MFC calibration method and system based on bilateral feedback and redundancy check mechanism

Abstract

The invention discloses an MFC calibration method based on a bilateral feedback and redundancy check mechanism. The MFC calibration method adopts the following calibration platform: the calibration platform comprises hardware equipment and upper computer software; wherein the hardware equipment comprises an oil-free air compressor, a digital display precision pressure regulating valve, standard MFC equipment, MFC equipment to be calibrated, standard MFM equipment, a temperature monitoring module and an upper computer; the method comprises the following steps: setting a plurality of calibration points in a measuring range of MFC equipment to be calibrated through upper computer software; for each calibration point, collecting set flow data of the standard MFC equipment and measured flow data of the standard MFM equipment in real time; performing redundancy check on the set flow data and the measured flow data corresponding to each calibration point; and generating a calibration curve for the to-be-calibrated and calibrated MFC equipment based on redundancy check results of the plurality of calibration points. According to the method and the system provided by the invention, high-precision, high-efficiency and intelligent calibration is realized through software and hardware cooperation.

Description

Technical Field

[0001] This invention relates to the field of flow control technology, and in particular to an MFC calibration method and system based on a dual-sided feedback and redundancy verification mechanism. Background Technology

[0002] With the continuous development of science and technology, the key technology of accurately measuring and controlling gas flow rate occupies an extremely important position in modern industry and scientific research, and is of great significance for ensuring product quality, improving production efficiency, reducing energy consumption, and even promoting scientific and technological progress.

[0003] Gas mass flow controllers (MFCs), as core components of precision gas flow control, play a crucial role in semiconductor manufacturing, photovoltaic industry, aerospace, chemical production, medical equipment, and scientific research. To meet the needs of actual production and technological development, there are currently more than one hundred flow measurement methods and devices developed based on different physical laws.

[0004] Given the unstable physical properties of gases, and the fact that this instability is largely influenced by external conditions or the gas's own characteristics, detecting gas flow rate is more complex and difficult to control compared to detecting other parameters. Since the measurement and control accuracy of mass flow controllers directly affects process stability and product quality, they must be calibrated regularly to ensure their long-term reliability.

[0005] Traditional calibration methods primarily rely on comparing a standard flow meter (MFM) in series with the mass flow controller (MFC) under test, such as using a soap film flow meter or a wet gas flow meter as a reference. In practice, this method requires frequent disassembly and reconnection of the MFC to the calibration system, which is not only cumbersome but also prone to gas path contamination or seal failure due to repeated disassembly and reassembly, thus affecting the MFC's lifespan and stability. Furthermore, the accuracy of this calibration method is entirely dependent on the standard flow meter; if the standard device has errors or instability, these issues will directly affect the calibration accuracy. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of current MFC calibration methods, this invention provides an MFC calibration method based on a dual-sided feedback and redundancy verification mechanism, which achieves high-precision, high-efficiency and intelligent calibration through hardware and software collaboration.

[0007] To achieve the above objectives, the embodiments of the present invention adopt the following technical solutions:

[0008] A calibration method for MFC (Multi-Functional Fusion) based on a dual-sided feedback and redundancy verification mechanism is disclosed. The method is implemented through a calibration platform comprising hardware devices and host computer software. The hardware devices include an oil-free air compressor, a digital display precision pressure regulating valve, a standard MFC device, an MFC device to be calibrated, a standard MFM (Multi-Functional Fusion) device, and a temperature detection module, connected in series via an air path and a quick-connect interface. The standard MFC device, the MFC device to be calibrated, and the standard MFM device are connected to the host computer via communication interfaces. The method includes the following steps:

[0009] The host computer software is used to set multiple calibration points within the measurement range of the MFC device to be calibrated.

[0010] For each calibration point, the set flow rate data of the standard MFC device as front-end feedback and the measured flow rate data of the standard MFM device as back-end feedback are collected in real time.

[0011] For each calibration point, a redundancy check is performed between the set flow rate data and the measured flow rate data.

[0012] Based on the redundant verification results of multiple calibration points, a calibration curve is generated for the MFC device to be calibrated.

[0013] According to one aspect of the present invention, the real-time acquisition of the set flow data of the standard MFC device as front-end feedback and the measured flow data of the standard MFM device as back-end feedback for each calibration point further includes: acquiring the operating temperature of the system in real time through a temperature monitoring module; and, at least based on the operating temperature, performing real-time compensation on the measured flow data of the standard MFM device to eliminate measurement errors introduced by temperature changes.

[0014] According to one aspect of the present invention, the redundancy check between the set flow rate data and the measured flow rate data corresponding to each calibration point specifically comprises:

[0015] Calculate the deviation between the set flow rate data and the measured flow rate data corresponding to the calibration point;

[0016] If the deviation value does not exceed the predetermined threshold, the average value of the set flow rate data and the measured flow rate data is taken as the calibration parameter of the calibration point;

[0017] If the deviation value exceeds the predetermined threshold, the data is determined to be invalid and a recalibration process is triggered.

[0018] According to one aspect of the present invention, the MFC calibration method further includes:

[0019] A calibration database is constructed to store the complete process data after each calibration, forming a full life cycle performance profile of the MFC device to be calibrated.

[0020] Data analysis is performed based on the calibration database to generate recommended data for calibration.

[0021] According to one aspect of the present invention, the MFC calibration method further includes: predicting the performance drift or future calibration value of the MFC device to be calibrated based on the calibration database.

[0022] According to one aspect of the present invention, the prediction step specifically includes:

[0023] Extract the historical deviation values ​​of the MFC device to be calibrated from the calibration database;

[0024] The deviation values ​​are trained and learned to plot the drift curves of key performance indicators of the MFC device to be calibrated.

[0025] Based on the drift curve, it is predicted whether the error of the MFC device to be calibrated will exceed the allowable tolerance range in the future.

[0026] According to one aspect of the present invention, the step of generating a calibration curve for the MFC device to be calibrated is implemented by a calibration model, specifically as follows:

[0027] Construct the calibration model based on the system's transfer characteristics;

[0028] Receive the set flow rate data, the measured flow rate data, and the recommended data;

[0029] The calibration curve is generated by performing multi-parameter collaborative calculations using a data fusion algorithm.

[0030] According to one aspect of the present invention, the host computer software is provided with a graphical human-computer interaction interface, which includes one or more of a flow control operation area, an instruction interaction area, and a flow calibration area.

[0031] According to one aspect of the present invention, the graphical human-computer interface performs the following operations:

[0032] The flow rate of the MFC device to be calibrated is controlled and its status is monitored in real time in the flow control operation area.

[0033] Receive and send custom serial port commands in the command interaction area to invoke device functions or perform system debugging;

[0034] In the flow calibration area, a multi-point linear correction process is performed on the MFC device to be calibrated to establish a linear relationship for flow control and verify key performance indicators.

[0035] An MFC calibration system based on a dual-sided feedback and redundancy verification mechanism is provided for implementing any of the MFC calibration methods described above. The system includes:

[0036] The hardware platform includes an oil-free air compressor, a digital display precision pressure regulating valve, a standard MFC device, an MFC device to be calibrated, a standard MFM device, and a temperature monitoring module, which are connected in series via air tubes and quick-connect interfaces.

[0037] The host computer is connected to the standard MFC device, the MFC device to be calibrated, and the standard MFM device via a communication interface.

[0038] The host computer runs calibration software and is configured to perform at least one of the following functions: data acquisition, cross-comparison, calibration parameter generation, temperature compensation, database management, and predictive analysis.

[0039] The advantages of this invention are as follows: By connecting standard MFC and standard MFM in series to form a dual-feedback and redundancy verification mechanism, abnormal data is dynamically filtered through cross-comparison of data from two devices, ensuring the reliability of the calibration benchmark from the source and avoiding the risks of contamination and sealing caused by repeated disassembly and assembly; by establishing a calibration database, a shift from passive periodic calibration to proactive predictive maintenance is achieved, extending the equipment maintenance cycle; furthermore, by constructing a calibration model and integrating multi-parameter collaborative calculation, high-precision calibration is achieved across the entire range. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0041] Figure 1 This is a schematic flowchart of an MFC calibration method based on a dual-sided feedback and redundancy verification mechanism as described in this invention.

[0042] Figure 2 This is a schematic diagram of another MFC calibration method based on a dual-sided feedback and redundancy verification mechanism described in this invention. Detailed Implementation

[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0044] Example 1

[0045] like Figure 1 and Figure 2 As shown, an MFC calibration method based on a dual-sided feedback and redundancy verification mechanism is disclosed. The method is implemented through a calibration platform, which includes hardware devices and host computer software. The hardware devices include an oil-free air compressor, a digital display precision pressure regulating valve, a standard MFC device, an MFC device to be calibrated, a standard MFM device, and a temperature monitoring module, connected in series via an air path and a quick-connect interface. The standard MFC device, the MFC device to be calibrated, and the standard MFM device are connected to the host computer via communication interfaces. The method includes the following steps:

[0046] Step S1: Set multiple calibration points within the measurement range of the MFC device to be calibrated using the host computer software.

[0047] Step S2: For each calibration point, the set flow rate data of the standard MFC device as the front-end feedback and the measured flow rate data of the standard MFM device as the back-end feedback are collected in real time.

[0048] Step S3: Perform redundancy verification between the set flow rate data and the measured flow rate data corresponding to each calibration point;

[0049] Step S4: Based on the redundant verification results of multiple calibration points, generate a calibration curve for the MFC device to be calibrated.

[0050] Specifically, in the hardware implementation of the calibration method, each hardware device is sequentially connected to the air tube via a quick-connect interface, and the entire assembly is fixed to the base using a bracket. This integrated fixing design not only effectively protects the equipment components and extends their service life, but also significantly enhances the stability and safety during operation.

[0051] The oil-free air compressor converts the mechanical energy of the motor into gas pressure energy, continuously outputting clean, dry compressed air. This effectively avoids contamination of downstream precision air circuits and the internal structure of the MFC by oil mist and impurities, providing a stable air source that meets preset requirements for the calibration process. The airflow is delivered to a digital display precision pressure regulating valve via a quick-connect interface. This valve integrates digital display and high-precision pressure regulation functions, achieving precise and rapid adjustment of gas pressure and flow rate through closed-loop feedback control, providing constant pressure and pure inlet conditions for subsequent flow detection.

[0052] During the calibration process, the airflow flows in series through the standard MFC device, the MFC device being calibrated, and the standard MFM device. This specific series structure forms the hardware foundation for realizing the dual-sided feedback and redundancy verification mechanism, enabling the setpoint of the front-end standard MFC and the measured value of the back-end standard MFM to form a closed-loop comparison and verification.

[0053] Further, in step S1, multiple calibration points are set within the measurement range of the MFC device to be calibrated using host computer software; the setting of these multiple calibration points follows the principle of coverage from feature points to the full measurement range, specifically including:

[0054] Zero-point calibration: With no gas passing through the hardware device, the calibration point is set to 0% to calibrate the device baseline and eliminate zero-drift error;

[0055] Feature point calibration: After the hardware device is supplied with gas and the pressure is stable, the calibration points are set to 50% and 100% of the full scale in sequence, which are used to calibrate the accuracy of the intermediate range and the maximum output accuracy of the full scale, respectively.

[0056] Linear correction point calibration: After completing the feature point calibration, starting from full scale, the calibration point is set in increments of 10% until it approaches zero, so as to achieve fine correction of nonlinear error across the entire scale range.

[0057] Furthermore, in step S2, for each calibration point, the set flow rate data of the standard MFC device (as front-end feedback) and the measured flow rate data of the standard MFM device (as back-end feedback) are collected in real time, specifically as follows:

[0058] Once the airflow at a certain calibration point reaches a stable state, the host computer software synchronously acquires the set flow data of the standard MFC device and the measured flow data of the standard MFM device through analog or digital communication interfaces.

[0059] The core of the calibration method's hardware calibration is a closed-loop calibration chain consisting of a standard MFC device, an MFC device to be calibrated, a standard MFM device, and a temperature monitoring module connected in series via a gas path, and connected to a host computer through an analog or digital communication interface. In the closed-loop calibration chain, the standard MFC acts as the front-end flow setter and generator, receiving instructions from the host computer and accurately generating the required stable flow rate; its own set flow rate data is read in real time. The standard MFM acts as the back-end high-precision flow measurement unit, and its reading is considered a reliable reference value for the current flow rate.

[0060] Furthermore, the system's operating temperature is collected in real time via a temperature monitoring module; based at least on the operating temperature, the measured flow data of the standard MFM device is compensated in real time to eliminate measurement errors introduced by temperature changes. The calibration method implements a differentiated temperature compensation strategy based on the functional differences of the equipment in the calibration chain, specifically:

[0061] Standard MFM equipment must undergo temperature compensation because its measurements are based on flow rate and directly affect calibration accuracy. Temperature data is used for real-time compensation to eliminate temperature errors. For MFC equipment being calibrated, compensation is flexible, allowing for real-time compensation or correction via calibration parameters. Standard MFC equipment typically does not require compensation because its calibration process already handles temperature effects.

[0062] Furthermore, in step S3, a redundancy check is performed on the set flow rate data and the measured flow rate data corresponding to each calibration point, specifically as follows:

[0063] Step S311: Calculate the deviation between the set flow rate data and the measured flow rate data corresponding to the calibration point;

[0064] Calculate the absolute or relative deviation between the set flow rate data of the standard MFC device and the measured flow rate data of the standard MFM device after temperature compensation at the same time.

[0065] Step S312: If the deviation value does not exceed the predetermined threshold, then the average value of the set flow rate data and the measured flow rate data is taken as the calibration parameter of the calibration point.

[0066] The calculated absolute or relative deviation value is compared with the preset allowable threshold. If the deviation does not exceed the threshold, the data set is deemed valid and proceeds to the next processing step. For valid data that passes the determination, the average value of the set flow rate data and the measured flow rate data is taken as the calibration parameter for the flow rate at the current calibration point.

[0067] Step S313: If the deviation value exceeds the predetermined threshold, the data is determined to be invalid and a recalibration process is triggered.

[0068] If the deviation exceeds the threshold, the system will automatically determine that the data point is unreliable due to instantaneous fluctuations in the system, mark it as invalid, and re-collect and compare the data at the calibration point. This dynamic filtering of abnormal data points ensures the reliability of the input data.

[0069] Simultaneously, after each calibration point, a brief backtracking to the 100% or 50% node can be performed to verify whether the full-scale or intermediate point accuracy is affected. The redundancy verification process dynamically suppresses potential errors from a single device or transient instability in the system through real-time mutual verification between the two standard devices.

[0070] Further, in step S4, based on the redundancy verification results of multiple calibration points, a calibration curve for the MFC device to be calibrated is generated. The generation of the calibration curve for the MFC device to be calibrated is achieved through a graphical user interface. Specifically:

[0071] The host computer software has a graphical human-computer interaction interface, which includes one or more of the following: a flow control operation area, a command interaction area, and a flow calibration area.

[0072] The graphical human-computer interface performs the following operations: In the flow control operation area, it performs real-time control and status monitoring of the flow of the MFC device to be calibrated; in the command interaction area, it receives and sends custom serial port commands to invoke device functions or perform system debugging; in the flow calibration area, it executes a multi-point linear correction process on the MFC device to be calibrated to establish a linear relationship in flow control and verify key performance indicators. Specifically:

[0073] The flow control area includes flow unit, current flow, valve opening, target value, and set value, etc., and is used for real-time control and status monitoring of the flow of the MFC equipment to be calibrated. In this area, the current flow value, the opening percentage of the internal valve, and the percentage of full scale are updated in real time; the current scale percentage is set in this area, and the flow is automatically adjusted to stabilize at the corresponding full scale percentage.

[0074] The command interaction area is used to receive and send custom serial port commands to invoke device functions or perform system debugging. This module allows users to send specific commands to the MFC device to be calibrated, such as sending calibration commands or reading specific device parameters, thereby enabling advanced debugging and special parameter configuration functions.

[0075] The flow calibration area is used to calibrate the flow output accuracy of the MFC equipment to be calibrated. At different set percentages, relevant parameters are adjusted by comparing actual measured values ​​with the original calibration values ​​to ensure the gas flow output more accurately meets the set requirements and guarantees the accuracy of flow control.

[0076] In summary, by generating calibration curves for the MFC device to be calibrated through multi-point calibration in a graphical human-computer interaction interface, the nonlinear error of the MFC device under different ranges is corrected, ensuring the flow accuracy across the entire range.

[0077] Example 2

[0078] like Figure 1 and Figure 2 As shown, the difference between this embodiment and Embodiment 1 is that a calibration database is constructed to predict the performance drift or future calibration values ​​of the MFC device to be calibrated. Specifically:

[0079] Step S1: Construct a calibration database to store the full process data after each calibration, forming a full life cycle performance profile of the MFC device to be calibrated.

[0080] After each calibration is completed, all calibration process data is synchronously stored in a time-series database to build a calibration database. This data includes, but is not limited to: the set time for each calibration point, ambient temperature, set flow rate data for the standard MFC device, measured flow rate data for the standard MFM device after temperature compensation, calculated deviation values, and the final generated calibration curve. This data is stored in a time-series association with the device serial number, forming a full lifecycle performance profile for the MFC device to be calibrated.

[0081] Furthermore, based on the calibration database, the performance drift or future calibration values ​​of the MFC device to be calibrated are predicted. The prediction step specifically includes:

[0082] Step S121: Extract the historical deviation values ​​of the MFC device to be calibrated from the calibration database;

[0083] For a specific MFC device to be calibrated, the deviation values ​​of the set flow rate data and measured flow rate data before all previous calibration cycles are extracted from the calibration database.

[0084] Step S122: Train and learn the deviation value to plot the drift curve of the key performance index of the MFC device to be calibrated.

[0085] By using machine learning or data fitting algorithms, the extracted historical deviation values ​​are trained and learned to plot the key performance indicators of the equipment, such as zero drift, range accuracy deviation, and drift curves over time.

[0086] Step S123: Based on the drift curve, predict whether the error of the MFC device to be calibrated will exceed the allowable tolerance range in the future.

[0087] Based on the drift curve, it is possible to predict whether the error of the MFC equipment to be calibrated may exceed the allowable tolerance range at some point in the future, thereby enabling predictive maintenance and issuing calibration warnings before the risk of exceeding tolerance occurs.

[0088] Step S2: Perform data analysis based on the calibration database to generate recommended data for calibration.

[0089] By conducting in-depth analysis of the calibration database, common error patterns were summarized for MFC devices with the same range and similar models. When calibrating new MFC devices or performing periodic calibrations, recommended data can be generated based on the historical data analysis results to improve calibration efficiency and initial accuracy.

[0090] Example 3

[0091] like Figure 1 and Figure 2 As shown, the difference between this embodiment and Embodiment 2 is that a calibration model is constructed to generate the calibration curve for the MFC device to be calibrated. Specifically:

[0092] Step S1: Construct the calibration model based on the system's transfer characteristics;

[0093] A calibration model H(S) based on system transmission characteristics is constructed as the intelligent hub.

[0094] Based on the theory of system transfer characteristics, a calibration model H(S) is constructed. This model, as an intelligent central hub, aims to describe the overall system transfer relationship from the standard MFC setpoint to the standard MFM measurement value, and can comprehensively compensate for the complex dynamic characteristics of the gas path system and equipment itself, such as nonlinearity and hysteresis.

[0095] Step S2: Receive the set flow rate data, the measured flow rate data, and the recommended data;

[0096] The calibration model H(S) receives multiple input parameters, including:

[0097] Input parameter X(S): Set flow data from the standard MFC device.

[0098] Output parameter Y(S): Temperature-compensated measured flow data from the standard MFM device, serving as a reliable reference.

[0099] Recommended data: Provided after data analysis of the calibration database in Example 2.

[0100] Step S3: Perform multi-parameter collaborative calculation using a data fusion algorithm to generate the calibration curve.

[0101] The calibration model H(S) uses a built-in data fusion algorithm, such as a neural network algorithm, to perform collaborative calculations and optimizations on the aforementioned multiple parameters. Through model computation, this algorithm obtains a set of calibration parameters that optimally correct the systematic errors of the MFC device to be calibrated across its entire range. This set of parameters constitutes a high-precision calibration curve, which can be directly sent to the device to be calibrated.

[0102] Example 4

[0103] An MFC calibration system based on a dual-sided feedback and redundancy verification mechanism is provided to implement the calibration methods described in Embodiments 1, 2, and 3. The system includes:

[0104] The hardware platform includes an oil-free air compressor, a digital display precision pressure regulating valve, a standard MFC device, an MFC device to be calibrated, a standard MFM device, and a temperature monitoring module, which are connected in series via air tubes and quick-connect interfaces.

[0105] The host computer is connected to the standard MFC device, the MFC device to be calibrated, and the standard MFM device via a communication interface.

[0106] The host computer runs calibration software and is configured to perform at least one of the following functions: data acquisition, cross-comparison, calibration parameter generation, temperature compensation, database management, and predictive analysis.

[0107] The advantages of this invention are as follows: By connecting standard MFC and standard MFM in series to form a dual-feedback and redundancy verification mechanism, abnormal data is dynamically filtered through cross-comparison of data from two devices, ensuring the reliability of the calibration benchmark from the source and avoiding the risks of contamination and sealing caused by repeated disassembly and assembly; by establishing a calibration database, a shift from passive periodic calibration to proactive predictive maintenance is achieved, extending the equipment maintenance cycle; furthermore, by constructing a calibration model and integrating multi-parameter collaborative calculation, high-precision calibration is achieved across the entire range.

[0108] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for MFC calibration based on bilateral feedback and redundancy check mechanism, characterized in that, The method is realized by a calibration platform, the calibration platform comprises a hardware device and a host computer software; wherein the hardware device comprises an oil-free air compressor, a digital precise pressure regulating valve, a standard MFC device, a calibration MFC device to be calibrated, a standard MFM device and a temperature detection module which are sequentially connected through an air path and a quick connector; the standard MFC device, the calibration MFC device to be calibrated and the standard MFM device are connected with the host computer through a communication interface respectively; the method comprises the following steps: Through the host computer software, a plurality of calibration points are set in the range of the calibration MFC device to be calibrated; For each calibration point, the set flow data of the standard MFC device as front-end feedback and the measured flow data of the standard MFM device as back-end feedback are collected in real time; The set flow data and the measured flow data corresponding to each calibration point are redundantly checked; Based on the redundancy check results of a plurality of calibration points, a calibration curve for the calibration MFC device to be calibrated is generated.

2. The MFC calibration method of claim 1, wherein, The step of collecting the set flow data of the standard MFC device as front-end feedback and the measured flow data of the standard MFM device as back-end feedback in real time for each calibration point further comprises: collecting the working temperature of the system in real time through the temperature monitoring module; at least based on the working temperature, the measured flow data of the standard MFM device is compensated in real time to eliminate the measurement error introduced by temperature change.

3. The MFC calibration method of claim 1, wherein, The redundancy check of the set flow data and the measured flow data corresponding to each calibration point specifically comprises: calculating the deviation value between the set flow data and the measured flow data corresponding to the calibration point; if the deviation value does not exceed a predetermined threshold, the average value of the set flow data and the measured flow data is taken as the calibration parameter of the calibration point; if the deviation value exceeds the predetermined threshold, the data is determined to be invalid and a re-calibration process is triggered.

4. The MFC calibration method of claim 3, wherein, The MFC calibration method further comprises: building a calibration database to store the whole process data after each calibration, forming a full life cycle performance file of the calibration MFC device to be calibrated; based on the calibration database, data analysis is performed to generate recommended data for calibration.

5. The MFC calibration method of claim 4, wherein, The MFC calibration method further comprises: based on the calibration database, the performance drift or future calibration value of the calibration MFC device to be calibrated is predicted.

6. The MFC calibration method of claim 5, wherein, The prediction step specifically comprises: extracting the historical deviation value of the calibration MFC device to be calibrated from the calibration database; training and learning the deviation value to draw a drift curve of the key performance indicators of the calibration MFC device to be calibrated; based on the drift curve, it is predicted whether the error of the calibration MFC device to be calibrated in the future will exceed the allowed tolerance range.

7. The MFC calibration method of claim 4, wherein, The step of generating a calibration curve for the calibration MFC device to be calibrated is realized by a calibration model, specifically: building the calibration model based on the system transfer characteristics; receiving the set flow data, the measured flow data and the recommended data; The calibration curve is generated through multi-parameter collaborative calculation by a data fusion algorithm.

8. The MFC calibration method of claim 1, wherein, The host computer software is provided with a graphical man-machine interface, and the graphical man-machine interface comprises one or more of a flow control operation area, an instruction interaction area and a flow calibration area.

9. The MFC calibration method of claim 8, wherein, The graphical man-machine interface performs the following operations: In the flow control operation area, the flow of the MFC device to be calibrated is controlled and monitored in real time; In the instruction interaction area, custom serial port instructions are received and sent to call device functions or perform system debugging; In the flow calibration area, a multi-point linear correction process is performed on the MFC device to be calibrated to establish a linear relationship of flow control and verify key performance indicators.

10. A MFC calibration system based on a dual feedback and redundancy check mechanism for implementing the MFC calibration method of any one of claims 1-9, characterized in that, The system comprises: a hardware platform comprising, in sequence through an air pipe and a quick connector, an oil-free air compressor, a digital precise pressure regulating valve, a standard MFC device, an MFC device to be calibrated, a standard MFM device and a temperature monitoring module; a host computer connected with the standard MFC device, the MFC device to be calibrated and the standard MFM device through a communication interface; The host computer runs a calibration software configured to perform at least one of data acquisition, cross comparison, calibration parameter generation, temperature compensation, database management and predictive analysis.

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