Accurate temperature control system for remote plasma source annular quartz cavity production

Abstract

The invention discloses a precise temperature control system for remote plasma source annular quartz cavity production, and relates to the technical field of annular quartz cavity production. According to the precise temperature control system for remote plasma source annular quartz cavity production, a plurality of independent temperature control subareas in the circumferential direction dynamically move along with a heat source, and a two-dimensional temperature control framework in which circumferential follow-up subareas and radial layering are matched is constructed in a manner of precise matching of radial layering and machining depth, so that effective improvement of temperature uniformity is ensured; the condition of internal stress concentration is effectively inhibited, the temperature control precision and the response speed are improved through multi-parameter coupling of raw material thermophysical characteristics and process dynamic parameters, bidirectional seamless switching of cutting and fire planning is achieved through the process switching adaptation unit, manual parameter adjustment is not needed, continuous high-precision production is adapted, and the production efficiency is improved. And a coupling model of temperature distribution, roundness error and surface roughness is established, active pre-judgment and temperature control correction of the machining precision are achieved, and the machining precision is further guaranteed.

Description

Technical Field

[0001] This invention relates to the field of annular quartz cavity production technology, specifically a precision temperature control system for the production of annular quartz cavities using remote plasma sources. Background Technology

[0002] As a core component of high-end equipment such as semiconductor etching and photovoltaic thin film deposition, the processing accuracy of the remote plasma source annular quartz cavity directly determines the stability of plasma transmission, energy utilization efficiency, and equipment lifespan. During the production of remote plasma source annular quartz cavities via cutting / gowing, the frictional heat generated between the cutting tool and the quartz or the localized burning of the high-temperature flame during gowing create instantaneous concentrated heat sources, and the location of these heat sources dynamically moves with the processing trajectory. Due to the low thermal conductivity and sensitive coefficient of thermal expansion of quartz, it is extremely sensitive to temperature gradients and fluctuations. Improper temperature control can easily lead to internal stress concentration, resulting in cavity deformation, cracking, and surface defects. However, the current temperature control technology used in the cutting / gowing production of annular quartz cavities still has the following shortcomings:

[0003] I. Limited Temperature Control Dimensions and Poor Temperature Uniformity: Existing technologies mostly adopt a uniform heating / cooling mode across the entire area, without designing adaptive structures for the circumferential and radial spatial characteristics of the annular cavity. Specifically, circumferential heat source tracking is not achieved, leading to sudden temperature increases in concentrated heat sources and circumferential temperature differences generally exceeding ±8℃. Radial temperature control is not layered according to machining depth, resulting in an imbalance between heat generation from deep cutting and heat dissipation from the surface, with radial temperature differences exceeding 10℃. This directly leads to cavity roundness errors exceeding 0.15mm, dimensional accuracy deviations of ±0.2mm, and deformation rates as high as 18%-20%.

[0004] 2. Lack of parameter adaptation and insufficient temperature control accuracy: The thermophysical properties of quartz raw materials and dynamic process parameters such as cutting speed, flame gas flow rate and flame temperature were not incorporated into the temperature control model. Fixed temperature control parameters were used for one-size-fits-all control. Individual differences in quartz raw materials and fluctuations in process parameters led to a disconnect between the temperature control response and actual needs, resulting in a low product qualification rate.

[0005] 3. Poor process switching and difficulty in adapting to high-precision production: The temperature requirements of cutting (500-600℃) and planing (700-800℃) processes are significantly different. When switching processes, the temperature control reference parameters need to be manually adjusted, resulting in high switching response delay and large temperature fluctuations during the switching period. This can easily cause defects in the cavity of the process connection section and cannot meet the requirements of continuous high-precision production.

[0006] In view of this, a precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources is proposed to solve the shortcomings of existing temperature control systems, which are difficult to adapt to the high-precision requirements of the production of ring-shaped quartz cavities for remote plasma sources, resulting in low product qualification rate, insufficient production efficiency, and poor adaptability to high-end applications. Summary of the Invention

[0007] To address the shortcomings of existing technologies, this invention provides a precise temperature control system for the production of ring-shaped quartz cavities using remote plasma sources. This system solves the problems of current temperature control technologies used in the cutting / gowing production process of ring-shaped quartz cavities, which suffer from single temperature control dimensions, poor temperature uniformity, lack of parameter adaptation, insufficient temperature control accuracy, poor process switching, and difficulty in adapting to high-precision production.

[0008] To achieve the above objectives, the present invention provides the following technical solution: a precision temperature control system for the production of remote plasma source annular quartz cavities, comprising:

[0009] A multi-dimensional sensing module is used to collect multi-dimensional sensing data, including thermophysical property parameters of quartz raw materials, dynamic parameters of cutting / gowing processes, local heat source distribution data of the processing area, and real-time temperature data.

[0010] A dual-dimensional temperature control execution module is communicatively connected to a multi-dimensional sensing module. The dual-dimensional temperature control execution module dynamically adjusts the temperature control range based on local heat source distribution data of the processing area, and performs independent temperature control partitioning and real-time tracking of heat sources through a mechanical drive mechanism.

[0011] A multi-objective optimization feedback control module is communicatively connected to a multi-dimensional sensing module and a dual-dimensional temperature control execution module. The multi-objective optimization feedback control module calculates the temperature compensation amount based on the multi-dimensional sensing data using a multi-parameter coupling algorithm and outputs the compensation command to the dual-dimensional temperature control execution module.

[0012] The central control module is connected to the multi-dimensional sensing module, the dual-dimensional temperature control execution module, and the multi-objective optimization closed-loop control module via the EtherCAT bus. The central control module outputs temperature control commands to the dual-dimensional temperature control execution module based on the multi-dimensional sensing data and temperature compensation.

[0013] The present invention is further configured such that the thermophysical properties of the quartz raw material include the thermal conductivity and the coefficient of linear expansion of the quartz raw material;

[0014] The dynamic parameters of the cutting / gowing process include cutting speed, cutting depth, gowing gas flow rate, and gowing flame temperature;

[0015] The local heat source distribution data of the processing area includes the three-dimensional coordinates of the heat source location and temperature gradient data.

[0016] The present invention is further configured such that: the dual-dimensional temperature control execution module includes a heat source following circumferential temperature control unit and a layered-depth matching radial temperature control unit;

[0017] The heat source following circumferential temperature control unit is used to control several independent temperature control zones distributed in a circle to move along the ring guide rail, and dynamically follow the heat source based on the three-dimensional coordinates of the heat source position in the local heat source distribution data of the processing area; each independent temperature control zone is equipped with a pulse infrared heating tube and an adaptive cooling channel, and an adjustable nozzle is installed at the outlet of the cooling channel and is installed close to the heat source.

[0018] The layered-depth matching radial temperature control unit is used to divide the independent temperature control zone into several layers of equal thickness along the radial direction of the quartz cavity. The temperature control parameters of each layer are linearly correlated with the cutting depth / gowing and burning thickness. A temperature sensor is embedded in each layer to collect real-time temperature data. The linear correlation formula is as follows:

[0019] ;

[0020] In the formula, For local target temperature, As the reference temperature, For the current processing depth, Let be the correlation coefficient, and .

[0021] The present invention is further configured such that: the multi-objective optimization feedback control module includes a multi-parameter coupling deviation calculation unit and a compensation instruction generation unit;

[0022] The multi-parameter coupling deviation calculation unit is used to calculate the temperature compensation amount, and the calculation formula is:

[0023] ;

[0024] In the formula, This is the temperature compensation amount. The global reference target temperature, For real-time temperature data, All are PID coefficients, self-tuned using the Ziegler-Nichols method. These are all raw material characteristic compensation coefficients, calibrated using standard samples. These are all process parameter correction coefficients. This is the flame temperature correction factor. This is the roundness error feedback coefficient. All were determined through orthogonal experiments. Thermal conductivity, Standard thermal conductivity The coefficient of linear expansion is 1 / 3. The standard coefficient of linear expansion. For cutting speed, As the reference cutting speed, This refers to the flow rate of the fire-gouging gas. The reference flame gouging gas flow rate, The flame temperature of the fire-gouging process. The reference flame temperature for gouging. For roundness error, For target roundness error;

[0025] The compensation command generation unit is used to convert the temperature compensation amount into a PWM duty cycle adjustment signal for the pulse infrared heating tube and a flow rate adjustment signal for the adaptive cooling channel to form a compensation command. At the same time, it calculates the temperature gradient through the real-time temperature data of adjacent temperature control zones. When the temperature gradient exceeds 0.5℃ / mm, it triggers a coordinated adjustment command for the adjacent zones.

[0026] The present invention is further configured such that: the central control module includes a process switching adaptation unit and an intelligent instruction scheduling unit;

[0027] The process switching adaptation model unit is used to pre-store the temperature control parameter threshold library of cutting / gowing processes, and dynamically calibrate the reference heating / cooling rate when a process switching signal is received.

[0028] The intelligent instruction scheduling unit divides the independent temperature control zone into a heat source concentration area and a non-heat source area based on temperature gradient data. After determining the priority weights for each area, it allocates CPU computing resources and communication bandwidth through a priority scheduling algorithm to prioritize the execution of temperature control instructions. The temperature control instructions include compensation instructions and adaptive temperature control instructions.

[0029] The present invention is further configured such that the calculation formula for the heating / cooling rate of the dynamic calibration reference is:

[0030] ;

[0031] In the formula, For the calibrated baseline heating / cooling rate, As the initial reference rate, This represents the maximum permissible roundness error.

[0032] The present invention is further configured such that the logic for dividing the independent temperature control zone into a heat source concentration area and a non-heat source area includes:

[0033] When the temperature gradient is greater than 0.3℃ / mm, the independent temperature region is identified as a concentrated heat source region.

[0034] When the temperature gradient is less than 0.3℃ / mm, the independent temperature region is determined to be a non-heat source region.

[0035] The present invention is further configured such that: the central control module is communicatively connected to the correction module, and the correction module is used to construct a roundness error coupling model and a surface roughness coupling model;

[0036] The roundness error coupling model includes:

[0037] ;

[0038] In the formula, The radius of the annular quartz cavity is given. This is the roundness correction factor. The coefficient representing the influence of thermal conductivity. For the first Real-time temperature data for each independent temperature zone. The average real-time temperature data for all independent temperature zones. Number of independent temperature zones;

[0039] The surface roughness coupling model includes:

[0040] ;

[0041] In the formula, For surface roughness, As the reference roughness, This is the temperature influence coefficient. This is the coefficient affecting cutting speed.

[0042] The present invention is further configured such that: the central control module is also communicatively connected to the anomaly warning and emergency handling module, the anomaly warning and emergency handling module being used to monitor in real time the thermophysical property parameters of quartz raw materials, dynamic parameters of cutting / gowing processes, temperature deviation and temperature gradient data, and when the corresponding threshold is exceeded, an early warning is issued and an emergency temperature control strategy is triggered.

[0043] The present invention is further configured such that the emergency temperature control strategy is as follows: the central control module controls the annular quartz cavity to suspend processing and uniformly cools the annular quartz cavity.

[0044] This invention provides a precise temperature control system for the production of toroidal quartz cavities using remote plasma sources. It offers the following advantages:

[0045] (1) This invention constructs a two-dimensional temperature control architecture that matches the circumferential moving partitions and the radial layering by dynamically moving several independent temperature control partitions in the circumferential direction with the heat source and precisely matching the radial layering with the processing depth. This ensures the effective improvement of temperature uniformity and effectively suppresses the concentration of internal stress. By coupling multiple parameters of the thermophysical properties of the raw materials and the dynamic parameters of the process, the accuracy of temperature control and the response speed are improved, which ensures the consistency of mass production of products. Furthermore, the process switching adaptation unit realizes the seamless switching between cutting and planing in both directions without the need for manual parameter adjustment, which is suitable for continuous high-precision production. In addition, a coupling model of temperature distribution with roundness error and surface roughness is established to realize the active prediction and temperature control correction of processing accuracy, further ensuring processing accuracy and improving production safety and economy.

[0046] (2) The present invention uses an abnormal early warning and emergency handling module to monitor and warn of temperature deviation, temperature gradient, raw material characteristics and process parameters in real time, and uses an emergency temperature control strategy for cooling to avoid the expansion of defects and equipment damage, effectively reducing production risks. Attached Figure Description

[0047] Figure 1 This is a system architecture block diagram of the present invention. Detailed Implementation

[0048] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0049] Please see Figure 1 This invention provides a precision temperature control system for the production of ring-shaped quartz cavities using remote plasma sources. The system includes a multi-dimensional sensing module, a dual-dimensional temperature control execution module, a multi-objective optimization feedback control module, a central control module, a calibration module, and an anomaly warning and emergency handling module. The dual-dimensional temperature control execution module is communicatively connected to the multi-dimensional sensing module. The multi-objective optimization feedback control module is communicatively connected to both the multi-dimensional sensing module and the dual-dimensional temperature control execution module. The central control module is communicatively connected to the multi-dimensional sensing module, the dual-dimensional temperature control execution module, and the multi-objective optimization closed-loop control module via an EtherCAT bus. The central control module is also communicatively connected to the anomaly warning and emergency handling module and the calibration module.

[0050] In an exemplary embodiment, the multi-dimensional sensing module is used to collect multi-dimensional sensing data. The multi-dimensional sensing data includes thermophysical property parameters of quartz raw materials, dynamic parameters of cutting / gowing processes, local heat source distribution data of the processing area, and real-time temperature data. Specifically, the thermophysical property parameters of quartz raw materials include the thermal conductivity and coefficient of linear expansion of quartz raw materials; the dynamic parameters of cutting / gowing processes include cutting speed, cutting depth, gowing gas flow rate, and gowing flame temperature; and the local heat source distribution data of the processing area includes the three-dimensional coordinates of the heat source location and temperature gradient data.

[0051] In an exemplary embodiment, the dual-dimensional temperature control execution module dynamically adjusts the temperature control range based on local heat source distribution data of the processing area, and performs real-time tracking of independent temperature control zones and heat sources through a mechanical drive mechanism. Specifically, the dual-dimensional temperature control execution module includes a heat source-following circumferential temperature control unit and a layered-depth matching radial temperature control unit. The heat source-following circumferential temperature control unit is used to control several circumferentially distributed independent temperature control zones to move along an annular guide rail. The number of independent temperature control zones is set to 8-16. The movement of each independent temperature control zone is driven by a stepper motor, and it dynamically follows the heat source based on the three-dimensional coordinates of the heat source position in the local heat source distribution data of the processing area. Each independent temperature control zone is equipped with a pulsed infrared heating tube and an adaptive cooling channel. An adjustable nozzle is installed at the outlet of the cooling channel and is installed close to the heat source to facilitate cooling.

[0052] The layered-depth matching radial temperature control unit is used to divide the independent temperature control zone into several layers of equal thickness along the radial direction of the quartz cavity. The number of temperature control layers is set to 4-8 layers. The temperature control parameters of each layer are linearly correlated with the cutting depth / burning thickness. A temperature sensor is embedded in each layer to collect real-time temperature data. The linear correlation formula is as follows:

[0053] ;

[0054] In the formula, For local target temperature, As the reference temperature, For the current processing depth, Let be the correlation coefficient, and .

[0055] To further explain, the power regulation of the pulse infrared heating tube is achieved through a PWM pulse width modulation circuit, and the power regulation signal is generated by a compensation command; the flow regulation signal of the adaptive cooling channel is also generated by a compensation command; the drive signal of the stepper motor is provided by the central control module, and the motor speed is corrected by a PID algorithm to reduce the heat source following error. The input data of the PID algorithm is the difference between the three-dimensional coordinates of the heat source position in the local heat source distribution data and the current position coordinates of the independent temperature control zone.

[0056] In an exemplary embodiment, the multi-objective optimization feedback control module calculates the temperature compensation amount based on multi-dimensional sensing data using a multi-parameter coupling algorithm, and outputs a compensation command to the dual-dimensional temperature control execution module. Specifically, the multi-objective optimization feedback control module includes a multi-parameter coupling deviation calculation unit and a compensation command generation unit. The multi-parameter coupling deviation calculation unit is used to calculate the temperature compensation amount, and the formula for calculating the temperature compensation amount is:

[0057] ;

[0058] In the formula, This is the temperature compensation amount. The global reference target temperature, For real-time temperature data, All are PID coefficients, self-tuned using the Ziegler-Nichols method. These are all raw material characteristic compensation coefficients, calibrated using standard samples. These are all process parameter correction coefficients. This is the flame temperature correction factor. This is the roundness error feedback coefficient. All were determined through orthogonal experiments. Thermal conductivity, Standard thermal conductivity The coefficient of linear expansion is 1 / 3. The standard coefficient of linear expansion. For cutting speed, As the reference cutting speed, This refers to the flow rate of the fire-gouging gas. The reference flame gouging gas flow rate, The flame temperature of the fire-gouging process. The reference flame temperature for gouging. For roundness error, This refers to the target roundness error.

[0059] As a detailed explanation, a laser diameter gauge is installed 100mm above the processing table, and four measuring points are evenly arranged along the circumference of the annular cavity. Roundness data, i.e., roundness error, is collected every 20ms and transmitted to the multi-parameter coupling deviation calculation unit via Ethernet.

[0060] Furthermore, the compensation command generation unit is used to convert the temperature compensation amount into a PWM duty cycle adjustment signal for the pulse infrared heating tube and a flow rate adjustment signal for the adaptive cooling channel to form a compensation command. At the same time, it calculates the temperature gradient through real-time temperature data of adjacent temperature control zones. When the temperature gradient exceeds 0.5℃ / mm, it triggers the coordinated adjustment command of adjacent zones to avoid thermal stress concentration.

[0061] In an exemplary embodiment, the central control module outputs temperature control commands to the dual-dimensional temperature control execution module based on multi-dimensional sensing data and temperature compensation. Specifically, the central control module includes a process switching adaptation unit and an intelligent command scheduling unit. The process switching adaptation model unit is used to pre-store a temperature control parameter threshold library for cutting / gowing processes, and dynamically calibrates the reference heating / cooling rate when a process switching signal is received. The formula for calculating the dynamic calibration reference heating / cooling rate is:

[0062] ;

[0063] In the formula, For the calibrated baseline heating / cooling rate, As the initial reference rate, This represents the maximum permissible roundness error.

[0064] The intelligent instruction scheduling unit divides the independent temperature control zones into concentrated heat source areas and non-heat source areas based on temperature gradient data. When the temperature gradient is higher than 0.3℃ / mm, the independent temperature zone is determined to be a concentrated heat source area; when the temperature gradient is lower than 0.3℃ / mm, the independent temperature zone is determined to be a non-heat source area. After determining the priority weights for the concentrated heat source areas and non-heat source areas respectively, the CPU computing resources and communication bandwidth are allocated through a priority scheduling algorithm to ensure that the concentrated heat source areas execute temperature control instructions first. The temperature control instructions include compensation instructions and adaptive temperature control instructions.

[0065] In one exemplary embodiment, the correction module is used to construct a roundness error coupling model and a surface roughness coupling model;

[0066] The roundness error coupling model includes:

[0067] ;

[0068] In the formula, The radius of the annular quartz cavity is given. This is the roundness correction factor. The coefficient representing the influence of thermal conductivity. For the first Real-time temperature data for each independent temperature zone. The average real-time temperature data for all independent temperature zones. Number of independent temperature zones;

[0069] The surface roughness coupling model includes:

[0070] ;

[0071] In the formula, For surface roughness, As the reference roughness, This is the temperature influence coefficient. This is the coefficient affecting cutting speed.

[0072] In an exemplary embodiment, the abnormal warning and emergency handling module is connected in communication to monitor the thermophysical properties of the quartz raw material, the dynamic parameters of the cutting / gowing process, the temperature deviation and temperature gradient data in real time. When the corresponding threshold is exceeded, an early warning is issued and an emergency temperature control strategy is triggered: the central control module controls the annular quartz cavity to suspend processing and uniformly cools the annular quartz cavity.

[0073] In an exemplary embodiment, the specific steps of applying the above-described precision temperature control system for producing a remote plasma source annular quartz cavity include:

[0074] S1. Select the raw material sample of the annular quartz cavity to be processed. Use a quartz raw material sample with a size of Φ12.7mm×2mm to test the thermal conductivity. Use a NETZSCH LFA 467 laser flare instrument to test the thermal conductivity of the raw material in the temperature range of 25℃-1200℃. Use a quartz raw material sample with a size of Φ5mm×50mm to test the coefficient of linear expansion. Use a NETZSCH DIL 402Expedis pusher dilatometer to test the coefficient of linear expansion in the range of 25℃-1200℃ at a heating rate of 5℃ / min.

[0075] S2. Eight FLIRA655sc infrared thermal imaging sensors are arranged in a ring array, ensuring that each sensor has a 30° field of view, fully covering the ring-shaped machining area. An OMRON E6B2-CWZ6C incremental encoder is installed in the spindle box, a KEYENCE GT2-H12K displacement sensor is installed in the tool holder, a K-type thermocouple is fixed 50mm from the outlet of the flame cutter gun, and a Bronkhorst F-201CV gas mass flow controller is installed in the gas pipeline. Twelve independent temperature control zones are arranged along the ring guide rail. Each zone is equipped with a STEHNEN SST86D3005 stepper motor. A Heraeus NIR 750 pulse infrared heating tube and a quartz glass adaptive cooling channel with an inner diameter of 4mm are installed in each zone. The nozzle orifice diameter of the cooling channel outlet is adjusted to 1mm, and the preset distance from the machining surface is ≤5mm. Six layers of Omega PT1000-1 / 3B platinum resistance temperature sensors are installed radially along the quartz cavity. High-temperature resistant PTFE cables are used for the leads to ensure stable and effective data transmission.

[0076] S3. Select the cutting or gouging process according to the processing requirements, and call the corresponding basic parameters from the temperature control parameter threshold library of the central control module: the preset target temperature for the cutting process is 500-600℃, and the heating rate is 8-12℃ / min; the preset target temperature for the gouging process is 700-800℃, and the heating rate is 12-18℃ / min; then enter the benchmark value of the process dynamic parameters, and preset the PID coefficient, raw material characteristic compensation coefficient, process parameter correction coefficient and roundness error feedback coefficient in the multi-objective optimization feedback control module;

[0077] S4. The multi-dimensional sensing module collects multi-dimensional sensing data: thermophysical property parameters of quartz raw materials, dynamic parameters of cutting / gowing processes, local heat source distribution data of the processing area, and real-time temperature data. The central control module receives the multi-dimensional sensing data and performs initial calibration through the process switching adaptation model unit. Refer to the above-mentioned calculation formula for the dynamic calibration reference heating / cooling rate to obtain the calibrated reference heating / cooling rate.

[0078] S5. Start the cutting / gowing processing equipment. The processing parameters are updated every 20ms. The real-time position and temperature gradient of the cutting friction point / gowing burning point are captured and transmitted to the central control module. The intelligent command scheduling unit allocates priorities based on the temperature gradient data: the priority weight of the heat source concentrated area is set to 3, and the priority weight of the non-heat source area is set to 1. The corresponding independent temperature control zone is driven to follow the heat source to ensure that the cooling channel outlet is always ≤5mm away from the heat source position.

[0079] S7. Real-time temperature data of each independent temperature control zone is collected at a frequency of 500Hz and transmitted to the multi-objective optimization feedback control module via RS485 bus to calculate the temperature compensation amount. The calculation formula is the same as the temperature compensation amount calculation formula above. The compensation command generation unit converts the temperature compensation amount into a PWM duty cycle adjustment signal and a flow rate adjustment signal, which are used to control the power change of the infrared heating tube and the nitrogen flow rate change of the cooling channel, respectively. At the same time, the temperature gradient between adjacent zones is calculated. If it exceeds 0.5℃ / mm, a coordinated adjustment command is triggered to balance the temperature of the area.

[0080] The roundness error was collected every 20ms at four measurement points along the circumference of the annular cavity using a Keyence LK-G80 laser diameter measuring instrument and transmitted to the multi-objective optimization feedback control module as input data for multi-parameter coupling calculation.

[0081] S8. Call the roundness error coupling model and surface roughness coupling model to predict the machining accuracy. If the predicted roundness error is ≥0.05mm or the surface roughness is ≥0.2μm, the correction module sends a correction command to the central control module. The central control module adjusts the power of the infrared heating tube and the flow rate of the cooling channel in the corresponding independent temperature control zone to correct the roundness error to ≤0.02mm and control the surface roughness to ≤0.1μm.

[0082] S9. When the processing requirement switches from cutting to planing or vice versa, the processing equipment sends a process switching signal to the central control module. The process switching adaptation model unit of the central control module calls the temperature control parameter threshold library of the corresponding process and performs calibration of the reference heating / cooling rate based on the current multi-dimensional sensing data. For details, please refer to the above calculation formula for the dynamic calibration reference heating / cooling rate. The central control module outputs an adaptive temperature control command to the dual-dimensional temperature control execution module to adjust the target temperature, heating rate and cooling flow reference values ​​to achieve seamless connection between cutting and planing.

[0083] S10, the anomaly warning and emergency handling module monitors the thermophysical properties of quartz raw materials, dynamic parameters of cutting / gowing processes, temperature deviation, and temperature gradient data in real time. An alarm will be triggered when any of the following conditions occur:

[0084] Temperature deviation is calculated by the difference between real-time temperature data and global benchmark target temperature. An early warning is issued when the deviation exceeds ±1℃ and lasts for ≥0.5s.

[0085] The temperature gradient is based on temperature gradient data in the local heat source distribution data, and an early warning is issued when it exceeds 1℃ / mm.

[0086] Among the thermophysical properties of quartz raw materials, when the thermal conductivity is ∉ [1.3, 1.7] W / (m・K) or the coefficient of linear expansion is ∉ [0.5×10⁻⁶] W / (m・K), the following conditions apply. -6 1.2×10 -6 A warning will be issued when the temperature reaches 100℃.

[0087] In the dynamic parameters of cutting / gowing process, an early warning is issued when the cutting speed is ∉[1,5]m / min, the gowing gas flow rate is ∉[10,30]L / min, or the gowing flame temperature is ∉[800,1200]℃.

[0088] Simultaneously, an emergency temperature control strategy is automatically executed: the central control module suspends processing, starts a uniform cooling program with a cooling rate of ≤2℃ / min, and stores the current process parameters and temperature control data in the local database to facilitate fault prediction and repair.

[0089] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A precision temperature control system for the production of a remote plasma source annular quartz cavity, characterized in that, include: A multi-dimensional sensing module is used to collect multi-dimensional sensing data, including thermophysical property parameters of quartz raw materials, dynamic parameters of cutting / gowing processes, local heat source distribution data of the processing area, and real-time temperature data. A dual-dimensional temperature control execution module is communicatively connected to a multi-dimensional sensing module. The dual-dimensional temperature control execution module dynamically adjusts the temperature control range based on local heat source distribution data of the processing area, and performs independent temperature control partitioning and real-time tracking of heat sources through a mechanical drive mechanism. A multi-objective optimization feedback control module is communicatively connected to a multi-dimensional sensing module and a dual-dimensional temperature control execution module. The multi-objective optimization feedback control module calculates the temperature compensation amount based on the multi-dimensional sensing data using a multi-parameter coupling algorithm and outputs the compensation command to the dual-dimensional temperature control execution module. The central control module is connected to the multi-dimensional sensing module, the dual-dimensional temperature control execution module, and the multi-objective optimization closed-loop control module via the EtherCAT bus. The central control module outputs temperature control commands to the dual-dimensional temperature control execution module based on the multi-dimensional sensing data and temperature compensation.

2. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 1, characterized in that: The thermophysical properties of the quartz raw material include its thermal conductivity and coefficient of linear expansion. The dynamic parameters of the cutting / gowing process include cutting speed, cutting depth, gowing gas flow rate, and gowing flame temperature; The local heat source distribution data of the processing area includes the three-dimensional coordinates of the heat source location and temperature gradient data.

3. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 2, characterized in that The dual-dimensional temperature control execution module includes a heat source following circumferential temperature control unit and a layered-depth matching radial temperature control unit. The heat source following circumferential temperature control unit is used to control several independent temperature control zones distributed in a circle to move along the ring guide rail, and dynamically follow the heat source based on the three-dimensional coordinates of the heat source position in the local heat source distribution data of the processing area; each independent temperature control zone is equipped with a pulse infrared heating tube and an adaptive cooling channel, and an adjustable nozzle is installed at the outlet of the cooling channel and is installed close to the heat source. The layered-depth matching radial temperature control unit is used to divide the independent temperature control zone into several layers of equal thickness along the radial direction of the quartz cavity. The temperature control parameters of each layer are linearly correlated with the cutting depth / gowing and burning thickness. A temperature sensor is embedded in each layer to collect real-time temperature data. The linear correlation formula is as follows: ； wherein is a local target temperature, is a reference temperature, is a current machining depth, is a correlation coefficient, and .

4. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 3, characterized in that The multi-objective optimization feedback control module includes a multi-parameter coupling deviation calculation unit and a compensation instruction generation unit; The multi-parameter coupling deviation calculation unit is used to calculate the temperature compensation amount, and the calculation formula is: ； In the formula, is a temperature compensation amount, is a global reference target temperature, is real-time temperature data, are all PID coefficients, are all raw material characteristic compensation coefficients, are all process parameter correction coefficients, is a flame temperature correction coefficient, is a roundness error feedback coefficient, is a thermal conductivity, is a standard thermal conductivity, is a linear expansion coefficient, is a standard linear expansion coefficient, is a cutting speed, is a reference cutting speed, is a fire gas flow, is a reference fire gas flow, is a fire gas flame temperature, is a reference fire gas flame temperature, is a roundness error, is a target roundness error; The compensation command generation unit is used to convert the temperature compensation amount into a PWM duty cycle adjustment signal for the pulse infrared heating tube and a flow rate adjustment signal for the adaptive cooling channel to form a compensation command. At the same time, it calculates the temperature gradient through the real-time temperature data of adjacent temperature control zones. When the temperature gradient exceeds 0.5℃ / mm, it triggers a coordinated adjustment command for the adjacent zones.

5. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 4, characterized in that The central control module includes a process switching adaptation unit and an intelligent instruction scheduling unit. The process switching adaptive model unit is used for pre-storing a threshold library of temperature control parameters of the cutting / burning process, and dynamically calibrating a reference temperature rising / falling rate when a process switching signal is received; The intelligent instruction scheduling unit divides the independent temperature control partition into a heat source concentrated area and a non-heat source area based on temperature gradient data, and after priority weight is determined respectively, allocates CPU operation resources and communication bandwidth to execute temperature control instructions preferentially through a priority scheduling algorithm.

6. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 5, characterized in that The calculation formula of the dynamically calibrated reference temperature rising / falling rate is: ； In the formula, is the calibrated reference temperature increase / decrease rate, is the initial reference rate, is the maximum allowable roundness error.

7. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 5, characterized in that, The division logic of dividing the independent temperature control partition into the heat source concentrated area and the non-heat source area comprises: When the temperature gradient is higher than 0.3℃ / mm, the independent temperature area is judged as the heat source concentrated area; When the temperature gradient is lower than 0.3℃ / mm, the independent temperature area is judged as the non-heat source area.

8. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 5, characterized in that, The central control module is in communication connection with a correction module, and the correction module is used for constructing a roundness error coupling model and a surface roughness coupling model; The roundness error coupling model comprises: ； wherein, is the radius of the annular quartz cavity, is the roundness correction factor, is the thermal conductivity influence factor, is the real-time temperature data of the th independent temperature zone, is the average real-time temperature data of all independent temperature zones, is the number of independent temperature zones; The surface roughness coupling model comprises: ； wherein R is the surface roughness, Rref is the reference roughness, T is the temperature influence coefficient, V is the cutting speed influence coefficient.

9. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 8, characterized in that The central control module is also in communication connection with an abnormality early warning and emergency handling module, and the abnormality early warning and emergency handling module is in communication connection for real-time monitoring of quartz raw material thermophysical property parameters, cutting / burning process dynamic parameters, temperature deviation and temperature gradient data, and when corresponding threshold values are exceeded, an early warning is issued, and an emergency temperature control strategy is triggered.

10. The precision temperature control system for the production of ring-shaped quartz cavities for remote plasma sources according to claim 9, characterized in that, The emergency temperature control strategy is that the central control module controls the ring-shaped quartz cavity to suspend processing, and uniformly cools the ring-shaped quartz cavity.

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