature change rate. S3. Calculate the predicted temperature. When it falls into the phase change temperature zone, analyze the temperature rise trend and calculate the trend deviation. Then, combine the temperature non-uniformity and temperature change rate to generate the phase change compensation power. S4. Determine the compensation strategy based on the current sintering process stage and issue it to the heating execution end for execution; S5. After the compensation strategy is executed, update the temperature distribution map and determine whether the compensation strategy needs to be redefined.

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