A multi-sensor-based vacuum furnace temperature control method and system

Abstract

The application discloses a vacuum furnace temperature control method and system based on multiple sensors and belongs to the technical field of temperature control. The application takes temperature measurement data with a difference from the average temperature less than a preset matching deviation threshold as calibration temperature data, establishes a thermocouple calibration model based on the calibration temperature data and corresponding calibration voltage data, filters out fluctuation data generated due to equipment transient disturbance or sensor noise, and makes the established thermocouple calibration model more accurately reflect real-time physical characteristics of the thermocouple.

Description

Technical Field

[0001] This invention belongs to the field of temperature control technology, specifically relating to a method and system for controlling the temperature of a vacuum furnace based on multiple sensors. Background Technology

[0002] Vacuum furnaces, as key equipment for precision heat treatment processes, provide a high-vacuum, oxidation-free environment, laying the foundation for processes such as metal sintering, ceramic hot pressing, and composite material molding. Throughout the heat treatment cycle, precise monitoring and control of the furnace temperature are necessary to ensure product quality uniformity and yield.

[0003] However, the temperature control system of existing vacuum furnaces relies on a single or a few thermocouple sensors for temperature measurement, which is a single-point temperature measurement method. Once the thermocouples in critical positions age, drift, or are completely damaged, accurate temperature data cannot be obtained, which will cause the performance of the entire furnace of high-value materials to deteriorate or even be scrapped due to temperature runaway, resulting in economic losses.

[0004] To address the aforementioned issues, this invention proposes a method and system for controlling the temperature of a vacuum furnace based on multiple sensors. Summary of the Invention

[0005] To address the shortcomings of existing technologies, the present invention aims to provide a vacuum furnace temperature control method and system based on multiple sensors, so as to reduce the delay of thermocouple temperature measurement data and perform real-time correction of its matching temperature parameters.

[0006] To achieve the above objectives, the present invention adopts the following technical solution:

[0007] A method for controlling the temperature of a vacuum furnace based on multiple sensors includes the following steps:

[0008] Acquire real-time thermocouple voltage data inside the vacuum furnace;

[0009] Based on a pre-established thermocouple calibration model, the temperature compensation value corresponding to the real-time thermocouple voltage data is determined.

[0010] When the temperature compensation value is determined to be valid by comparing it with the current temperature measurement value at the same time, a temperature deviation signal is generated based on the temperature difference between the temperature compensation value and the current temperature measurement value to adjust the heating equipment of the vacuum furnace.

[0011] The establishment of the thermocouple calibration model includes:

[0012] Acquire temperature measurement data from the temperature sensor and voltage data from the thermocouple inside the vacuum furnace;

[0013] Within a preset statistical period, the calibration temperature data is identified from the temperature measurement data, and the calibration voltage data corresponding to the calibration temperature data in time is also identified.

[0014] A thermocouple calibration model is established based on calibration temperature and calibration voltage data.

[0015] Preferably, identifying calibration temperature data from temperature measurement data within a preset statistical period includes:

[0016] Calculate the average temperature of the temperature measurement data obtained within the preset statistical period;

[0017] In addition, the temperature measurement data whose difference from the average temperature is less than the preset matching deviation threshold is identified as the calibration temperature data.

[0018] Preferably, the method further includes:

[0019] When the temperature compensation value is determined to be invalid, an alarm operation is executed, and the temperature adjustment parameters for adjusting the heating equipment of the vacuum furnace are obtained based on the temperature compensation value and the current temperature measurement value.

[0020] Preferably, obtaining the temperature regulation parameters for adjusting the heating equipment of the vacuum furnace based on the temperature compensation value and the current temperature measurement value includes:

[0021] Calculate the adjustment time based on the temperature difference and the preset temperature adjustment rate;

[0022] Based on the temperature difference and adjustment time, determine the heating power or heating duration, and use the heating power or heating duration as the temperature adjustment parameter.

[0023] Preferably, the method further includes assessing the condition of the thermocouple, specifically including:

[0024] When the temperature change of the thermocouple calibration model, which corresponds to the preset voltage value, exceeds the state judgment threshold within the preset evaluation period, the thermocouple state is determined to be abnormal.

[0025] When the thermocouple is determined to be abnormal, the operation of switching to the preset backup thermocouple or suspending heating is performed.

[0026] Preferably, assessing the condition of the thermocouple further includes:

[0027] Based on historical calibration temperature data, the average aging parameter values ​​characterizing the aging degree of thermocouples are calculated.

[0028] When the difference between the average aging parameter value and the baseline aging value exceeds the allowable deviation of aging, the thermocouple condition is determined to be abnormal.

[0029] A multi-sensor-based vacuum furnace temperature control system includes the following modules:

[0030] The multi-source data acquisition module is used to acquire temperature measurement data from the temperature sensor and voltage data from the thermocouple inside the vacuum furnace.

[0031] The calibration model building module is used to build a thermocouple calibration model based on the temperature measurement data and voltage data obtained by the multi-source data acquisition module.

[0032] The temperature compensation control module is used to respond to the real-time thermocouple voltage data acquired by the multi-source data acquisition module, call the thermocouple calibration model to determine the temperature compensation value, and when the temperature compensation value is determined to be valid, generate a temperature deviation signal for adjusting the heating equipment of the vacuum furnace.

[0033] The thermocouple condition assessment module is used to assess the condition of thermocouples based on the output of the thermocouple calibration model within a preset assessment period, and to generate safety control commands when the thermocouple condition is determined to be abnormal.

[0034] In addition, there is a control execution module, which is used to adjust the heating equipment according to the temperature deviation signal and execute safety control commands.

[0035] Preferably, the thermocouple calibration model is established based on the temperature measurement data and voltage data acquired by the multi-source data acquisition module, including:

[0036] Calculate the average temperature within the temperature measurement data;

[0037] The temperature measurement data whose difference from the average temperature is less than the preset matching deviation threshold is identified as calibration temperature data, and a thermocouple calibration model is established based on the calibration temperature data and the corresponding calibration voltage data.

[0038] Preferably, the temperature compensation control module is further configured as follows:

[0039] When the temperature compensation value is determined to be invalid, an alarm operation is executed, and the temperature regulation parameters of the heating equipment used to adjust the vacuum furnace are obtained.

[0040] Preferably, the thermocouple condition assessment module is further configured as follows:

[0041] Calculate the average aging parameter values ​​that characterize the degree of thermocouple aging;

[0042] When the difference between the average aging parameter value and the baseline aging value exceeds the allowable deviation of aging, the thermocouple condition is determined to be abnormal.

[0043] Beneficial effects

[0044] 1. This invention uses temperature measurement data with a difference from the average temperature less than a preset matching deviation threshold as calibration temperature data. Based on this calibration temperature data and the corresponding calibration voltage data, a thermocouple calibration model is established to filter out fluctuation data caused by instantaneous equipment disturbances or sensor noise, so that the established thermocouple calibration model can more accurately reflect the real-time physical characteristics of the thermocouple.

[0045] 2. In this invention, when the difference between the temperature compensation value and the current temperature measurement value is greater than the validity judgment threshold, the temperature compensation value is determined to be invalid and an alarm operation is executed; the thermocouple status is evaluated based on the temperature change output by the model within a preset evaluation period; when the thermocouple status is determined to be abnormal, the system switches to a preset backup thermocouple or suspends heating, thereby realizing the instant identification of single sensor failures and safe redundancy switching to avoid temperature control errors caused by thermocouple failure. Attached Figure Description

[0046] Figure 1 This is a flowchart of the method of the present invention;

[0047] Figure 2 This is a system module diagram of the present invention. Detailed Implementation

[0048] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely for explaining the invention and are not intended to limit the scope of protection of the invention.

[0049] Example 1

[0050] See Figure 1 This embodiment provides a vacuum furnace temperature control method based on multiple sensors, the specific steps of which are as follows:

[0051] S1. Obtain the temperature measurement data from the temperature sensor inside the vacuum furnace and the voltage data output by the thermocouple inside the vacuum furnace;

[0052] By installing temperature sensors at multiple key temperature measurement points inside the vacuum furnace, real-time temperature measurement data of various points inside the furnace is continuously acquired. These real-time temperature measurement data have the characteristics of high accuracy and high stability; among them, the temperature sensors are preferably high-precision platinum resistance thermometers.

[0053] Simultaneously acquire voltage data from thermocouples physically adjacent to these temperature sensors.

[0054] Thermocouples are used as a key auxiliary and redundant temperature measurement method due to their fast response speed and wide measurement range. Their output voltage data can reflect the changes in thermal intensity in the area in real time, providing basic data for establishing accurate voltage and temperature conversion relationships.

[0055] S2. Within a preset statistical period, calculate the average temperature of the temperature measurement data, and identify the data whose difference from the average temperature is less than the preset matching deviation threshold as calibration temperature data. At the same time, extract the voltage data of the corresponding time as calibration voltage data.

[0056] Set a preset statistical period and a preset matching deviation threshold; acquire a set of temperature measurement data within the preset statistical period; calculate the average temperature of the set of temperature measurement data; identify the data in the set of temperature measurement data whose difference from the average temperature is less than the preset matching deviation threshold as calibration temperature data; identify the voltage data corresponding to the calibration temperature data in time as calibration voltage data.

[0057] Furthermore, to ensure the stability and representativeness of the data used to establish subsequent calibration relationships, the following steps are taken: The acquired temperature measurement data is screened to filter out instantaneous temperature fluctuations caused by factors such as electromagnetic interference, instantaneous opening and closing of the furnace door, or material phase changes. Specifically:

[0058] A preset statistical period is set as the baseline window for data processing. Within this preset statistical period, the following processing is performed on a set of acquired temperature measurement data:

[0059] Calculate the arithmetic mean of all temperature measurement data in the group to obtain the average temperature; set a preset matching deviation threshold, for example, ±2℃ according to specific process requirements; calculate the absolute difference between each data point in the group and the average temperature, and determine whether the difference is less than the preset matching deviation threshold; wherein the matching deviation threshold refers to a preset tolerance value, which is used to determine whether the measurement value is a stable reading by comparing the deviation of a single temperature measurement value with the average temperature value within the period.

[0060] If the difference is less than the preset matching deviation threshold, the data is identified as calibration temperature data and considered a valid reading under stable operating conditions; otherwise, the data is identified as fluctuating data and discarded.

[0061] Identify and extract the voltage data that precisely corresponds to all the identified calibration temperature data on the timestamp, and use it as the calibration voltage data to form a one-to-one valid data pair.

[0062] S3. Based on the calibration temperature data and calibration voltage data, establish a thermocouple calibration model;

[0063] Based on the valid data pairs selected in step S2, namely calibration temperature data and calibration voltage data, a thermocouple calibration model is established to convert the voltage output of the thermocouple into the corresponding temperature value in real time. The core of this thermocouple calibration model is to construct an accurate mathematical mapping, and its establishment process is as follows:

[0064] By using preset mathematical calculation rules, such as polynomial fitting calculation methods, conversion formulas that can describe the nonlinear relationship between voltage and temperature can be generated based on data pairs; or reference data tables containing multiple sets of voltage values ​​and their corresponding temperature values ​​can be generated.

[0065] In practical use, intermediate values ​​can be determined by consulting the table and using linear or spline interpolation methods. The thermocouple calibration model is dynamic and can be updated after each preset statistical period to adapt to the characteristic drift that may occur in thermocouples due to long-term use.

[0066] The calibration relationship is a dynamic mathematical mapping based on the calibration temperature data and calibration voltage data. It is used to convert the voltage output of the thermocouple into the corresponding temperature value, and is specifically expressed as a mathematical formula or reference data table.

[0067] S4. Obtain real-time thermocouple voltage data;

[0068] The real-time thermocouple voltage data is input into the thermocouple calibration model, the predicted temperature is output, and the predicted temperature is determined as the temperature compensation value; the current temperature measurement value of the temperature sensor at the same moment is obtained; the temperature compensation value is compared with the current temperature measurement value, and the correction temperature is generated.

[0069] During the control process, the voltage data of the thermocouple is acquired in real time, i.e., the real-time thermocouple voltage data, and input into the established thermocouple calibration model. The predicted temperature is calculated based on this relationship. The predicted temperature is determined as the temperature compensation value to represent the temperature estimate obtained based on the fast response characteristics of the thermocouple.

[0070] Obtain the temperature sensor reading at exactly the same time point, i.e., the current temperature measurement value; calculate the difference between the temperature compensation value and the current temperature measurement value, and define the difference as the correction value. Correct the current temperature measurement value based on the correction value; the specific correction method is to add the current temperature measurement value and the correction value to obtain the corrected temperature.

[0071] Among them, the temperature calibration combines the rapid response of the thermocouple with the absolute accuracy of the temperature sensor, providing a more reliable and timely feedback value for subsequent control decisions.

[0072] S5. Calculate the temperature difference between the temperature compensation value and the current temperature measurement value, and compare it with the validity judgment threshold.

[0073] Set a validity judgment threshold; determine whether the temperature difference between the temperature compensation value and the current temperature measurement value is less than the validity judgment threshold; if the temperature difference is less than the validity judgment threshold, the temperature compensation value is deemed valid, and a temperature deviation signal is generated based on the temperature difference to adjust the heating equipment of the vacuum furnace; if the temperature difference is not less than the validity judgment threshold, the temperature compensation value is deemed invalid, an alarm operation is executed, and the temperature compensation value and the current temperature measurement value are passed into the evaluation processing flow to obtain the temperature adjustment parameters used to adjust the heating equipment of the vacuum furnace.

[0074] The temperature difference between the temperature compensation value and the current temperature measurement value is calculated and compared with a preset validity judgment threshold to diagnose in real time whether there is a significant deviation between the thermocouple and the temperature sensor.

[0075] The preferred effectiveness threshold is ±3℃.

[0076] If the temperature difference is less than the validity judgment threshold, it indicates that the readings of the two sensors are in good agreement. The temperature compensation value output by the thermocouple calibration model is deemed valid, and this temperature difference can be used as a temperature deviation signal to directly fine-tune the heating equipment of the vacuum furnace to maintain the stability of the furnace temperature.

[0077] If the temperature difference is greater than or equal to the validity judgment threshold, it indicates that there is a significant difference between the two, which means that the thermocouple has drifted, malfunctioned, or there is a local temperature anomaly in the furnace. At this time, the temperature compensation value is determined to be invalid, and an alarm operation is immediately executed to remind the operator. At the same time, the invalid temperature compensation value and the current temperature measurement value are sent to the preset evaluation and processing flow.

[0078] Furthermore, the pre-defined evaluation and processing procedure is as follows:

[0079] Obtain a preset reference temperature adjustment rate that matches the thermal characteristics of the vacuum furnace; calculate the adjustment time required for the furnace temperature to return to the target value based on the difference between the current temperature measurement value and the process target temperature and the reference temperature adjustment rate;

[0080] The specific heating power adjustment or heating duration is determined by combining the difference and the adjustment time, and then output as a temperature regulation parameter to the controller of the heating equipment. This allows for temperature correction based on more reliable temperature sensor readings while ensuring safety.

[0081] The reference temperature adjustment rate refers to a preset parameter that reflects the inherent thermal characteristics of the vacuum furnace, defining the standard rate at which the furnace temperature responds to changes in heating power.

[0082] S6. Within the preset evaluation period, the output temperature change of the preset voltage value is evaluated based on the thermocouple calibration model. When the change exceeds the state judgment threshold, the thermocouple state is determined to be abnormal, and the operation of switching to the backup thermocouple or pausing heating is performed.

[0083] Set a preset evaluation period; within each preset evaluation period, obtain the temperature corresponding to the preset voltage value output by the thermocouple calibration model in two consecutive preset statistical periods; calculate the change in model output temperature in two consecutive preset statistical periods; where the change in output temperature refers to the difference between the two output temperatures obtained after inputting the same preset voltage value into the calibration relationship updated by data from two consecutive statistical periods, also known as the calibration relationship drift, which is used to measure the short-term changes in thermocouple characteristics.

[0084] Set a state judgment threshold; determine whether the model output temperature change exceeds the state judgment threshold; if the model output temperature change exceeds the state judgment threshold, the thermocouple state is determined to be abnormal, and the operation of switching to the preset backup thermocouple or pausing heating is performed; if the model output temperature change does not exceed the state judgment threshold, the thermocouple state is determined to be normal, and the model is calibrated using thermocouples.

[0085] Furthermore, by introducing a condition assessment mechanism, long-term active monitoring of the thermocouple's health status is achieved, specifically:

[0086] Set a preset evaluation cycle, such as once per hour; within each preset evaluation cycle, select a fixed preset voltage value, which corresponds to a common temperature point in the process. Calculate the output temperature corresponding to this preset voltage value using a thermocouple calibration model updated in two consecutive preset statistical periods. The preset voltage value refers to a fixed reference voltage input used within the evaluation cycle to test the consistency of the calibration relationship at different time points.

[0087] Calculate the difference between the two output temperatures and determine the calibration relationship drift; where the calibration relationship drift is the change in the model output temperature, which directly reflects the degree of change of the thermocouple calibration model in two consecutive time periods, and compare it with the preset state judgment threshold.

[0088] If the temperature change output by the model exceeds the state judgment threshold, it indicates that the characteristics of the thermocouple have changed significantly in a short period of time. This is usually a precursor to aging or damage. Therefore, the thermocouple is judged to be in an abnormal state, and the preset emergency plan is executed.

[0089] The emergency response plan includes, but is not limited to: automatically switching to redundant backup thermocouples, suspending heating and issuing a maintenance alarm in the absence of backups;

[0090] If the temperature change output by the model does not exceed the state judgment threshold, the thermocouple state is determined to be normal, and the current thermocouple calibration model continues to be used.

[0091] Furthermore, to achieve a quantitative assessment of the aging trend of thermocouples, the determination process also includes a step of analyzing the degree of thermocouple aging, as follows:

[0092] Arrange multiple sets of historical calibration temperature data in chronological order, calculate the first difference between two adjacent sets of historical calibration temperature data, and determine this first difference as the temperature change, which reflects the rate of temperature change over time.

[0093] Extract two adjacent temperature changes over time and calculate the second difference between these two temperature changes. This second difference is determined as the aging parameter value. Its physical meaning represents the change in the rate of temperature change, that is, the acceleration of temperature change. It is a sensitive indicator for measuring whether the thermocouple response characteristics have deteriorated.

[0094] Multiple aging parameter values ​​are obtained and their average values ​​are calculated to obtain the average aging parameter value, which smooths short-term fluctuations and reflects medium- and long-term aging trends.

[0095] Furthermore, to achieve more accurate aging assessment, the following steps are adopted:

[0096] Based on the time information of multiple sets of historical calibration temperature data, the time interval corresponding to the current average aging parameter value is calculated;

[0097] Set a baseline update cycle, such as every 24 running hours, and determine whether the time interval is greater than the baseline update cycle. If the time interval is greater than the baseline update cycle, it means that enough new data has been accumulated to update the health baseline. At this time, the current average aging parameter value is set as the new baseline aging value.

[0098] The reference aging value refers to a reference standard representing the normal aging rate of a thermocouple.

[0099] In daily monitoring, set an allowable aging deviation and compare the latest average aging parameter value with the set baseline aging value. If the difference exceeds the allowable aging deviation, it indicates that the aging rate of the thermocouple has exceeded the normal range and its condition is judged as abnormal. Conversely, if the difference does not exceed the allowable aging deviation, its condition is judged as normal.

[0100] By comparing the results of thermocouples and temperature sensors in real time, the measurement and control system is guaranteed to have self-diagnostic capabilities. By periodically monitoring the trend of thermocouple parameter changes or thermocouple status, it is possible to predict and replace them in time to avoid potential failure risks. This method is applicable to multi-area temperature measurement needs, dynamic process adjustment needs, and extreme temperature difference control occasions, thereby improving the overall safety, intelligence, and product yield of vacuum furnace equipment.

[0101] Example 2

[0102] See Figure 2 This embodiment provides a multi-sensor-based vacuum furnace temperature control system, including:

[0103] The multi-source data acquisition module is configured to communicate with the sensor network inside the vacuum furnace to acquire multiple types of data in real time. Specifically, the multi-source data acquisition module continuously acquires at least two core data streams:

[0104] Temperature measurement data from a temperature sensor inside the vacuum furnace, which can be a high-precision, high-stability reference sensor, such as a platinum resistance thermometer; voltage data from thermocouples inside the vacuum furnace, i.e. real-time thermocouple voltage data. After these data are collected, they are appended with precise timestamps and transmitted to subsequent functional modules for processing.

[0105] The calibration model building module is configured to build and dynamically update a thermocouple calibration model that accurately describes the nonlinear relationship between the thermocouple output voltage and the actual temperature.

[0106] In the specific execution process, the calibration model establishment module receives temperature measurement data and corresponding voltage data within a preset statistical period from the multi-source data acquisition module.

[0107] Furthermore, to ensure the accuracy of the model, the calibration model building module performs a data filtering process to identify calibration data, specifically:

[0108] The average temperature of all temperature measurements within the preset statistical period is calculated. Then, data points whose difference from the average temperature is less than a preset matching deviation threshold are identified as calibration temperature data. This step is used to select data from the vacuum furnace during its stable heat preservation phase, when temperature fluctuations are small and the measured values ​​are closer to the true values. Simultaneously, the module identifies voltage data that perfectly corresponds to these calibration temperature data in time, using this as calibration voltage data.

[0109] Based on paired calibration temperature and voltage data, this module employs a mathematical fitting method to establish a thermocouple calibration model. This model can output an accurate temperature value based on the input voltage value. The preferred mathematical fitting method is polynomial regression, piecewise linear interpolation, or training a neural network.

[0110] The temperature compensation control module is configured to receive real-time thermocouple voltage data acquired by the multi-source data acquisition module during the operation of the vacuum furnace, input this voltage data into the thermocouple calibration model established by the calibration model establishment module, and thus calculate a high-precision temperature compensation value.

[0111] Furthermore, to ensure the robustness of the control, an effectiveness judgment is performed, specifically:

[0112] The calculated temperature compensation value is compared with the current temperature measurement value measured by the temperature sensor at the same time. When the difference between the two is within a reasonable and preset range, the temperature compensation value is determined to be valid. In this case, the module calculates the temperature difference between the temperature compensation value and the current temperature measurement value, and generates a temperature deviation signal based on the temperature difference.

[0113] When the temperature compensation value is determined to be invalid, i.e., the difference between the two is too large, indicating a sudden problem with the sensor or model, this module will trigger an alarm to notify the operator. Simultaneously, to maintain uninterrupted production, based on the temperature compensation value and the current temperature measurement value, the module obtains the temperature adjustment parameters for regulating the heating equipment of the vacuum furnace. This process may include:

[0114] The required adjustment time is calculated based on the temperature difference and the reference temperature adjustment rate. Then, based on these two factors, the specific heating power or heating duration is determined as the temperature adjustment parameter, and temporary control is carried out in a more conservative manner.

[0115] The thermocouple condition assessment module is configured to monitor and provide early warnings about the long-term condition of thermocouples to prevent production accidents caused by sensor aging or failure.

[0116] The thermocouple condition assessment module performs the assessment in at least two ways, as follows:

[0117] This module performs a rapid state assessment within a preset assessment cycle. It inputs a preset, fixed voltage value into the current thermocouple calibration model to obtain the model output temperature. By comparing the current output temperature with the output temperature of the previous assessment cycle, it calculates the change in the model output temperature. If the change exceeds the preset state judgment threshold, it indicates that the thermocouple characteristics have drifted significantly in a short period of time, and the module immediately determines that the thermocouple state is abnormal.

[0118] This module performs long-term aging trend analysis. Based on historical calibration temperature data, such as the stable period data used to build the model over the past few weeks or months, it calculates one or more average aging parameter values ​​that can characterize the degree of thermocouple aging, such as the average rate of change of the Seebeck coefficient. When the difference between the average aging parameter value and the baseline aging value representing a brand new or ideal state exceeds the allowable aging deviation, it indicates that the thermocouple has undergone irreversible chronic aging. This module also determines that the thermocouple condition is abnormal. When any evaluation method determines that the thermocouple condition is abnormal, this module will immediately generate a safety control command.

[0119] The control execution module is configured to translate the logical instructions generated by the upstream module into actual operations on the physical device. Specifically:

[0120] Upon receiving a temperature deviation signal or temperature regulation parameter, it converts it into specific control commands for the vacuum furnace heating equipment, such as adjusting the heater's power output percentage, controlling the heating time, or adjusting the PID controller's set value to precisely regulate the furnace temperature.

[0121] Upon receiving a safety control command, the control execution module will immediately execute the preset safety plan. For example, it can automatically switch to a preset backup thermocouple to seamlessly take over the temperature measurement task; or, in the absence of a backup sensor, it can pause heating and lock the system for manual maintenance, thereby ensuring the safety of the equipment and products.

Claims

1. A method for controlling the temperature of a vacuum furnace based on multiple sensors, characterized in that, Includes the following steps: Acquire real-time thermocouple voltage data inside the vacuum furnace; Based on a pre-established thermocouple calibration model, the temperature compensation value corresponding to the real-time thermocouple voltage data is determined. When the temperature compensation value is determined to be valid by the temperature difference between the temperature compensation value and the current temperature measurement value at the same time being less than the validity judgment threshold, a temperature deviation signal is generated based on the temperature difference between the temperature compensation value and the current temperature measurement value to adjust the heating equipment of the vacuum furnace. The establishment of the thermocouple calibration model includes: Acquire temperature measurement data from the temperature sensor and voltage data from the thermocouple inside the vacuum furnace; Within a preset statistical period, the calibration temperature data is identified from the temperature measurement data, and the calibration voltage data corresponding to the calibration temperature data in time is also identified. A thermocouple calibration model was established based on calibration temperature and calibration voltage data. Among them, identifying calibration temperature data from temperature measurement data within a preset statistical period includes: Calculate the average temperature of the temperature measurement data obtained within a preset statistical period; and determine the data in the temperature measurement data whose difference from the average temperature is less than a preset matching deviation threshold as calibration temperature data.

2. The vacuum furnace temperature control method based on multiple sensors according to claim 1, characterized in that, The method further includes: When the temperature compensation value is determined to be invalid, an alarm operation is executed, and the temperature compensation value and the current temperature measurement value are transmitted to the evaluation and processing flow to obtain the temperature regulation parameters for adjusting the vacuum furnace heating equipment.

3. The vacuum furnace temperature control method based on multiple sensors according to claim 2, characterized in that, Based on the temperature compensation value and the current temperature measurement value, the temperature regulation parameters for adjusting the heating equipment of the vacuum furnace are obtained, including: Calculate the adjustment time based on the temperature difference and the preset temperature adjustment rate; Based on the temperature difference and adjustment time, determine the heating power or heating duration, and use the heating power or heating duration as the temperature adjustment parameter.

4. The vacuum furnace temperature control method based on multiple sensors according to claim 3, characterized in that, The method also includes assessing the condition of the thermocouple, specifically including: When the temperature change of the thermocouple calibration model, which corresponds to the preset voltage value, exceeds the state judgment threshold within the preset evaluation period, the thermocouple state is determined to be abnormal. When the thermocouple is determined to be abnormal, the operation of switching to the preset backup thermocouple or suspending heating is performed.

5. The vacuum furnace temperature control method based on multiple sensors according to claim 4, characterized in that, Assessing the condition of thermocouples also includes: Based on historical calibration temperature data, the average aging parameter values ​​characterizing the aging degree of thermocouples are calculated. When the difference between the average aging parameter value and the baseline aging value exceeds the allowable deviation of aging, the thermocouple condition is determined to be abnormal.

6. A vacuum furnace temperature control system based on multiple sensors, characterized in that, Includes the following modules: The multi-source data acquisition module is used to acquire temperature measurement data from the temperature sensor and voltage data from the thermocouple inside the vacuum furnace. The calibration model building module is used to build a thermocouple calibration model based on the temperature measurement data and thermocouple voltage data obtained by the multi-source data acquisition module. The temperature compensation control module is used to respond to the real-time thermocouple voltage data acquired by the multi-source data acquisition module, call the thermocouple calibration model to determine the temperature compensation value, and when the temperature compensation value is determined to be valid, generate a temperature deviation signal for adjusting the heating equipment of the vacuum furnace. The thermocouple condition assessment module is used to assess the condition of thermocouples based on the output of the thermocouple calibration model within a preset assessment period, and to generate safety control commands when the thermocouple condition is determined to be abnormal. In addition, a control execution module is used to adjust the heating equipment according to the temperature deviation signal and to execute safety control commands; The thermocouple calibration model, based on temperature measurement data and thermocouple voltage data acquired by the multi-source data acquisition module, includes: Calculate the average temperature within the temperature measurement data; identify the temperature measurement data whose difference from the average temperature is less than the preset matching deviation threshold as calibration temperature data, and establish a thermocouple calibration model based on the calibration temperature data and the corresponding calibration voltage data.

7. A vacuum furnace temperature control system based on multiple sensors according to claim 6, characterized in that, The temperature compensation control module is also configured as follows: When the temperature compensation value is determined to be invalid, an alarm operation is executed, and the temperature compensation value and the current temperature measurement value are transmitted to the evaluation and processing flow to obtain the temperature regulation parameters for adjusting the vacuum furnace heating equipment.

8. A vacuum furnace temperature control system based on multiple sensors according to claim 7, characterized in that, The thermocouple condition assessment module is also configured as follows: Calculate the average aging parameter values ​​that characterize the degree of thermocouple aging; When the difference between the average aging parameter value and the baseline aging value exceeds the allowable deviation of aging, the thermocouple condition is determined to be abnormal.

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