High vacuum furnace control method and system based on multi-station linkage

Abstract

The application provides a high-vacuum furnace control method and system based on multi-station linkage, relates to the technical field of automatic control, and comprises the following steps: deploying a linkage temperature controller, performing optimization iteration of multi-station power coordination and judgment of power regulation mode; establishing a radiation heat exchange network matrix, calculating real-time radiation heat exchange power, positioning energy-rich stations and energy-deficient stations, and outputting target power instructions; driving synchronous monitoring states according to the target power instructions, performing heating stage judgment based on a three-element criterion, and automatically entering the holding stage and issuing a shutdown prompt if the heating is completed. The application solves the technical problem that the heating efficiency of a high-vacuum furnace is affected because each heating unit of the multi-station high-vacuum furnace only adopts simple interlocking logic in the prior art, realizes optimal decoupling distribution of multi-station power under the premise of ensuring power supply safety and three-phase balance, and improves the heating efficiency of the high-vacuum furnace.

Description

Technical Field

[0001] This application relates to the field of automation control technology, specifically to a high vacuum furnace control method and system based on multi-station linkage. Background Technology

[0002] Existing multi-station high-vacuum furnaces typically use simple interlocking logic for power coordination among their heating units. This can be achieved through hard-wiring or PLC programming to implement power exclusion or fixed priority limits between stations, preventing the total current from exceeding the power supply line capacity. However, this coordination method fails to dynamically allocate power based on real-time temperature deviations, heating rates, and current margins of each station. It does not treat the power supply topology composed of transformers, cables, and heaters as a dynamic resistance network, nor does it perform multi-station power collaborative optimization with the total current of each phase as a real-time constraint. Furthermore, it fails to quantify the impact of dominant radiative heat transfer in the high-vacuum environment on the station's energy balance. Instead, it relies solely on a single temperature threshold to trigger phase switching, resulting in power allocation remaining in a suboptimal, conservative state focused on safety. Ultimately, this reduces the heating efficiency and equipment capacity of the high-vacuum furnace.

[0003] In summary, the existing technology has a technical problem: because the heating units of a multi-station high vacuum furnace only use simple interlocking logic, it is impossible to achieve optimal power distribution, which further affects the heating efficiency of the high vacuum furnace. Summary of the Invention

[0004] The purpose of this application is to provide a high vacuum furnace control method and system based on multi-station linkage, in order to solve the technical problem in the prior art that the heating units of the multi-station high vacuum furnace only use simple interlocking logic, which makes it impossible to achieve optimal power distribution and further affects the heating efficiency of the high vacuum furnace.

[0005] To achieve the above objectives, this application provides a high vacuum furnace control method and system based on multi-station linkage.

[0006] Firstly, this application provides a high-vacuum furnace control method based on multi-station linkage. This method is implemented through a high-vacuum furnace control system based on multi-station linkage. The method includes: treating the high-vacuum furnace's station linkage control architecture as a resistance network; deploying a linkage temperature controller; uploading heating requirements and using the total current of each phase as a real-time constraint; performing optimization iteration and power adjustment mode judgment for multi-station power coordination; and solving for the optimal power command for each station's heater. Based on the internal architecture of the high-vacuum furnace, a radiation heat transfer network matrix is ​​established; the real-time radiation heat transfer power based on the optimal power command is calculated; by locating energy-rich and energy-deficient stations, the power is allocated through gradient descent adjustment before outputting the target power command; a ternary criterion is deployed using the vacuum degree change rate, the maximum temperature difference between multiple stations, and the heating rate of each station as detection indicators; the status is monitored synchronously with the target power command; heating stage judgment is performed based on the ternary criterion; and if heating is complete, the furnace automatically enters the heat preservation stage and issues a shutdown prompt.

[0007] Optionally, the power supply transformer, cable, solid-state relay and heaters at each station are equivalent to a resistance network, wherein the real-time resistance of each heater changes dynamically with temperature; based on the resistance network, optimization objectives and constraints are introduced, and the underlying logic is to use multi-station optimization solution and power adjustment mode switching based on phase control or zero-crossing power adjustment, and to deploy a linkage temperature controller.

[0008] Optionally, the optimization objective includes a first objective and a second objective, wherein the first objective is to minimize the sum of squares of the deviations between the heater temperature of each station and the set value, and the second objective is to minimize the three-phase current imbalance; wherein the constraints include: the power of each station heater does not exceed the rated value, the total current of each phase does not exceed the line current carrying capacity, and the solid-state relay conduction angle or duty cycle is continuously adjustable.

[0009] Optionally, the heaters at each workstation are grouped according to the power supply phase sequence, and the total current of each phase is calculated in real time. The heating demand is uploaded, and the total current of each phase is used as a real-time constraint condition and input to the linkage temperature controller. Multi-workstation optimization solution and power adjustment mode judgment are performed, and the optimal power command of each workstation heater is output. Among them, phase-controlled power adjustment uses the conduction angle as the adjustment parameter, and zero-crossing power adjustment uses the duty cycle sequence as the adjustment parameter. The power allocation is determined by checking whether the total current of each phase is close to the current carrying capacity limit, and iterative optimization under power adaptive coordination under three-phase balance is used. The power adjustment mode is judged according to the power allocation to determine the target power adjustment mode. The optimal power command of each workstation heater is generated according to the power allocation and the target power adjustment mode.

[0010] Optionally, for a high-vacuum furnace, the angular coefficients between the surfaces of each workstation and between the workstation and the furnace wall are calculated. A radiative heat transfer network matrix is ​​established by combining the workstation geometry, relative position, and the relationship between surface emissivity and temperature. Using the optimal power command as the initial value, the radiative heat transfer power between each workstation is calculated in real time within the radiative heat transfer network matrix. Based on the radiative heat transfer power, the optimal power command is optimized and adjusted to determine the target power command.

[0011] Optionally, based on the radiative heat transfer power, energy-rich workstations and energy-deficient workstations are located, wherein the energy-rich workstation is one where the received radiative power is greater than its own heat generation power, and the energy-deficient workstation is one where the received radiative power is less than its own heat dissipation power; and the workstation setting value is satisfied as a priori constraint, and the power allocation optimization based on gradient descent is performed on the energy-rich workstations and energy-deficient workstations to obtain the target power command.

[0012] Optionally, detection indicators are defined, including vacuum degree change rate, maximum temperature difference between multiple stations, and heating rate of each station; a ternary criterion is deployed based on the detection indicators to construct a heating endpoint determiner; the high vacuum furnace is synchronously monitored by the multi-station joint drive of the target power command, converted into a detection indicator vector, and input into the heating endpoint determiner; when heating is determined to be complete, the furnace automatically enters the heat preservation stage and issues a furnace shutdown prompt.

[0013] Optionally, vacuum stability is used as the first criterion, temperature difference convergence is used as the second criterion, and the inflection point of heating rate is used as the third criterion. A weighted score is obtained by ternary judgment and weighted calculation. When the weighted score exceeds a preset threshold, it is determined that heating is complete.

[0014] Optionally, the Joule heat of the cable and solid-state relay is collected in real time to predict the temperature rise of the power supply line; if the temperature rise of the power supply line exceeds the temperature rise threshold, a power adjustment command is generated, wherein the power adjustment command includes reducing the power limit of the corresponding workstation or triggering rotating heating; the harmonic distortion rate of each phase current is monitored in real time to generate an operating condition alarm command, wherein if the distortion rate suddenly increases, it is determined to be a solid-state relay failure or a short circuit to ground of the workstation heater.

[0015] Secondly, this application also provides a high vacuum furnace control system based on multi-station linkage, used to execute the high vacuum furnace control method based on multi-station linkage as described in the first aspect. The high vacuum furnace control system based on multi-station linkage includes: a power adjustment mode judgment module, used to convert the station linkage control architecture of the high vacuum furnace into a resistance network, deploy a linkage temperature controller, upload heating requirements and use the total current of each phase as a real-time constraint, execute optimization iteration and power adjustment mode judgment for multi-station power coordination, and solve for the optimal power command of each station heater; a gradient descent adjustment module, used to establish a radiation heat transfer network matrix according to the internal architecture of the high vacuum furnace, calculate the real-time radiation heat transfer power based on the optimal power command, locate energy-rich stations and energy-deficient stations, distribute power through gradient descent adjustment, and output the target power command; and a ternary criterion heating stage judgment module, used to deploy a ternary criterion with the vacuum degree change rate, the maximum temperature difference of multiple stations, and the heating rate of each station as detection indicators, synchronously monitor the status driven by the target power command, execute heating stage judgment based on the ternary criterion, and automatically switch to the heat preservation stage and issue a furnace shutdown prompt if heating is completed.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages: By equating the station linkage control architecture of the high vacuum furnace to a resistance network, a linkage temperature controller is deployed. Heating requirements are uploaded, and the total current of each phase is used as a real-time constraint. Optimization iteration and power adjustment mode judgment are performed for multi-station power coordination to solve for the optimal power command of each station heater. A radiation heat transfer network matrix is ​​established based on the internal architecture of the high vacuum furnace. The real-time radiation heat transfer power based on the optimal power command is calculated. By locating energy-rich and energy-deficient stations, the power distribution is adjusted through gradient descent before outputting the target power command. A ternary criterion is deployed using the vacuum degree change rate, the maximum temperature difference between multiple stations, and the heating rate of each station as detection indicators. The status is monitored synchronously with the target power command, and heating stage judgment is performed based on the ternary criterion. If heating is completed, the furnace automatically enters the heat preservation stage and issues a shutdown prompt. In other words, by equating the workstation linkage architecture to a dynamic resistance network and using the total current of each phase as a hard constraint to perform multi-workstation power coordination, and combining the radiation heat transfer network matrix to locate energy-rich / deficient workstations and perform gradient descent correction, and using the ternary criterion to determine the heating endpoint, the optimal decoupled allocation of multi-workstation power is achieved under the premise of ensuring power supply safety and three-phase balance, effectively suppressing the thermal field imbalance caused by radiation interference and improving the heating efficiency of the high vacuum furnace.

[0017] The above description is merely an overview of the technical solution of this application. To better understand the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 This is a flowchart illustrating the high vacuum furnace control method based on multi-station linkage proposed in this application.

[0020] Figure 2 This is a schematic diagram of the high vacuum furnace control system based on multi-station linkage in this application.

[0021] Figure labeling: 11 Power adjustment mode judgment module, 12 Gradient descent adjustment module, 13 Three-element criterion heating stage judgment module. Detailed Implementation

[0022] This application provides a control method and system for a high-vacuum furnace based on multi-station linkage, solving the technical problem in existing technologies where the heating units of multi-station high-vacuum furnaces only use simple interlocking logic, resulting in the inability to achieve optimal power distribution and further affecting the heating efficiency of the high-vacuum furnace. By equating the station linkage architecture to a dynamic resistance network and using the total current of each phase as a hard constraint to perform multi-station power coordination, combined with the radiation heat transfer network matrix to locate energy-rich / deficient stations and perform gradient descent correction, and using a ternary criterion to determine the heating endpoint, the optimal decoupled power distribution of the multi-station furnace is achieved under the premise of ensuring power supply safety and three-phase balance. This effectively suppresses the thermal field imbalance caused by radiation interference and improves the heating efficiency of the high-vacuum furnace.

[0023] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.

[0024] Example 1, please refer to the appendix. Figure 1 This application provides a high vacuum furnace control method based on multi-station linkage, wherein the high vacuum furnace control method based on multi-station linkage is applied to a high vacuum furnace control system based on multi-station linkage, and the high vacuum furnace control method based on multi-station linkage specifically includes the following steps: The station linkage control architecture of the high vacuum furnace is equivalent to a resistance network. A linkage temperature controller is deployed, the heating demand is uploaded, and the total current of each phase is used as a real-time constraint. The optimization iteration of multi-station power coordination and the power adjustment mode judgment are performed to solve the optimal power command of the heater at each station.

[0025] Furthermore, this application also includes the following steps: equating the power supply transformer, cable, solid-state relay and heaters at each workstation to a resistance network, wherein the real-time resistance of each heater at each workstation changes dynamically with temperature; based on the resistance network, introducing optimization objectives and constraints, using multi-workstation optimization solutions and switching between power regulation modes based on phase control or zero-crossing power regulation as the underlying logic, and deploying a linkage temperature controller.

[0026] Furthermore, this application also includes the following steps: the optimization objective includes a first objective and a second objective, wherein the first objective is to minimize the sum of squares of the deviations between the heater temperature of each station and the set value, and the second objective is to minimize the three-phase current imbalance; wherein the constraints include: the power of the heater of each station does not exceed the rated value, the total current of each phase does not exceed the line current carrying capacity, and the solid-state relay conduction angle or duty cycle is continuously adjustable.

[0027] Specifically, the short-circuit impedance parameters of the power supply transformer, the resistance values ​​of each cable segment, and the on-state resistance of the solid-state relay are obtained. The temperature of each heater at each station is collected in real time, and the hot-state resistance of each heater at the current temperature is calculated based on the known resistance-temperature relationship curve of the heater material. According to the actual wiring method, such as connecting stations one, two, and three to phases A, B, and C respectively, and station four to phase A, a resistance network is constructed, with the transformer output as the voltage source, each heater as a variable load, and the intermediate line resistors connected in series. The resistance network can calculate the response value of the total current in each phase when a certain voltage or power is applied to each heater.

[0028] The first optimization objective is defined as the sum of the squares of the differences between the real-time temperature of all workstations and their respective process set temperatures; the smaller this value, the better. The second optimization objective is defined as the three-phase current imbalance, which is calculated by taking the root mean square error between the current of each phase and the average current. For example, calculate the total current of phases A, B, and C, find the average value of the three phases, and then take the square root of the sum of the squares of the differences between the current of each phase and the average value. The smaller this value, the more balanced the three phases are.

[0029] Three hard constraints are specified: the power of each heater at each station cannot exceed its rated power; the sum of the currents of all heaters on each phase cannot exceed the allowable current carrying capacity of that phase line; and the conduction angle of the solid-state relay can only be adjusted between 0° and 180° in phase-controlled mode, and the duty cycle can only be adjusted between 0 and 1 in zero-crossing mode.

[0030] The linkage temperature controller reads the current temperature from the thermocouples at each station, the target temperature and heating rate requirements for each station from the process recipe, and the real-time value of the total current for each phase from the current transformer. Based on the temperature deviation, an initial power allocation scheme is generated using a proportional relationship, such as pre-allocating the total available power according to the proportion of the temperature deviation at each station to the total deviation.

[0031] Substituting the initial power allocation into the resistive network model, the total current in each phase under the current heater resistance is calculated. The system checks for violations of constraints. If no violations are found, the values ​​of the two optimization objectives are calculated, and the power of each station is fine-tuned, such as decreasing the power of one station while increasing the power of another. The current and objective function are then recalculated. This process is iterated repeatedly, using constraint optimization algorithms such as gradient projection, until a power allocation scheme is found that achieves a predetermined trade-off balance between the two objectives. For example, the dual objectives can be transformed into a single objective using weighting coefficients, and all constraints are satisfied. This iterative process runs continuously at millisecond intervals, tracking temperature changes in real time.

[0032] Based on the optimized target power values ​​for each workstation, the appropriate power regulation mode is determined. If a fast power regulation response is required and harmonic requirements are not stringent, phase-controlled power regulation mode is selected, and the target power is converted into a corresponding conduction angle command. If reducing grid harmonic pollution is required and load inertia is significant, zero-crossing power regulation mode is selected, and the target power is converted into a duty cycle command. The linkage temperature controller is a software algorithm module built based on a resistor network model, optimization objectives, and constraints. It receives the setpoint and measured temperature values ​​for each workstation, solves for the optimal power allocation command in real time, and automatically determines whether to use phase-controlled power regulation or zero-crossing power regulation mode. These commands are then sent to each solid-state relay to drive the heaters to operate at the optimal power.

[0033] The three-phase current imbalance is explicitly incorporated into the optimization objective. The controller can actively adjust the load of each phase while meeting the temperature requirements, avoiding the situation in traditional solutions where one phase reaches its current carrying capacity limit too early while other phases still have margin. This improves the overall utilization rate of the power supply system and extends the service life of transformers and cables.

[0034] Furthermore, this application also includes the following steps: grouping the heaters at each workstation according to the power supply phase sequence and calculating the real-time total current of each phase; uploading the heating demand, using the total current of each phase as a real-time constraint condition, inputting it into the linkage temperature controller, performing multi-workstation optimization solution and power adjustment mode judgment, and outputting the optimal power command for each workstation heater, wherein phase-controlled power adjustment uses the conduction angle as the adjustment parameter, and zero-crossing power adjustment uses the duty cycle sequence as the adjustment parameter; wherein, by verifying whether the total current of each phase is close to the current carrying capacity limit, iterative optimization under power adaptive coordination under three-phase balance is used to determine the power allocation; power adjustment mode judgment is performed based on the power allocation to determine the target power adjustment mode; and the optimal power command for each workstation heater is generated based on the power allocation and the target power adjustment mode.

[0035] Specifically, based on the electrical wiring diagram, the power supply phase connected to each heater at each workstation is recorded in the configuration table of the control system. All heaters in the multi-station high-vacuum furnace are divided into three groups according to their actual power supply phase (phase A, phase B, or phase C). The total current value of phases A, B, and C is collected in real time using current transformers installed at the main input line of each phase. Simultaneously, the current operating current of each heater within each group can be accumulated for redundancy verification. The calculated total current value for each phase is used as the numerical basis for the real-time constraints. The total current for each phase is the algebraic sum of the operating currents of all heaters within the same phase sequence group.

[0036] The linkage temperature controller obtains the current power demand value from the temperature control loop of each station. It is usually calculated proportionally from the temperature deviation of that station and expressed as the percentage or absolute value of the power that the station wants to obtain relative to its rated power. Each station independently uploads its own heating demand.

[0037] The controller reads the current total current value of each phase and compares it with the preset upper limit of the current carrying capacity of that phase. It calculates the current margin of each phase by subtracting the current value from the upper limit.

[0038] An initial power allocation is generated based on the heating requirements of each workstation. The total current per phase is calculated based on the real-time resistance of each heater. The current in each phase is checked to ensure it does not exceed the current carrying capacity limit. If any phase exceeds the limit, the power allocation for one or more workstations within that phase group is reduced, and the power of workstations with remaining capacity in other phase groups is increased accordingly, while maintaining the total power requirement as close as possible. This process is repeated until all phase currents are within limits and the power allocation for each workstation is as close as possible to its original requirement. During the iteration, a three-phase balance objective is also considered. When the current margin of a phase is significantly smaller than that of other phases, the power of workstations within that phase group is proactively reduced, even if the demand for that workstation is high. The operator is alerted, or the phase sequence of subsequent workstations is automatically adjusted to avoid long-term imbalance. After multiple iterations, when all phase currents do not exceed the upper limit and the three-phase current differences are minimized, the iteration converges, resulting in a power allocation scheme that satisfies all current constraints and maintains three-phase balance.

[0039] For each workstation's target power value, the controller independently determines the appropriate power adjustment mode. The judgment rules can be set based on the process stage: for example, if a workstation requires a low power value, such as less than 30% of the rated power, phase-controlled power adjustment is selected, utilizing the continuous adjustment capability of the conduction angle to achieve smooth output and avoid temperature fluctuations caused by zero-crossing power adjustment at low power; if a workstation requires a high and stable power value, such as during the heat preservation stage, greater than or equal to 70% of the rated power, or if the process is in the heat preservation stage and has strict requirements for grid harmonics, zero-crossing power adjustment is selected to reduce harmonic pollution; for medium power ranges, a hysteresis range is set to prevent frequent switching. Phase-controlled power adjustment is used in the initial stage of heating to achieve a rapid response, while switching to zero-crossing power adjustment in the later stages of heating or the constant temperature stage.

[0040] For workstations determined to be subject to phase-controlled power regulation, the controller converts the allocated target power value into the conduction angle of the solid-state relays. The conversion process is based on the heater's cold-state resistance, the hot-state resistance at the current temperature, and the effective value of the power supply voltage. The specific conduction angle value is deduced using the cosine law between the effective value of the phase-controlled power regulation output voltage and the conduction angle. For workstations determined to be subject to zero-crossing power regulation, the controller converts the target power value into a duty cycle, which is the target power divided by the rated power, and generates a cycle sequence accordingly. For example, setting a fixed time period, such as 200 AC cycles corresponding to 4 seconds, a duty cycle of 0.6 means that 120 cycles are conducted and 80 cycles are turned off within that cycle. The sequence can be evenly distributed to reduce current surges. The optimal power command is a set of control parameters generated after optimization iterations and power regulation mode judgment, and sent to each solid-state relay. For workstations using phase-controlled power regulation, the command is the specific conduction angle value; for workstations using zero-crossing power regulation, the command is the specific duty cycle sequence.

[0041] The above steps are repeated periodically to track temperature and power supply current changes at each workstation in real time, dynamically update power commands, and ensure that the system always operates within electrical safety boundaries and that power distribution is close to optimal.

[0042] For example, assume the test equipment is configured as a 4-station high-vacuum furnace, with stations one through four. The phase sequence is station one (phase A), station two (phase B), station three (phase C), and station four (phase A). Each station heater has a room temperature resistance of 18.5Ω and a resistance of 20.95Ω at 800℃, a rated voltage of 220V, a rated power of 2.6kW, and a rated current of 11.8A. It is a three-phase four-wire system, with a maximum current carrying capacity of 200A per phase. Assume the current carrying capacity is artificially reduced to create a stressful scenario: the maximum current carrying capacity of phase A is set at 20A (because phase A powers two stations), and the maximum current carrying capacity of phases B and C is set at 12A (each powers one station). Current operating conditions are as follows: Station 1 (Phase A) temperature 500℃, setpoint 950℃, heating demand 100% (full power 2.6kW, current 11.8A); Station 2 (Phase B) temperature 850℃, setpoint 900℃, heating demand 30% (power 0.78kW, current 3.5A); Station 3 (Phase C) temperature 860℃, setpoint 880℃, heating demand 20% (power 0.52kW, current 2.4A); Station 4 (Phase A) temperature 600℃, setpoint 920℃, heating demand 90% (power 2.34kW, current 10.6A). Phase A includes the current from Station 1 (11.8A) + Station 4 (10.6A), so the total current is 22.4A; the total current of Phase B is 3.5A; and the total current of Phase C is 2.4A. The maximum current carrying capacity of Phase A is known to be 20A, and the current 22.4A exceeds this limit; Phases B and C are within their limits. The demand for each workstation is 100%, 30%, 20%, and 90%. The total current of each phase is used as a constraint input to the controller: Phase A current 22.4A > 20A, violating the constraint. The controller initiates iteration. The initial allocation is directly applied to the full demand, but overcurrent is detected in Phase A. Therefore, the power of the workstations within Phase A is reduced. Priority is given to reducing the power of workstation four (90%) or workstation one (100%), which have higher demand, while attempting to transfer some power to phases B and C. However, the demand for workstations two and three on phases B and C is very low, and their rated power is limited, making significant increases impossible. Therefore, the overall power of Phase A must be reduced. After iteration, the following allocation is obtained: the power of workstation one is reduced to 2.1kW (current 9.5A), the power of workstation four is reduced to 1.8kW (current 8.2A), and the total current of Phase A is reduced to 17.7A (below 20A). Workstation two remains at 0.78kW (3.5A), and workstation three remains at 0.52kW (2.4A). At this point, the phase currents are: A = 17.7A, B = 3.5A, and C = 2.4A. The three-phase imbalance is significant, but the current constraints are met. The final power allocation is determined as follows: Station 1 2.1kW, Station 2 0.78kW, Station 3 0.52kW, and Station 4 1.8kW. Station 1's target power of 2.1kW represents 81% of its rated power (2.6kW), which is considered high power and is in the middle of the heating phase, not yet approaching the set value.The controller determines that zero-crossing power adjustment is used to reduce harmonics because the power is high and the load inertia is large, with a duty cycle of 0.81. Station 2 has a target power of 0.78kW (30%), which is low power, so phase-controlled power adjustment is used to achieve continuous and smooth output, avoiding temperature fluctuations caused by zero-crossing power adjustment at low power. Station 3 has a target power of 0.52kW (20%), also using phase-controlled power adjustment. Station 4 has a target power of 1.8kW (69%), which is medium to high power, and the heating demand is reduced from 90%, so zero-crossing power adjustment is used. For Station 1 (zero-crossing power adjustment), the duty cycle sequence is 162 cycles on and 38 cycles off out of every 200 AC cycles. For Station 2 (phase-controlled power adjustment), the calculated conduction angle is approximately 115°. Station 3 is similar, with a conduction angle of approximately 130°. The duty cycle sequence for Station 4 is 138 cycles on and 62 cycles off. The instructions were sent to each solid-state relay driver module via the fieldbus, and the heaters operated accordingly. After 10 seconds, the temperature at each station changed, with station one rising to 510℃. The demand remained high, but the current in phase A changed slightly due to a minor increase in resistance. The controller recalculated and gradually adjusted the power. Ultimately, all stations reached their set values ​​within the specified time, and no phase current exceeded its current-carrying capacity for an extended period.

[0043] By verifying the relationship between the total current of each phase and the upper limit of the current carrying capacity in real time, and actively adjusting the power distribution during optimization iterations, it is ensured that no line overload will occur under any operating conditions. Adaptive and coordinated iterative optimization under three-phase balance is adopted. When the current margin of a certain phase is small while other phases still have room, some power demand is transferred to the lightly loaded phase, making the three-phase current tend to be balanced. This reduces the additional losses and vibrations caused by transformer imbalance and avoids forcing the limitation of the entire unit power due to a certain phase reaching its upper limit prematurely.

[0044] A radiation heat transfer network matrix is ​​established based on the internal architecture of the high vacuum furnace. The real-time radiation heat transfer power is calculated based on the optimal power command. The target power command is output after the power distribution is adjusted by locating the energy surplus station and the energy deficiency station through gradient descent.

[0045] Furthermore, this application also includes the following steps: for a high vacuum furnace, calculate the angular coefficients between the surfaces of each workstation and between the workstation and the furnace wall; and establish a radiative heat transfer network matrix by combining the workstation geometry, relative position, and surface emissivity with temperature; using the optimal power command as the initial value, calculate the radiative heat transfer power between each workstation in real time within the radiative heat transfer network matrix; and optimize and adjust the optimal power command based on the radiative heat transfer power to determine the target power command.

[0046] Furthermore, this application also includes the following steps: based on the radiative heat transfer power, locate energy-rich workstations and energy-deficient workstations, wherein the energy-rich workstation is one where the received radiative power is greater than its own heat generation power, and the energy-deficient workstation is one where the received radiative power is less than its own heat dissipation power; and perform gradient descent-based power allocation optimization on the energy-rich workstations and energy-deficient workstations to obtain the target power command, satisfying the workstation setting value as a priori constraint.

[0047] Specifically, based on the actual internal structure of the high-vacuum furnace, the geometry, dimensions, and relative positions of all exposed surfaces at each workstation are measured and recorded. Simultaneously, the emissivity of the furnace wall inner surface and the surface materials at each workstation are measured or consulted from material handbooks to obtain the functional relationship between temperature and the emissivity of these materials. For surfaces that cannot be directly measured, standard values ​​can be used, such as an emissivity of 0.2 for polished stainless steel and 0.8 for oxidized stainless steel.

[0048] For each surface within the furnace cavity, including the workstation surface and the furnace wall surface, calculate its angle coefficient to every other surface. Since the angle coefficient depends only on geometry, it is calculated once during initialization and stored as an angle coefficient matrix F, where F(i,j) represents the proportion of radiant energy emitted from surface i that falls onto surface j. Note that the self-view coefficient F(i,i) must be 0 (convex surface) or non-zero (concave surface), and energy conservation must be maintained, meaning the sum of the angle coefficients in each row is 1. The angle coefficient, also known as the viewing angle coefficient or shape coefficient, represents the proportion of radiant energy emitted from one surface that directly falls onto another surface. It depends only on the geometry, relative position, and spacing of the two surfaces and is independent of surface temperature and material. The angle coefficient ranges from 0 to 1 and satisfies additivity and interchangeability.

[0049] Treating each surface as a node, its net radiative heat transfer is described by the surface radiative heat flux equation. For each surface i, the net radiative heat flux Q... rad ,i=(Eb,i-Ji) / ((1-εi) / (εi·Ai)), where Eb,i is the blackbody radiative force, proportional to the fourth power of temperature, Ji is the effective radiation, the total radiant energy leaving the surface, Ai is the surface area, and εi is the emissivity. Simultaneously, the effective radiation between all surfaces satisfies a linear relationship: Ji=Eb,i-((1-εi) / εi)·Q rad i, and Q radThe equations are given by: i = Σ(F(i,j)·(Ji-Jj)). These equations are then combined and written in matrix form: A·J = B, where J is the effective radiation vector of each surface, and B consists of blackbody radiation force, etc. The size of the radiation heat transfer network matrix is ​​equal to the number of surfaces participating in radiation. Since emissivity and blackbody radiation force vary with temperature, this matrix is ​​nonlinear and needs to be solved again in each control cycle. The radiation heat transfer network matrix treats all surfaces participating in radiation heat transfer within the furnace as nodes and the radiative heat flow between surfaces as branches, and is a matrix of linear or nonlinear equations established based on parameters such as angle coefficient, surface emissivity, and temperature. By solving this matrix, the net absorbed or emitted radiation power of each surface can be obtained.

[0050] The electric heating power of each workstation is taken as a known heat source term, and the current actual temperature and furnace wall temperature of each workstation are measured or estimated. Based on the actual temperature and furnace wall temperature, the blackbody radiation force of each surface is calculated. The radiation heat transfer network matrix is ​​solved to obtain the net radiation heat transfer power Q of each surface. rad For a workstation surface, this value represents the net heat power gained or lost from radiation at that workstation. The optimal power command is the electrical heating power value of the heaters at each workstation, which satisfies electrical constraints. Radiative heat transfer power is the net radiative heat exchanged between each workstation surface and all other surfaces, calculated in the radiative heat transfer network matrix. A positive value indicates that the workstation net absorbs radiative energy, and a negative value indicates that the workstation net releases radiative energy.

[0051] For each workstation, its net radiative heat transfer power is compared with its own electric heating power. If the net radiative heat transfer power is greater than its own electric heating power, it means that the heat obtained by the workstation from radiation exceeds its own electric heating capacity. Even if the electric heating is reduced, the radiative heat can maintain the temperature, so it is defined as an energy-sufficient workstation. If the net radiative heat transfer power is less than its own heat dissipation power, that is, the net radiation is negative and the absolute value is large, it is defined as an energy-deficient workstation.

[0052] Establish an objective function, such as the sum of squares of the differences between the actual temperature and the set temperature at all workstations. The optimization variable is the electric heating power of each workstation, with the initial value being the optimal power command. In each iteration, the radiative heat transfer network is re-solved based on the current electric heating power and temperature to obtain a new net radiative power, which is then used to predict temperature changes. The gradient of the objective function with respect to each electric heating power is calculated. The direction of gradient descent is the direction that minimizes the objective function the most, i.e., adjusting the electric heating power along the negative gradient direction: new electric heating power = electric heating power - learning rate × gradient. During the adjustment process, for energy-rich workstations, gradient descent automatically reduces their electric heating power because reducing power helps reduce temperature deviation; for energy-deficient workstations, gradient descent automatically increases their electric heating power. Simultaneously, prior constraints must be enforced; no adjustment should cause the workstation to fail to reach the set temperature in steady state. The iterations are repeated until the objective function converges, i.e., the deviation between the temperature and the set value at each workstation is within the allowable range, or the maximum number of iterations is reached. Finally, a set of corrected electric heating power values, i.e., the target power command, is obtained.

[0053] The target power command is sent to the solid-state relay drive circuits of each workstation, replacing the optimal power command from the previous step. The electric heating power of energy-rich workstations is reduced, utilizing radiant energy received from the surrounding environment to maintain temperature; the electric heating power of energy-deficient workstations is increased to compensate for their radiative heat loss. This not only makes the actual temperature more uniform across all workstations but may also reduce overall energy consumption by decreasing ineffective electric heating in energy-rich workstations. Because temperature changes over time, this process needs to be repeated every few seconds to tens of seconds to track changes in operating conditions and continuously optimize power allocation.

[0054] Based on the aforementioned power scheme, further utilization of in-furnace thermal crosstalk is achieved by adjusting the heating power distribution to reduce total heating energy consumption and ensure coordination between the inside and outside of the furnace.

[0055] The system deploys a ternary criterion based on the vacuum degree change rate, the maximum temperature difference between multiple workstations, and the heating rate of each workstation. It synchronously monitors the status as the target power command drives the heating stage judgment based on the ternary criterion. If the heating is completed, it automatically enters the heat preservation stage and issues a furnace shutdown prompt.

[0056] Furthermore, this application also includes the following steps: defining detection indicators, wherein the detection indicators include vacuum degree change rate, maximum temperature difference of multiple stations and heating rate of each station; deploying a ternary criterion according to the detection indicators to construct a heating endpoint determiner; synchronously monitoring the status of the high vacuum furnace with the multi-station joint drive of the target power command, converting it into a detection indicator vector, inputting it into the heating endpoint determiner, and automatically switching to the heat preservation stage and issuing a furnace shutdown prompt when heating is determined to be complete.

[0057] Furthermore, this application also includes the following steps: using vacuum stability as the first criterion, temperature difference convergence as the second criterion, and the inflection point of heating rate as the third criterion, a weighted score is obtained through ternary judgment and weighted calculation; when the weighted score exceeds a preset threshold, it is determined that heating is complete.

[0058] Specifically, the detection indicators are defined, including the vacuum degree change rate, the maximum temperature difference across multiple stations, and the heating rate at each station. Using a fixed sampling period, such as once per second, the pressure value of the vacuum gauge is read. The vacuum degree change rate is obtained using the difference method: the current value minus the previous value divided by the time interval. Note that in the initial stage of heating, the vacuum degree may increase due to gas release, resulting in a positive change rate; after stabilization, the change rate approaches zero or is slightly negative. The current temperature of all stations is read, the maximum and minimum values ​​are identified, and the difference is calculated to obtain the maximum temperature difference across multiple stations. For each station, a first-order difference method similar to that used for vacuum degree is employed to calculate the heating rate per minute or per second. The heating rate is higher in the initial stage of heating and gradually decreases as it approaches the set value.

[0059] Based on specific process requirements and empirical data, weights are assigned to the three indicators. For example, the weight of vacuum degree change rate is set to 0.5, the weight of maximum temperature difference at multiple stations is set to 0.3, and the weight of heating rate is set to 0.2. Ideal completion values ​​and initial values ​​are set for each indicator, and real-time measured values ​​are mapped to a score range of 0 to 1. Then, a weighted total score is calculated: Total Score = Weight 1 × Normalized Vacuum Degree Change Rate Score + Weight 2 × Normalized Temperature Difference Score + Weight 3 × Normalized Heating Rate Score. A threshold is set, such as 0.85; heating is considered complete when the total score exceeds the threshold. The weighted scoring logic is encapsulated into an independent program module, namely the heating endpoint determiner. The input is a three-dimensional vector, including vacuum degree change rate, maximum temperature difference, and heating rate at each station; the output is a Boolean value, where 0 indicates incomplete and 1 indicates complete. To prevent misjudgment due to instantaneous disturbances, debouncing logic is added to the determiner, requiring multiple consecutive tests, such as 3 times, before the total score exceeds the threshold to output a completion signal.

[0060] Solid-state relays drive the heaters according to the target power commands for each station. During this process, the control system reads the real-time temperature and furnace vacuum level of all stations at fixed control cycles, calculates the current vacuum level change rate, the maximum temperature difference across multiple stations, and the heating rate of each station, and combines these three values ​​into a detection index vector. After each status monitoring cycle, the current three-dimensional vector is sent to the heating endpoint determiner. The determiner performs a weighted calculation and compares it with a threshold, outputting an intermediate result indicating whether heating is complete or incomplete. If the output indicates incomplete heating, the monitoring continues for the next cycle.

[0061] If heating is complete, the system automatically switches to the heat preservation stage and issues a shutdown prompt. The control mode is switched from heating mode to heat preservation mode, ceasing control based on the heating rate curve and instead maintaining the temperature setpoint at the target heat preservation temperature. The PID parameters are switched to those for heat preservation. The interactive interface displays that heating is complete and heat preservation has automatically begun, accompanied by audible and visual alerts. The current time is recorded as the heating end time. After transitioning to heat preservation, temperature monitoring continues, and PID control maintains the temperature at each station near the setpoint until the heat preservation time is reached or manual intervention by the operator is required. After heat preservation, the system automatically proceeds to the next step, such as cooling, vacuum breaking, and unloading. If heating has been prolonged, exceeding the preset maximum heating time, and heating completion is not detected, an alarm is issued, and the system is forced to switch to heat preservation or stop heating altogether to prevent equipment damage.

[0062] For the vacuum stability criterion, an ideal upper limit and an allowable upper limit for the vacuum change rate are defined, such as an ideal upper limit of 0.01 Pa / s and an allowable upper limit of 0.1 Pa / s. When the change rate is below 0.01 Pa / s, the criterion scores 1; when it is above 0.1 Pa / s, the score is 0; linear interpolation is used in between. For the temperature difference convergence criterion, a maximum allowable temperature difference and an ideal temperature difference are defined. When the actual maximum temperature difference is less than or equal to the ideal temperature difference, 1 point is awarded; when it is greater than the maximum temperature difference, 0 points are awarded; linear interpolation is used in between. For the heating rate inflection point criterion, the real-time trend of the heating rate at each station is calculated. When the rate decreases and its absolute value is below a threshold (e.g., 0.5℃ / min), and the duration exceeds a certain time (e.g., 30 seconds), an inflection point is identified, and the criterion scores 1; otherwise, the score is 0.

[0063] Based on the degree of importance the process places on the three dimensions, weights are assigned, such as vacuum stability (0.5 weight), temperature difference convergence (0.3 weight), and heating rate inflection point (0.2 weight), with the sum of the weights being 1. A threshold for the weighted score is also set, such as 0.85.

[0064] In each control cycle, the current vacuum degree change rate, the current maximum temperature difference across multiple workstations, and the current heating rate of each workstation are calculated. An inflection point is then determined. These three measured values ​​are normalized and then weighted and summed to calculate a weighted score: Weighted Score = 0.5 * Vacuum Degree Change Rate + 0.3 * Current Maximum Temperature Difference Across Multiple Workstations + 0.2 * Current Heating Rate of Each Workstation. The calculated weighted score is compared to a preset threshold. If the score is greater than the threshold, heating is considered complete. Alternatively, if the weighted score does not exceed the threshold, each of the three criteria is checked to ensure it meets its independent satisfaction standard. The number of satisfied criteria is counted. If the number of satisfied criteria is greater than or equal to 2, heating is considered complete; otherwise, heating is considered incomplete.

[0065] If heating is determined to be complete, the process stage indicator is switched from heating up to heat preservation, the set temperature of each station controller is switched to the heat preservation target temperature, a furnace shutdown prompt is issued, and the heating end time is recorded. If heating is determined to be incomplete, monitoring continues in a loop, heating control is maintained, and power commands are continuously updated.

[0066] By refining the judgment logic of the three criteria, two complementary judgment mechanisms—weighted scoring and multi-condition satisfaction—are introduced to avoid missed judgments due to temporary sensor failure or unreasonable weight settings. The three criteria originate from different physical domains, making the probability of simultaneous misjudgment extremely low. After heating, the system immediately switches to heat preservation, avoiding overheating or energy waste caused by manual delays or fixed-time control.

[0067] Furthermore, this application also includes the following steps: real-time acquisition of Joule heat of the cable and solid-state relay to predict the temperature rise of the power supply line; if the temperature rise of the power supply line exceeds the temperature rise threshold, generating a power adjustment command, wherein the power adjustment command includes reducing the power upper limit of the corresponding workstation or triggering rotating heating; real-time monitoring of the harmonic distortion rate of each phase current to generate an operating condition alarm command, wherein if the distortion rate suddenly increases, it is determined to be a solid-state relay fault or a short circuit to ground of the workstation heater.

[0068] Specifically, the resistance value of the cable is obtained and calculated based on the cable length, cross-sectional area, and resistivity of copper. Similarly, the on-state resistance and thermal resistance of the heatsink are found in the solid-state relay's datasheet. The ambient temperature inside the cabinet is measured. Using these parameters, a simple thermal network model is constructed, similar to a circuit composed of resistors and capacitors: heat generation power corresponds to current, thermal resistance to resistance, thermal capacitance to capacitance, and temperature to voltage. The current temperature rise is calculated in real time, and the temperature rise trend for the next few seconds to tens of seconds is predicted. In each control cycle, such as every 0.5 seconds, the total current of each phase and the current of each solid-state relay branch are measured using a current transformer. Simultaneously, the actual current is collected by temperature sensors mounted on the cable surface and the solid-state relay heatsink. The ambient temperature is also measured by sensors inside the cabinet. Based on the real-time current and known resistance, the current heat generation power is calculated. Heat generation power equals the square of the current multiplied by the resistance. This heat generation power is input into the thermal model and corrected by combining the difference between the current measured temperature and the model's predicted temperature to obtain a more accurate estimate of the current temperature rise. Assuming the current remains constant for the next few seconds, the temperature rise at future moments is calculated using the thermal model. The basic principle of prediction is that the future temperature rise equals the current temperature rise plus (heating power minus heat dissipation power) divided by the heat capacity. The heat dissipation power depends on the difference between the current temperature and the ambient temperature, as well as the thermal resistance.

[0069] The predicted temperature rise is compared with a preset temperature rise threshold. If the predicted temperature rise exceeds the threshold, an appropriate power regulation command is selected based on the specific object and severity of the overheating. If overheating of a certain phase of cable is predicted, the maximum allowable power of all stations on that phase is reduced, and the previous optimization controller is immediately updated to ensure that subsequent power allocation does not exceed this new upper limit. For example, the power limit of a station is temporarily reduced by 20% from the rated value. If multiple stations are connected to a phase, and their power cannot be reduced due to process requirements, a time-division multiplexing method is used to divide these stations into time slices for intermittent heating. For example, station one heats at full power for 10 seconds and then is turned off, while station two heats at full power for 10 seconds, and so on. Although the instantaneous current remains unchanged, the average current decreases, and Joule heating is reduced. The rotation cycle and duty cycle are dynamically adjusted by the controller based on the temperature rise margin.

[0070] A current transformer is installed at the input of each phase, and the current signal is connected to the harmonic analysis module to acquire the current waveform at a high sampling rate. The effective value of the fundamental current and the effective values ​​of each harmonic current are calculated by Fourier transform. The total harmonic distortion rate is equal to the square root of the sum of the squares of all harmonic effective values, divided by the effective value of the fundamental current, and then multiplied by 100%.

[0071] Set the normal operating range for harmonic distortion rate. For zero-crossing power regulation mode, the distortion rate is typically below 5%; for phase-controlled power regulation mode, the distortion rate is generally between 10% and 30%. Calculate the rate of change of distortion rate in real time, i.e., the change per second. If the distortion rate rises above a set threshold (e.g., 20 percentage points) within a very short period, or if the absolute value of the distortion rate exceeds the safety limit (e.g., 50%), it is considered abnormal.

[0072] Based on the abnormal characteristics, the fault type is determined. If the distortion rate suddenly increases while the effective value of the current in that phase does not decrease significantly or even slightly increases, and the power command does not increase, the solid-state relay may be broken down. If the distortion rate suddenly increases but the effective value of the current drops to zero or is very small, the solid-state relay may be open-circuited or have poor contact. An alarm command is generated, specific fault information is displayed on the human-machine interface, an audible and visual alarm is issued, and the system determines whether to automatically shut down based on the severity of the fault, such as immediately cutting off the main power supply or forcibly turning off all solid-state relays.

[0073] By monitoring Joule heating in real time to predict temperature rise and current harmonic distortion rate, proactive safety protection and fault diagnosis of power supply lines and solid-state relays are achieved. Power reduction or alternating heating measures are taken in advance to keep the temperature within the allowable range, avoiding sudden shutdowns and production interruptions, and improving equipment availability.

[0074] In summary, the high vacuum furnace control method based on multi-station linkage provided in this application has the following technical effects: by equating the station linkage control architecture of the high vacuum furnace to a resistance network, deploying a linkage temperature controller, uploading heating requirements and using the total current of each phase as a real-time constraint, performing optimization iteration and power adjustment mode judgment for multi-station power coordination, and solving for the optimal power command of each station heater; establishing a radiation heat transfer network matrix based on the internal architecture of the high vacuum furnace, calculating the real-time radiation heat transfer power based on the optimal power command, locating energy-rich and energy-deficient stations, adjusting the power distribution through gradient descent, and outputting the target power command; deploying a ternary criterion with vacuum degree change rate, maximum temperature difference of multiple stations, and heating rate of each station as detection indicators, synchronously monitoring the status driven by the target power command, performing heating stage judgment based on the ternary criterion, and automatically switching to the heat preservation stage and issuing a furnace shutdown prompt if heating is completed. In other words, by equating the workstation linkage architecture to a dynamic resistance network and using the total current of each phase as a hard constraint to perform multi-workstation power coordination, and combining the radiation heat transfer network matrix to locate energy-rich / deficient workstations and perform gradient descent correction, and using the ternary criterion to determine the heating endpoint, the optimal decoupled allocation of multi-workstation power is achieved under the premise of ensuring power supply safety and three-phase balance, effectively suppressing the thermal field imbalance caused by radiation interference and improving the heating efficiency of the high vacuum furnace.

[0075] Example 2: Based on the same inventive concept as the high vacuum furnace control method based on multi-station linkage in Example 1, this application also provides a high vacuum furnace control system based on multi-station linkage. Please refer to the appendix. Figure 2 The high vacuum furnace control system based on multi-station linkage includes: a power adjustment mode judgment module 11, which is used to convert the station linkage control architecture of the high vacuum furnace into a resistance network, deploy a linkage temperature controller, upload heating requirements and use the total current of each phase as a real-time constraint, perform optimization iteration and power adjustment mode judgment for multi-station power coordination, and solve for the optimal power command of each station heater; a gradient descent adjustment module 12, which is used to establish a radiation heat transfer network matrix according to the internal architecture of the high vacuum furnace, calculate the real-time radiation heat transfer power based on the optimal power command, locate the energy-rich station and the energy-deficient station, and output the target power command after allocating power through gradient descent adjustment; and a ternary criterion heating stage judgment module 13, which is used to deploy a ternary criterion with the vacuum degree change rate, the maximum temperature difference of multiple stations and the heating rate of each station as detection indicators, synchronously monitor the status with the target power command, perform heating stage judgment based on the ternary criterion, and automatically switch to the heat preservation stage and issue a furnace shutdown prompt if heating is completed.

[0076] Furthermore, the power adjustment mode judgment module 11 in the high vacuum furnace control system based on multi-station linkage is also used to: equate the power supply transformer, cable, solid-state relay and each station heater to a resistance network, wherein the real-time resistance of each station heater changes dynamically with temperature; based on the resistance network, introduce optimization objectives and constraints, and use multi-station optimization solution and power adjustment mode switching based on phase control power adjustment or zero-crossing power adjustment as the underlying logic to deploy a linkage temperature controller.

[0077] Furthermore, the power adjustment mode judgment module 11 in the high vacuum furnace control system based on multi-station linkage is also used for: the optimization objective includes a first objective and a second objective, wherein the first objective is to minimize the sum of squares of the deviations between the temperature of each station heater and the set value, and the second objective is to minimize the three-phase current imbalance; wherein the constraints include: the power of each station heater does not exceed the rated value, the total current of each phase does not exceed the line current carrying capacity, and the solid-state relay conduction angle or duty cycle is continuously adjustable.

[0078] Furthermore, the power adjustment mode judgment module 11 in the high vacuum furnace control system based on multi-station linkage is also used for: grouping the heaters of each station according to the power supply phase sequence, calculating the real-time total current of each phase; uploading the heating demand, using the total current of each phase as a real-time constraint condition, inputting it into the linkage temperature controller, executing multi-station optimization solution and power adjustment mode judgment, and outputting the optimal power command for each station heater, wherein phase-controlled power adjustment uses the conduction angle as the adjustment parameter, and zero-crossing power adjustment uses the duty cycle sequence as the adjustment parameter; wherein, by verifying whether the total current of each phase is close to the upper limit of the current carrying capacity, iterative optimization under power adaptive coordination under three-phase balance is used to determine the power allocation; power adjustment mode judgment is performed based on the power allocation to determine the target power adjustment mode; and the optimal power command for each station heater is generated based on the power allocation and the target power adjustment mode.

[0079] Furthermore, the gradient descent adjustment module 12 in the high vacuum furnace control system based on multi-station linkage is also used for: calculating the angular coefficients between the surfaces of each station and between the station and the furnace wall for the high vacuum furnace; establishing a radiative heat transfer network matrix by combining the station geometry, relative position, and surface emissivity with temperature; calculating the radiative heat transfer power between each station in real time in the radiative heat transfer network matrix using the optimal power command as the initial value; and optimizing and adjusting the optimal power command according to the radiative heat transfer power to determine the target power command.

[0080] Furthermore, the gradient descent adjustment module 12 in the high vacuum furnace control system based on multi-station linkage is also used to: locate energy-rich stations and energy-deficient stations according to the radiation heat transfer power, wherein the energy-rich station is one where the received radiation power is greater than its own heating power, and the energy-deficient station is one where the received radiation power is less than its own heat dissipation power; and optimize the power allocation of the energy-rich station and the energy-deficient station based on gradient descent to obtain the target power command, while satisfying the station setting value as a priori constraint.

[0081] Furthermore, the ternary criterion heating stage judgment module 13 in the multi-station linkage high vacuum furnace control system is also used for: defining detection indicators, wherein the detection indicators include vacuum degree change rate, maximum temperature difference of multiple stations and heating rate of each station; deploying ternary criteria according to the detection indicators to construct a heating endpoint judge; synchronously monitoring the status of the high vacuum furnace with the multi-station joint drive of the target power command, converting it into a detection indicator vector, inputting it into the heating endpoint judge, and automatically switching to the heat preservation stage and issuing a furnace shutdown prompt when heating is determined to be completed.

[0082] Furthermore, the ternary criterion heating stage judgment module 13 in the high vacuum furnace control system based on multi-station linkage is also used to: use vacuum stability as the first criterion, temperature difference convergence as the second criterion, and heating rate inflection point as the third criterion, and obtain a weighted score through ternary judgment and weighted calculation; when the weighted score exceeds a preset threshold, it is determined that heating is complete.

[0083] Furthermore, the ternary criterion heating stage judgment module 13 in the high vacuum furnace control system based on multi-station linkage is also used for: real-time acquisition of Joule heat of cables and solid-state relays to predict the temperature rise of power supply lines; if the temperature rise of the power supply lines exceeds the temperature rise threshold, generating a power adjustment command, wherein the power adjustment command includes reducing the power upper limit of the corresponding station or triggering alternating heating; real-time monitoring of the harmonic distortion rate of each phase current to generate an operating condition alarm command, wherein if the distortion rate suddenly increases, it is determined to be a solid-state relay failure or a short circuit to ground of the station heater.

[0084] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The high vacuum furnace control method and specific examples based on multi-station linkage in the foregoing embodiment one are also applicable to the high vacuum furnace control system based on multi-station linkage in this embodiment. Through the foregoing detailed description of the high vacuum furnace control method based on multi-station linkage, those skilled in the art can clearly understand the high vacuum furnace control system based on multi-station linkage in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0085] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0086] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.

Claims

1. A high-vacuum furnace control method based on multi-station linkage, characterized in that, include: The station linkage control architecture of the high vacuum furnace is equivalent to a resistance network. A linkage temperature controller is deployed, the heating demand is uploaded, and the total current of each phase is used as a real-time constraint. The optimization iteration of multi-station power coordination and the power adjustment mode judgment are performed to solve the optimal power command of each station heater. A radiation heat transfer network matrix is ​​established based on the internal architecture of the high vacuum furnace. The real-time radiation heat transfer power based on the optimal power command is calculated. The target power command is output after the power distribution is adjusted by locating the energy surplus station and the energy shortage station through gradient descent. The three-dimensional criteria are deployed with vacuum degree change rate, maximum temperature difference of multiple stations and heating rate of each station as detection indicators. The status is monitored synchronously with the target power command. The heating stage judgment is performed based on the three-dimensional criteria. If heating is completed, it automatically enters the heat preservation stage and issues a furnace shutdown prompt. Among them, the synchronous monitoring status driven by the target power command, and the execution of the heating stage judgment based on the ternary criterion, include: Define detection indicators, wherein the detection indicators include vacuum degree change rate, maximum temperature difference of multiple stations and heating rate of each station; Based on the aforementioned detection indicators, a ternary criterion is deployed to construct a heating endpoint determiner; The high vacuum furnace is simultaneously monitored by multiple stations in conjunction with the target power command. The status is converted into a detection index vector and input into the heating endpoint judge. When the heating is determined to be complete, the furnace automatically enters the heat preservation stage and issues a furnace shutdown prompt. The input to the heating endpoint determiner includes: Using vacuum stability as the first criterion, temperature difference convergence as the second criterion, and the inflection point of heating rate as the third criterion, a weighted score is obtained through ternary judgment and weighted calculation. When the weighted score exceeds a preset threshold, heating is considered complete.

2. The high vacuum furnace control method based on multi-station linkage as described in claim 1, characterized in that, The station linkage control architecture of the high vacuum furnace is equivalent to a resistance network, and a linkage temperature controller is deployed, including: The power supply transformer, cable, solid-state relay and heaters at each station are equivalent to a resistance network, in which the real-time resistance of each heater changes dynamically with temperature. Based on the aforementioned resistor network, optimization objectives and constraints are introduced. The underlying logic is to use multi-station optimization and power adjustment mode switching based on phase control or zero-crossing power adjustment, and to deploy a linkage temperature controller.

3. The high vacuum furnace control method based on multi-station linkage as described in claim 2, characterized in that, The optimization objective includes a first objective and a second objective, wherein the first objective is to minimize the sum of squares of the deviations between the heater temperature at each workstation and the set value, and the second objective is to minimize the three-phase current imbalance. The constraints include: the power of the heater at each station does not exceed the rated value, the total current of each phase does not exceed the line current carrying capacity, and the solid-state relay conduction angle or duty cycle is continuously adjustable.

4. The high vacuum furnace control method based on multi-station linkage as described in claim 3, characterized in that, Perform multi-station power coordination optimization iteration and power adjustment mode judgment to solve for the optimal power command of the heater at each station, including: Group the heaters at each workstation according to the power supply phase sequence and calculate the total current of each phase in real time; The heating requirement is uploaded, and the total current of each phase is used as a real-time constraint condition. The input is given to the linkage temperature controller, which performs multi-station optimization and power adjustment mode judgment, and outputs the optimal power command for each station heater. Among them, the phase control power adjustment uses the conduction angle as the adjustment parameter, and the zero-crossing power adjustment uses the duty cycle sequence as the adjustment parameter. Among them, the power allocation is determined by checking whether the total current of each phase is close to the upper limit of the current carrying capacity, and by iterative optimization under the power adaptive coordination under the three-phase balance. Based on the power distribution, determine the power adjustment mode and identify the target power adjustment mode; Based on the power allocation and the target power adjustment mode, the optimal power command for each station heater is generated.

5. The high vacuum furnace control method based on multi-station linkage as described in claim 1, characterized in that, Output target power command, including: For high vacuum furnaces, the angular coefficients between the surfaces of each workstation and between the workstation and the furnace wall are calculated. Combined with the workstation geometry, relative position, and the relationship between surface emissivity and temperature, a radiation heat transfer network matrix is ​​established. Using the optimal power command as the initial value, the radiative heat transfer power between each station is calculated in real time in the radiative heat transfer network matrix; Based on the radiative heat transfer power, the optimal power command is optimized and adjusted to determine the target power command.

6. The high vacuum furnace control method based on multi-station linkage as described in claim 5, characterized in that, Optimizing and adjusting the optimal power command includes: Based on the radiative heat transfer power, energy-rich workstations and energy-deficient workstations are located, wherein the energy-rich workstation is one that receives radiative power greater than its own heat generation power, and the energy-deficient workstation is one that receives radiative power less than its own heat dissipation power. By satisfying the workstation setting value as a priori constraint, power allocation optimization based on gradient descent is performed on the energy-rich workstation and the energy-deficient workstation to obtain the target power command.

7. The high vacuum furnace control method based on multi-station linkage as described in claim 1, characterized in that, Following the target power command, it includes: Real-time acquisition of Joule heat from cables and solid-state relays to predict temperature rise in power supply lines; If the temperature rise of the power supply line exceeds the temperature rise threshold, a power adjustment command is generated, wherein the power adjustment command includes reducing the power limit of the corresponding workstation or triggering rotating heating. The system monitors the harmonic distortion rate of each phase current in real time and generates operating condition alarm commands. If the distortion rate suddenly increases, it is determined to be a solid-state relay failure or a short circuit to ground of the station heater.

8. A high-vacuum furnace control system based on multi-station linkage, characterized in that, The step of implementing the high vacuum furnace control method based on multi-station linkage according to any one of claims 1 to 7, wherein the high vacuum furnace control system based on multi-station linkage comprises: The power adjustment mode judgment module is used to convert the station linkage control architecture of the high vacuum furnace into a resistance network, deploy linkage temperature controllers, upload heating requirements and use the total current of each phase as a real-time constraint, perform multi-station power coordination optimization iteration and power adjustment mode judgment, and solve the optimal power command of each station heater. The gradient descent adjustment module is used to establish a radiation heat transfer network matrix based on the internal architecture of the high vacuum furnace, calculate the real-time radiation heat transfer power based on the optimal power command, locate the energy surplus station and the energy deficiency station, and output the target power command after allocating the power through gradient descent adjustment. The ternary criterion heating stage judgment module is used to deploy ternary criteria based on the vacuum degree change rate, the maximum temperature difference of multiple stations and the heating rate of each station. It synchronously monitors the status according to the target power command, performs heating stage judgment based on the ternary criteria, and automatically switches to the heat preservation stage and issues a furnace shutdown prompt if heating is completed.

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