Multi-temperature multi-pressure intelligent flowmeter calibration table and calibration method thereof

Abstract

The invention relates to the technical field of gas flow measurement, in particular to a multi-temperature multi-pressure intelligent flowmeter calibration table and a calibration method thereof. Comprising a detection table, an intelligent control end, a gas flow generator, heating equipment, a temperature and pressure sensor, an MEMS ultrasonic flowmeter, a standard flowmeter and an MFC proportional valve, flow, temperature and pressure parameters are coordinated through the intelligent control end, automatic all-working-condition calibration of the MEMS ultrasonic flowmeter is achieved, an AI training data set is constructed, the calibration efficiency and precision are improved, and the calibration precision is improved. The method is suitable for large-scale flowmeter intelligent production lines.

Description

Technical Field

[0001] The present invention relates to the technical field of gas flow measurement, and in particular to a multi-temperature and multi-pressure intelligent flowmeter calibration platform and a calibration method thereof. Background Art

[0002] Gas flow meter calibration can correct measurement deviations caused by temperature and pressure changes, installation errors, or long-term use, ensuring that the measured value is consistent with the actual flow rate, safeguarding the fairness of trade settlements for natural gas, industrial gas, etc., and providing reliable data for production process control and safety monitoring in the chemical, environmental protection and other fields. By comparing with standard devices, measurement traceability can be achieved. Calibration can also detect the status of equipment components and warn of faults to extend service life. It is a key link to ensure accurate and compliant gas flow measurement and stable system operation. Currently, flowmeter calibration is mostly performed at room temperature and pressure, relying on manual adjustment of flow controllers. This is inefficient and lacks systematic coverage of environmental variables such as temperature and pressure. For MEMS ultrasonic flowmeters and thermal flowmeters, temperature and pressure changes significantly affect measurement results, making conventional calibration methods difficult to meet the high-precision calibration requirements across all operating conditions. Therefore, there is a need for an intelligent flowmeter calibration platform that can automatically and accurately calibrate gas flowmeters under different temperature and pressure conditions. Summary of the Invention

[0003] The purpose of the present invention is to provide a multi-temperature and multi-pressure intelligent flowmeter calibration platform and a calibration method thereof, aiming to solve the technical problems in the prior art that flowmeter calibration is mostly carried out under normal temperature and pressure environment, relies on manual adjustment of flow controller, is inefficient, and lacks systematic coverage of environmental variables such as temperature and pressure.

[0004] To achieve the above-mentioned objectives, the present invention adopts a multi-temperature and multi-pressure intelligent flowmeter calibration platform, which includes a detection platform, an intelligent control terminal, a gas flow generator, a heating device, a temperature and pressure sensor, a MEMS ultrasonic flowmeter, a standard flowmeter and an MFC proportional valve. The detection platform is installed with the MFC proportional valve, the MEMS ultrasonic flowmeter, the standard flowmeter and the temperature and pressure sensor. The heating device and the gas flow generator are both coupled to the detection platform. The intelligent control terminal is arranged on one side of the detection platform, and the intelligent control terminal is electrically connected to the gas flow generator, the heating device, the temperature and pressure sensor, the MEMS ultrasonic flowmeter, the standard flowmeter and the MFC proportional valve respectively.

[0005] The present invention also provides a multi-temperature and multi-pressure intelligent flowmeter calibration method, comprising the following steps: using the intelligent control terminal to set parameters, constructing the temperature, pressure and flow values of the detection platform, and completing the detection working condition setting; obtaining data on the standard flowmeter, calibrating the data to form reference data; collecting data on the MEMS ultrasonic flowmeter, and recording the data; comparing the data of the standard flowmeter with the data of the MEMS ultrasonic flowmeter, calculating the error to form data points; collecting data points to form a data set as the basis for AI modeling training.

[0006] Among them, the intelligent control terminal sends control instructions to the MFC proportional valve to set the target flow value; synchronously controls the heating device to set the target temperature and maintains a constant temperature through PID control; sets the gas pressure through the pressure stabilizing device to complete the test environment initialization.

[0007] The accurate value of the current flow rate is obtained from the standard flow meter as a reference value for this test; at the same time, the real-time feedback value of the temperature and pressure sensor is read to confirm that the environment is stable.

[0008] Among them, the MEMS ultrasonic flowmeter and upstream / downstream TOF time are collected; the current value of the temperature and pressure sensor is obtained; the actual sound velocity of the on-site gas in this state is detected and recorded, and the instantaneous flow value is calculated based on the value of the MEMS ultrasonic flow.

[0009] The intelligent control terminal compares the output value of the MEMS ultrasonic flowmeter with the standard reference value to calculate the error value; and the parameter records are packaged into data points.

[0010] Among them, the set points are repeatedly sampled several times, and the average processing is performed to improve the data support; the system saves it as a labeled data set for subsequent AI modeling training.

[0011] The present invention provides a multi-temperature and multi-pressure intelligent flowmeter calibration platform and its calibration method. When in use, the MEMS ultrasonic flowmeter is placed in the detection platform, and the intelligent control terminal outputs a command to the gas flow generator to generate the fluid input amount and input speed required for detection, and uses the heating equipment to increase the temperature, obtain data from the temperature and pressure sensor, and then collect the speed, temperature and pressure parameters on the MEMS ultrasonic flowmeter. Finally, the standard pressure temperature and the data on the standard flowmeter are read. After the model training is completed, it is automatically burned into the intelligent control terminal. In this way, fully automatic linkage control of temperature, pressure and flow is realized, supporting intelligent calibration of flowmeters under all working conditions, integrating automated data acquisition, calibration and AI modeling, meeting the intelligent calibration needs of large-scale flowmeter production lines, reducing the output of labor costs and improving the efficiency of detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0013] Figure 1 It is a structural schematic diagram of the multi-temperature and multi-pressure intelligent flowmeter calibration platform of the present invention.

[0014] Figure 2 It is a flowchart of the steps of the multi-temperature and multi-pressure intelligent flowmeter calibration method of the present invention.

[0015] Figure 3 It is a step flow chart of S100 of the present invention.

[0016] Figure 4 It is a step flow chart of S200 of the present invention.

[0017] Figure 5 It is a step flow chart of S300 of the present invention.

[0018] Figure 6 It is a step flow chart of S400 of the present invention.

[0019] Figure 7 It is a step flow chart of S500 of the present invention.

[0020] Figure 8 This is the structural framework diagram of the multi-temperature and multi-pressure intelligent flowmeter calibration station system.

[0021] Figure 9 It is a flow chart for automatic scanning and data collection of temperature, pressure and flow.

[0022] Figure 10 It is a flowchart of AI-assisted calibration and model output.

[0023] 101-Test bench, 102-Intelligent control terminal, 103-Gas flow generator, 104-Heating equipment, 105-Temperature and pressure sensor, 106-MEMS ultrasonic flowmeter, 107-Standard flowmeter, 108-MFC proportional valve. DETAILED DESCRIPTION

[0024] Exemplary embodiments are described in detail herein, with examples illustrated in the accompanying drawings. When the following description refers to the drawings, identical numerals in different drawings represent identical or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all embodiments consistent with this application.

[0025] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. As used in this application and the appended claims, the singular forms "a," "an," "the," and "the" are intended to include the plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0026] It should be understood that although the terms first, second, third, etc. may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0027] See also Figure 1 , Figure 1 It is a structural schematic diagram of the multi-temperature and multi-pressure intelligent flowmeter calibration platform of the present invention.

[0028] The present invention provides a multi-temperature and multi-pressure intelligent flowmeter calibration platform, including a test platform 101, an intelligent control terminal 102, a gas flow generator 103, a heating device 104, a temperature and pressure sensor 105, a MEMS ultrasonic flowmeter 106, a standard flowmeter 107 and an MFC proportional valve 108. The test platform 101 is installed with the MFC proportional valve 108, the MEMS ultrasonic flowmeter 106, the standard flowmeter 107 and the temperature and pressure sensor 105. The heating device 104 and the gas flow generator 103 are both coupled to the test platform 101. The intelligent control terminal 102 is arranged on one side of the test platform 101, and the intelligent control terminal 101 is electrically connected to the gas flow generator 103, the heating device 104, the temperature and pressure sensor 105, the MEMS ultrasonic flowmeter 106, the standard flowmeter 107 and the MFC proportional valve 108 respectively.

[0029] In this embodiment, when in use, the MEMS ultrasonic flowmeter 106 is placed in the detection table 101, and the intelligent control terminal 102 outputs a command to the gas flow generator 103 to generate the fluid input amount and input speed required for detection, and uses the heating device 104 to increase the temperature, obtain the data on the temperature and pressure sensor 105, and then collect the speed, temperature and pressure parameters on the MEMS ultrasonic flowmeter 106. Finally, the standard pressure temperature and the data on the standard flowmeter 107 are read. After the model training is completed, it is automatically burned into the intelligent control terminal 102. In this way, fully automatic linkage control of temperature, pressure and flow is achieved, and intelligent calibration of flow meters under all working conditions is supported. Automated data acquisition, calibration and AI modeling are integrated to meet the intelligent calibration needs of large-scale flow meter production lines, reduce labor cost output and improve detection efficiency.

[0030] The MEMS ultrasonic flowmeter 106 is an ultrasonic sensor manufactured based on micro-electromechanical system technology and is used to measure gas flow.

[0031] The MFC proportional valve 106 is a mass flow control proportional valve; See also Figures 2 to 10 ,in, Figure 2 This is a flow chart of the steps of the multi-temperature and multi-pressure intelligent flow meter calibration method of the present invention. Figure 3 is a flow chart of the steps of S100 of the present invention, Figure 4 is a flow chart of the steps of S200 of the present invention, Figure 5 is a flow chart of the steps of S300 of the present invention, Figure 6 is a flow chart of the steps of S400 of the present invention, Figure 7 is a flow chart of the steps of S500 of the present invention, Figure 8 This is the system structure diagram of the multi-temperature and multi-pressure intelligent flowmeter calibration station. Figure 9 It is a flow chart of automatic scanning and data collection of temperature, pressure and flow. Figure 10 It is a flowchart of AI-assisted calibration and model output.

[0032] The present invention also provides a multi-temperature and multi-pressure intelligent flow meter calibration method, comprising the following steps: S100: Using the intelligent control terminal 102 to set parameters, construct the temperature, pressure and flow values of the test platform 101, and complete the setting of the test conditions; S200: Acquire data from the standard flow meter 107 and calibrate the data to form reference data; S300: Collecting data from the MEMS ultrasonic flow meter 106 and recording the data; S400: Compare the data of the standard flow meter 107 and the data of the MEMS ultrasonic flow meter 106, calculate the error and form a data point; S500: Collect data points to form a data set as the basis for AI modeling training.

[0033] In this embodiment, the intelligent control terminal 102 is used to set parameters, and the temperature, pressure and flow values of the detection platform 101 are constructed to complete the detection working condition setting; the data on the standard flow meter 107 is obtained, and the data is calibrated to form reference data; the data on the MEMS ultrasonic flow meter 106 is collected and recorded; the data of the standard flow meter 107 and the MEMS ultrasonic flow meter 106 are compared, and the error is calculated to form data points; the data points are collected to form a data set as the basis for AI modeling training. In this way, fully automatic linkage control of temperature, pressure and flow is achieved, and intelligent calibration of flow meters under all working conditions is supported. Automated data acquisition, calibration and AI modeling are integrated to meet the intelligent calibration needs of large-scale flow meter production lines, reduce labor cost output and improve detection efficiency.

[0034] Furthermore, in the step of setting parameters by using the intelligent control terminal 102 and constructing the temperature, pressure and flow values of the detection platform 101 to complete the setting of the detection working conditions: The intelligent control terminal 102 sends a control instruction to the MFC proportional valve 108 to set the target flow value; Synchronously control the heating device 104 to set a target temperature and maintain a constant temperature through PID control; The gas pressure is set by the pressure stabilizing device to complete the initialization of the test environment.

[0035] In this embodiment, the intelligent control terminal 102 (the control agent on the PC) sends a control instruction to the MFC proportional valve 108 to set a target flow value (e.g., 10%, 30%, 60%, 100% FS), where FS is FullScale. The heating device 104 is synchronously controlled to set a target temperature (-10°C to 50°C) and maintain a constant temperature through PID control. The gas pressure (0.5 to 2 bar) is set through the pressure stabilizer to complete the test environment initialization.

[0036] Furthermore, in the step of obtaining the data from the standard flow meter 107 and calibrating the data to form reference data: In the step of collecting data from the MEMS ultrasonic flowmeter 106 and recording the data: Obtain the accurate value of the current flow rate from the standard flow meter 107 as a reference value for this test; At the same time, the real-time feedback value of the temperature and pressure sensor 105 is read to confirm that the environment is stable.

[0037] In this embodiment, after the target operating conditions are established, the system obtains the precise value of the current flow rate through the standard flow meter 107 (such as a Coriolis mass flowmeter) as the "reference value" for this test; at the same time, the real-time feedback value of the temperature and pressure sensor 105 is read to confirm that the environment is stable.

[0038] Furthermore, in the step of collecting data from the MEMS ultrasonic flowmeter 106 and recording the data: Collect the MEMS ultrasonic flowmeter 106 and upstream / downstream TOF time; Obtaining the current value of the temperature and pressure sensor 105; The actual sound velocity of the gas at the scene under this state is detected and recorded, and the instantaneous flow value is calculated based on the value of the MEMS ultrasonic flow.

[0039] In this embodiment, data from the MEMS ultrasonic flowmeter 106 is acquired; upstream / downstream TOF times (time of flight of ultrasonic signals) are collected; current temperature and pressure are collected; the "actual sound velocity of the on-site gas" in this state (commonly used for sound velocity calibration in static or low flow rate states) is automatically detected and recorded; and the instantaneous flow value calculated on the MEMS ultrasonic flowmeter 106 is recorded.

[0040] Furthermore, in the step of comparing the data of the standard flow meter 107 and the data of the MEMS ultrasonic flow meter 106 and calculating the error to form a data point: The intelligent control terminal 102 compares the output value of the MEMS ultrasonic flow meter 106 with the standard reference value to calculate the error value; Parameter records are packaged as data points.

[0041] In this embodiment, the system compares the output value of the MEMS ultrasonic flow meter 106 with the standard reference value and calculates the error value; all parameter records are packaged into a set of data points.

[0042] Furthermore, in the step of collecting data points to form a dataset as the basis for AI modeling training: Repeat sampling several times at the set point, perform average processing, and improve data support; The system saves the data as a labeled dataset for subsequent AI modeling training.

[0043] In this embodiment, each set point is repeatedly sampled several times (e.g., 3 to 5 times) and averaged to improve data stability; the system automatically saves the data as a labeled dataset for subsequent AI modeling training.

[0044] Through the above process, the system collects flow data under multiple temperature and pressure conditions and constructs a labeled data set for use in AI model training.

[0045] The model can use algorithms such as linear regression and support vector machines for error compensation optimization and be deployed in the device-side MCU to improve measurement accuracy.

[0046] The above disclosure is only a preferred embodiment of the present invention, and certainly cannot be used to limit the scope of the rights of the present invention. Ordinary technicians in this field can understand that all or part of the processes of the above embodiment and equivalent changes made in accordance with the claims of the present invention are still within the scope of the invention.

Claims

1. A multi-temperature and multi-pressure intelligent flowmeter calibration platform, characterized in that: The invention comprises a detection platform, an intelligent control terminal, a gas flow generator, a heating device, a temperature and pressure sensor, a MEMS ultrasonic flow meter, a standard flow meter and an MFC proportional valve. The detection platform is equipped with the MFC proportional valve, the MEMS ultrasonic flow meter, the standard flow meter and the temperature and pressure sensor. The heating device and the gas flow generator are coupled to the detection platform. The intelligent control terminal is arranged on one side of the detection platform and is electrically connected to the gas flow generator, the heating device, the temperature and pressure sensor, the MEMS ultrasonic flow meter, the standard flow meter and the MFC proportional valve respectively.

2. A multi-temperature and multi-pressure intelligent flowmeter calibration method, applied to the multi-temperature and multi-pressure intelligent flowmeter calibration platform as claimed in claim 1, characterized in that: The steps include: The intelligent control terminal is used to set parameters, establish the temperature, pressure and flow values of the test bench, and complete the setting of the test conditions; Acquiring data from the standard flow meter and calibrating the data to form reference data; Collecting data from the MEMS ultrasonic flow meter and recording the data; Comparing data of the standard flow meter and the MEMS ultrasonic flow meter, calculating errors to form data points; Collect data points to form a data set, which serves as the basis for AI modeling training.

3. The multi-temperature and multi-pressure intelligent flowmeter calibration method according to claim 2, characterized in that: In the step of setting parameters by using the intelligent control terminal, constructing the temperature, pressure and flow values of the test bench, and completing the setting of the test conditions: The intelligent control terminal sends a control instruction to the MFC proportional valve to set a target flow value; Synchronously control the heating device to set a target temperature and maintain a constant temperature through PID control; The gas pressure is set by the pressure stabilizing device to complete the initialization of the test environment.

4. The multi-temperature and multi-pressure intelligent flowmeter calibration method according to claim 2, characterized in that: In the step of obtaining data from the standard flow meter and calibrating the data to form reference data: Obtain the accurate value of the current flow rate from the standard flow meter as a reference value for this test; At the same time, read the real-time feedback values of the temperature and pressure sensors and confirm that the environment is stable.

5. The multi-temperature and multi-pressure intelligent flowmeter calibration method according to claim 2, characterized in that: In the step of collecting data from the MEMS ultrasonic flowmeter and recording the data: Collecting the MEMS ultrasonic flowmeter and upstream / downstream TOF time; Obtaining the current value of the temperature and pressure sensor; The actual sound velocity of the gas at the scene under this state is detected and recorded, and the instantaneous flow value is calculated based on the value of the MEMS ultrasonic flow.

6. The multi-temperature and multi-pressure intelligent flowmeter calibration method according to claim 2, characterized in that: In the step of comparing the data of the standard flow meter and the MEMS ultrasonic flow meter and calculating the error to form data points: The intelligent control terminal compares the output value of the MEMS ultrasonic flow meter with a standard reference value and calculates an error value; Parameter records are packaged as data points.

7. The multi-temperature and multi-pressure intelligent flowmeter calibration method according to claim 2, characterized in that: In the step of collecting data points to form a dataset as the basis for AI model training: Repeat sampling several times at the set point, perform average processing, and improve data support; The system saves the data as a labeled dataset for subsequent AI modeling training.

Images