Ultrasonic gas meter with novel calibration model and calibration method thereof

Abstract

The invention relates to the technical field of gas metering, and discloses an ultrasonic gas meter with a novel calibration model and a calibration method thereof.The ultrasonic gas meter comprises an ultrasonic sensor module used for calculating the flow velocity by measuring the propagation time difference of ultrasonic waves in a gas medium; the signal processing module is used for amplifying, filtering and digitally converting the received ultrasonic signals; the microprocessor module is used for calculating and controlling the collected data; and the communication module is used for realizing data communication and system management with a remote server. By introducing a self-adaptive calibration model, a calibration coefficient can be dynamically adjusted according to real-time environmental parameters (such as temperature, pressure and fuel gas components), environmental data are collected through auxiliary sensors such as a temperature sensor and a pressure sensor, and real-time compensation is realized in combination with a machine learning model; and it is ensured that the gas meter can keep high measurement precision under different working conditions.

Description

Technical Field

[0001] The present invention relates to the technical field of gas metering, and specifically to an ultrasonic gas meter with a new calibration model and its calibration method. Background Art

[0002] An ultrasonic gas meter is a metering device that calculates gas flow by measuring the propagation time of ultrasonic waves in a gas medium. Existing ultrasonic gas meters usually adopt fixed calibration methods, most of which are based on initial laboratory calibration and cannot adapt to the dynamic changes of the environment during actual operation. The measurement accuracy of gas flow is affected by various factors such as temperature, pressure, and gas composition. Especially in different application scenarios such as residential, commercial, and industrial, the frequent changes in environmental parameters make the existing technologies have obvious deficiencies in terms of accuracy and stability.

[0003] Existing ultrasonic gas meters are calibrated through laboratory calibration before leaving the factory and use fixed calibration coefficients to compensate for errors. However, this static calibration method cannot effectively cope with changes in gas composition, temperature, and pressure during actual use; due to the lack of self - adaptability of the calibration coefficients, when environmental conditions change (such as temperature changes, seasonal alternations, etc.), the system fails to adjust the compensation parameters in real time, resulting in an increase in measurement errors and significantly affecting the accuracy of flow measurement. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides an ultrasonic gas meter with a new calibration model and its calibration method, which solves the problem that the static calibration method cannot effectively cope with changes in gas composition, temperature, and pressure during actual use.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: An ultrasonic gas meter with a new calibration model, comprising: An ultrasonic sensor module for calculating the flow velocity by measuring the time difference of ultrasonic wave propagation in a gas medium; A signal processing module for amplifying, filtering, and digitally converting the received ultrasonic signals; A microprocessor module for calculating and controlling the collected data; A communication module for realizing data communication and system management with a remote server.

[0006] Preferably, the ultrasonic sensor module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, and a sensor protection unit; The ultrasonic transmitting unit includes a transmitter drive circuit and a transmitter crystal, and the transmitter drive circuit uses pulse current technology to stabilize the power and frequency of the transmitted signal; The ultrasonic receiving unit includes a receiver amplifier circuit and a receiver crystal. The receiver amplifier circuit uses low-noise amplification technology to amplify the received signal and ensure the sensitivity of the signal. The sensor protection unit includes a protective cover and a temperature adjustment device. The protective cover is made of corrosion-resistant material, and the temperature adjustment device uses PTC components to protect the sensor from the external environment and keep it working properly under low-temperature conditions.

[0007] Preferably, the signal processing module includes a signal amplification unit, a filtering unit, and a digital conversion unit. The signal amplification unit includes a low-noise amplifier and a variable-gain amplifier. The low-noise amplifier uses weak-signal enhancement technology to amplify weak signals and adaptively adjust the gain. The variable-gain amplifier optimizes the signal dynamic range by controlling the gain of the input signal. The filtering unit includes a high-pass filter and a low-pass filter. The high-pass filter uses a passive inductance-capacitance design to remove low-frequency interference, and the low-pass filter is used to remove high-frequency noise. The filtering unit further includes a band-pass filter for retaining signals within the target frequency range. The digital conversion unit includes an analog-to-digital converter and a sample-and-hold circuit. The analog-to-digital converter uses successive approximation conversion technology to convert analog signals into digital signals and maintains signal stability through the sample-and-hold circuit. The ADC has a resolution of more than 12 bits, and the sample-and-hold circuit uses low-leakage capacitors to ensure the stability of the sampled signals.

[0008] Preferably, the microprocessor module includes a data acquisition unit, a calculation and control unit, and a storage unit. The data acquisition unit includes a multi-channel collector and a data buffer. The multi-channel collector uses multiplexing technology to collect data from multiple sensors and temporarily store them. The data buffer uses a FIFO (First In First Out) structure to process data in an orderly manner. The calculation and control unit includes flow calculation, error correction, and control logic. The flow calculation uses the time-difference algorithm, and its flow calculation formula is:

[0009] where Q represents the gas flow rate, K is the calibration coefficient, L is the length of the ultrasonic propagation path, and t2 and t1 are the times for ultrasonic waves to propagate downstream and upstream respectively. The error correction uses a data-driven error compensation method, and its error correction formula is:

[0010] Among them, Ecorr represents the error correction value, T is the temperature, P is the pressure, C is the gas composition, and f is the error compensation function, which is continuously updated through a machine learning model and is used to calculate the gas flow rate in real time, correct the measurement error, and achieve the intelligent control of the system; the calculation and control unit integrates a digital signal processor to accelerate complex mathematical operations; The storage unit includes a non-volatile memory and a data recording memory. The non-volatile memory uses Flash storage technology and is used to store system configuration parameters and historical measurement data; the data recording memory has a circular storage function and is used to record data for a long time.

[0011] Preferably, the communication module includes a wireless communication unit, a wired communication unit, and a remote management unit; The wireless communication unit includes NB-IoT and LoRa. NB-IoT uses low-power wide-area network communication technology for remote data transmission, and LoRa is used for long-distance communication; The wired communication unit includes an RS485 interface and an Ethernet interface. The RS485 interface uses differential signal transmission technology for communication with industrial equipment, and the Ethernet interface is used for communication with the host computer; The remote management unit includes OTA over-the-air download and fault diagnosis. OTA uses remote firmware update technology for remote system software update, and the fault diagnosis module is used to diagnose system faults.

[0012] Preferably, the calibration method of the ultrasonic gas meter with a new calibration model includes the following steps: S1. Initial calibration Equipment installation: Install the ultrasonic gas meter on the test bench; Initial data collection: Turn on the gas flow, and collect the initial ultrasonic propagation time data, the upstream time t1 and the downstream time t2, through the ultrasonic sensor; Static calibration: According to the standard gas flow rate, under static conditions, by comparing the true flow rate value Q 实际 and the measured flow rate value Q 测量 to determine the calibration coefficient K so that the calculation formula satisfies:

[0013] S2. Dynamic calibration Environmental data collection: During actual use, collect the environmental parameters affecting the flow measurement in real time, including the temperature T, the pressure P, and the gas composition C; Error modeling: Use a machine learning model to analyze the collected environmental data and establish a measurement error model. The error correction formula is:

[0014] Among them, f is a compensation function obtained through machine learning training, which is used to correct the measurement error caused by environmental changes; S3. Real-time calibration Flow calculation and error correction: During normal use, calculate the ultrasonic propagation time difference t2 - t1 to obtain the real-time flow rate Q, and combine it with the error correction model:

[0015] Among them, Q_corrected is the flow rate value after correction; S4. Online learning and model update Data feedback and model optimization: Utilize the data collected in the long term to continuously optimize the error compensation model. Compare the newly collected temperature, pressure, and gas component data with the actual measurement values, which are used to train and update the machine learning model, making the error compensation function f more accurate; Adaptive adjustment: After the model is optimized, apply the calibration model to the ultrasonic gas meter through remote firmware update OTA to ensure that the gas meter can adapt to environmental changes; S5. Fault detection and self-diagnosis Fault monitoring: Real-time monitor the status of the ultrasonic sensor, including signal intensity and sensor operating temperature. When an abnormal signal intensity or abnormal environmental parameter is detected, start the self-diagnosis program; Alarm and maintenance: When a major deviation or fault is found, send an alarm message to the remote server through the communication module.

[0016] The present invention provides an ultrasonic gas meter with a new calibration model and its calibration method. It has the following beneficial effects: 1. The present invention introduces an adaptive calibration model, which can dynamically adjust the calibration coefficient according to real-time environmental parameters (such as temperature, pressure, and gas components). Collect environmental data through auxiliary sensors such as temperature sensors and pressure sensors, and combine with the machine learning model to achieve real-time compensation, ensuring that the gas meter can maintain a high measurement accuracy under different working conditions. By using a data-driven calibration model, it can learn and capture non-linear relationships, reducing the error of gas flow measurement. Especially under the condition of large fluctuations in environmental conditions, it can still maintain stable flow measurement.

[0017] 2. The present invention uses machine learning methods to construct an error compensation model. Through continuous iteration and optimization of machine learning, the calibration model can continuously learn the relationship between environmental parameters and errors, thereby providing more accurate correction and meeting the requirements of high-precision application scenarios.

[0018] 3. The gas meter of the present invention integrates a remote communication module and an OTA (Over-the-Air) update function, enabling the system to update and optimize the calibration model through the cloud. Without on-site manual intervention, the system can perform self-calibration and model improvement through remote firmware updates (OTA). This ability of automated calibration and remote maintenance greatly reduces the need for daily maintenance and on-site manual calibration, reduces operating costs, improves the reliability and service life of the gas meter, and reduces the dependence on technicians. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a system architecture diagram of an ultrasonic gas meter with a new calibration model of the present invention; Figure 2 It is a system architecture diagram of the ultrasonic sensor module of the present invention; Figure 3 It is a system architecture diagram of the signal processing module of the present invention; Figure 4 It is a system architecture diagram of the microprocessor module of the present invention; Figure 5 It is a system architecture diagram of the communication module of the present invention; Figure 6 It is a flowchart of the calibration method of the ultrasonic gas meter with a new calibration model of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions of the present invention will be clearly and completely described in conjunction with the drawings of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0021] Please refer to the attached Figure 1 - attached Figure 5 , the embodiments of the present invention provide an ultrasonic gas meter with a new calibration model, including: An ultrasonic sensor module for calculating the flow rate by measuring the time difference of ultrasonic wave propagation in the gas medium; A signal processing module for amplifying, filtering, and digitally converting the received ultrasonic signal; A microprocessor module for calculating and controlling the collected data; A communication module for realizing data communication and system management with a remote server.

[0022] The ultrasonic sensor module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, and a sensor protection unit; The ultrasonic transmitting unit includes a transmitter driving circuit and a transmitter crystal. The transmitter driving circuit uses pulse current technology to stabilize the power and frequency of the transmitted signal. The ultrasonic receiving unit includes a receiver amplifying circuit and a receiver crystal. The receiver amplifying circuit uses low-noise amplification technology to amplify the received signal and ensure the signal sensitivity. The sensor protection unit includes a protective cover and a temperature regulating device. The protective cover is made of corrosion-resistant material, and the temperature regulating device uses PTC components to protect the sensor from the external environment and keep it working properly under low-temperature conditions.

[0023] Specifically, the ultrasonic sensor module is used to calculate the gas flow rate by measuring the time difference of ultrasonic wave propagation in the gas medium. It consists of the following units: Ultrasonic transmitting unit: It includes a transmitter driving circuit and a transmitter crystal. The transmitter driving circuit uses pulse current technology to drive the piezoelectric ceramic crystal to generate a stable and high-power ultrasonic signal. The ultrasonic signal propagates along the gas pipeline, and the stability of the propagation path directly affects the measurement accuracy of the gas meter.

[0024] Ultrasonic receiving unit: It consists of a receiver amplifying circuit and a receiver crystal. After the receiver crystal receives the ultrasonic signal, the signal is very weak, so it needs to be amplified by a low-noise amplifying circuit to ensure the effectiveness of the signal. The material and design of the receiver crystal ensure its sensitivity under different flow conditions.

[0025] Sensor protection unit: It includes a protective cover and a temperature regulating device. The protective cover is made of corrosion-resistant material to protect the sensor from gas impurities, moisture and corrosion. The temperature regulating device uses PTC (positive temperature coefficient) components to heat the sensor under low-temperature conditions to ensure its stable operation.

[0026] The signal processing module includes a signal amplifying unit, a filtering unit and a digital conversion unit; The signal amplifying unit includes a low-noise amplifier and a variable-gain amplifier. The low-noise amplifier uses weak signal enhancement technology to amplify weak signals and adaptively adjust the gain; the variable-gain amplifier optimizes the signal dynamic range by controlling the gain of the input signal. The filtering unit includes a high-pass filter and a low-pass filter. The high-pass filter uses a passive inductance-capacitance design to remove low-frequency interference, and the low-pass filter is used to remove high-frequency noise; The filtering unit also includes a band-pass filter for retaining signals within the target frequency range; The digital conversion unit includes an analog-to-digital converter and a sample-and-hold circuit. The analog-to-digital converter adopts successive approximation conversion technology to convert analog signals into digital signals and maintains signal stability through the sample-and-hold circuit; the ADC has a resolution of more than 12 bits, and the sample-and-hold circuit uses low-leakage capacitors to ensure the stability of the sampled signal.

[0027] Specifically, the signal processing module processes the received ultrasonic signals to extract effective information and converts it into data that can be understood by the microprocessor. The signal processing module includes the following units: Signal amplification unit: It consists of a low-noise amplifier (LNA) and a variable-gain amplifier (VGA). The LNA is used to enhance weak signals, and its design is based on the requirement of reducing noise to minimize signal distortion caused by external interference. The VGA is used to adaptively amplify signals of different intensities, and maintains the dynamic range of the signal by adjusting the gain to ensure linear response within different flow ranges.

[0028] Filtering unit: It includes a high-pass filter, a low-pass filter, and a band-pass filter. The high-pass filter is used to remove low-frequency background noise such as vibration and environmental noise; the low-pass filter is used to remove high-frequency electronic noise; the band-pass filter is used to retain only signals within a specific frequency range to ensure that only effective signals of the target frequency are processed.

[0029] Digital conversion unit: It includes an analog-to-digital converter (ADC) and a sample-and-hold circuit. The ADC adopts successive approximation register (SAR) technology to convert analog signals into digital signals for processing by the microprocessor. The resolution of the ADC is 12 bits or higher to ensure high-precision signal conversion. The sample-and-hold circuit is used to maintain signal stability during the ADC conversion process and avoid signal fluctuations from affecting the conversion accuracy.

[0030] The microprocessor module includes a data acquisition unit, a calculation and control unit, and a storage unit; The data acquisition unit includes a multi-channel collector and a data buffer. The multi-channel collector uses multiplexing technology to collect data from multiple sensors and temporarily store it; the data buffer adopts a first-in-first-out (FIFO) structure to enable orderly processing of data; The calculation and control unit includes flow calculation, error correction, and control logic. The flow calculation uses the time-difference algorithm, and its flow calculation formula is:

[0031] Where Q represents the gas flow rate, K is the calibration coefficient, L is the length of the ultrasonic propagation path, and t2 and t1 are the propagation times of the ultrasonic wave downstream and upstream respectively; Error correction adopts a data-driven error compensation method, and its error correction formula is:

[0032] Among them, Ecorr represents the error correction value, T is the temperature, P is the pressure, C is the gas composition, and f is the error compensation function, which is continuously updated through a machine learning model and is used to calculate the gas flow rate in real time, correct the measurement error, and achieve the intelligent control of the system; the calculation and control unit integrates a digital signal processor to accelerate complex mathematical operations; The storage unit includes a non-volatile memory and a data recording memory. The non-volatile memory uses Flash storage technology and is used to store system configuration parameters and historical measurement data; the data recording memory has a circular storage function and is used to record data for a long time.

[0033] Specifically, the microprocessor module is the core of the ultrasonic gas meter and is used to implement the functions of measurement, control, and data processing, and includes the following units: Data acquisition unit: It includes a multi-channel collector and a data buffer. The multi-channel collector uses multiplexing technology and is used to collect data of multiple sensors such as ultrasonic signals, temperature, and pressure at the same time. The data buffer uses a FIFO structure to ensure the order and real-time performance of data processing and avoid data loss.

[0034] Calculation and control unit: It includes a flow rate calculation module, an error correction module, and a control logic unit. The flow rate calculation module calculates the flow rate based on the time difference algorithm, and its formula is:

[0035] Among them, Q represents the gas flow rate, K is the calibration coefficient, L is the length of the ultrasonic propagation path, and t2 and t1 are the propagation times of the ultrasonic wave downstream and upstream respectively; the error correction module is based on a data-driven error compensation method, and by collecting environmental parameters (such as temperature, pressure, gas composition) in real time, it dynamically updates the error compensation function in combination with a machine learning model:

[0036] Among them, Ecorr represents the error correction value, T is the temperature, P is the pressure, C is the gas composition, and f is the error compensation function. The control logic unit performs complex operations through a digital signal processor (DSP) to improve the real-time response ability of the system.

[0037] Storage unit: It includes a non-volatile memory and a data recording memory. The non-volatile memory uses Flash storage technology and is mainly used to store key data such as system configuration parameters and calibration models; the data recording memory uses a circular storage structure and is used to record gas data for a long time for analysis and traceability, and at the same time ensures that the data is not lost in the case of power failure.

[0038] The communication module includes a wireless communication unit, a wired communication unit, and a remote management unit; The wireless communication unit includes NB-IoT and LoRa. NB-IoT uses low-power wide-area network communication technology for remote data transmission, and LoRa is used for long-distance communication; The wired communication unit includes an RS485 interface and an Ethernet interface. The RS485 interface uses differential signal transmission technology for communication with industrial devices, and the Ethernet interface is used for communication with the host computer; The remote management unit includes OTA (Over-the-Air) and fault diagnosis. OTA uses remote firmware update technology for remotely updating system software, and the fault diagnosis module is used to diagnose system faults.

[0039] Specifically, the communication module realizes data communication and system management functions between the gas meter and the remote server, and includes the following units: Wireless communication unit: It includes an NB-IoT module and a LoRa module. The NB-IoT module uses low-power wide-area network technology and is suitable for transmitting a small amount of data and remote monitoring scenarios. The LoRa module is used for long-distance data transmission and is especially suitable for application environments covering long distances.

[0040] Wired communication unit: It includes an RS485 interface and an Ethernet interface. The RS485 interface uses differential signal transmission technology for stable data communication with industrial devices, and the Ethernet interface is used to achieve high-speed data communication between the gas meter and the host computer system.

[0041] Remote management unit: It includes an OTA (Over-the-Air) module and a fault diagnosis module. The OTA module is used to achieve remote firmware update to ensure that the gas meter can upgrade the calibration model and software functions at any time; the fault diagnosis module is used to monitor the working state of the gas meter in real time and send fault information to the remote server when an abnormality is detected for timely processing.

[0042] The above modules and units constitute a complete ultrasonic gas meter system with a new calibration model. Each module cooperates with each other. The signal processing module amplifies, filters, and digitally converts the received signal, and the microprocessor module analyzes the data, corrects errors, and calculates the flow rate. The communication module is used for remote data transmission and management.

[0043] Please refer to the appendix Figure 6 , and the calibration method of the ultrasonic gas meter with a new calibration model includes the following steps: S1. Initial calibration Equipment installation: Install the ultrasonic gas meter on the test bench to ensure that the gas flow conditions and the installation of the sensor meet the standard requirements; Initial data collection: Turn on the gas flow and collect the initial ultrasonic propagation time data, i.e., the upstream time t1 and the downstream time t2, through the ultrasonic sensor. Static calibration: According to the standard gas flow rate, under static conditions, determine the calibration coefficient K by comparing the true flow rate value Q 实际 and the measured flow rate value Q 测量 to make the calculation formula satisfy:

[0044] S2. Dynamic calibration Environmental data collection: During actual use, collect in real time the environmental parameters that affect the flow measurement, including the temperature T, pressure P, and gas composition C. Error modeling: Use a machine learning model to analyze the collected environmental data and establish a measurement error model. The error correction formula is:

[0045] where f is a compensation function obtained through machine learning training, which is used to correct the measurement error caused by environmental changes. S3. Real-time calibration Flow calculation and error correction: During normal use, calculate the ultrasonic propagation time difference t2 - t1 to obtain the real-time flow rate Q, and combine it with the error correction model:

[0046] where Qcalibrated is the flow rate value after calibration. S4. Online learning and model update Data feedback and model optimization: Use the data collected in the long term to continuously optimize the error compensation model. Compare the newly collected temperature, pressure, and gas composition data with the actual measurement values for training and updating the machine learning model, so that the error compensation function f is more accurate.

[0047] Adaptive adjustment: After the model is optimized, apply the calibration model to the ultrasonic gas meter through over-the-air (OTA) remote firmware update to ensure that the gas meter can adapt to environmental changes. S5. Fault detection and self-diagnosis Fault monitoring: Monitor the status of the ultrasonic sensor in real time, such as signal strength, sensor operating temperature, etc. Once an abnormal signal strength or abnormal environmental parameter is detected, start the self-diagnosis program.

[0048] Alarm and maintenance: If a major deviation or fault is found, send an alarm message to the remote server through the communication module for timely maintenance.

[0049] Although embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An ultrasonic gas meter with a new calibration model, characterized in that Including: An ultrasonic sensor module for calculating the flow rate by measuring the time difference of ultrasonic wave propagation in the gas medium; A signal processing module for amplifying, filtering, and digitally converting the received ultrasonic signals; A microprocessor module for calculating and controlling the collected data; A communication module for realizing data communication and system management with the remote server.

2. The ultrasonic gas meter with a new calibration model according to claim 1, characterized in that, The ultrasonic sensor module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, and a sensor protection unit; The ultrasonic transmitting unit includes a transmitter driving circuit and a transmitter crystal, and the transmitter driving circuit uses pulse current technology to stabilize the power and frequency of the transmitted signal; The ultrasonic receiving unit includes a receiver amplifying circuit and a receiver crystal, and the receiver amplifying circuit uses low-noise amplification technology to amplify the received signal and ensure the sensitivity of the signal; The sensor protection unit includes a protective cover and a temperature regulating device. The protective cover is made of corrosion-resistant material, and the temperature regulating device uses a PTC element to protect the sensor from the external environment and keep it working normally under low-temperature conditions.

3. The ultrasonic gas meter with a new calibration model according to claim 1, characterized in that, The signal processing module includes a signal amplifying unit, a filtering unit, and a digital conversion unit; The signal amplifying unit includes a low-noise amplifier and a variable gain amplifier. The low-noise amplifier uses weak signal enhancement technology to amplify weak signals and adaptively adjust the gain; the variable gain amplifier optimizes the signal dynamic range by controlling the gain of the input signal; The filtering unit includes a high-pass filter and a low-pass filter. The high-pass filter uses a passive inductance-capacitance design to remove low-frequency interference, and the low-pass filter is used to remove high-frequency noise; The filtering unit further includes a band-pass filter for retaining signals within the target frequency range; The digital conversion unit includes an analog-to-digital converter and a sample-and-hold circuit. The analog-to-digital converter uses successive approximation conversion technology to convert analog signals into digital signals and maintains the signal stability through the sample-and-hold circuit; the ADC has a resolution of more than 12 bits, and the sample-and-hold circuit uses low-leakage capacitance to ensure the stability of the sampled signal.

4. The ultrasonic gas meter with a new calibration model according to claim 1, characterized in that, The microprocessor module includes a data acquisition unit, a calculation and control unit, and a storage unit; The data acquisition unit includes a multi-channel collector and a data buffer. The multi-channel collector uses multiplexing technology to collect data from multiple sensors and temporarily store them; the data buffer uses a FIFO (First In First Out) structure to process data in an orderly manner; The calculation and control unit includes flow rate calculation, error correction, and control logic. The flow rate calculation uses the time difference algorithm, and its flow rate calculation formula is: ； Where Q represents the gas flow rate, K is the calibration coefficient, L is the length of the ultrasonic propagation path, and t2 and t1 are the propagation times of the ultrasonic wave downstream and upstream respectively; The error correction uses a data-driven error compensation method, and its error correction formula is: ； Among them, Ecorr represents the error correction value, T is the temperature, P is the pressure, C is the gas composition, and f is the error compensation function, which is continuously updated through a machine learning model and is used to calculate the gas flow rate in real time, correct the measurement error, and achieve the intelligent control of the system; the calculation and control unit integrates a digital signal processor to accelerate complex mathematical operations; The storage unit includes a non-volatile memory and a data recording memory. The non-volatile memory uses Flash storage technology and is used to store system configuration parameters and historical measurement data; the data recording memory has a circular storage function and is used to record data for a long time.

5. The ultrasonic gas meter with a new calibration model according to claim 1, characterized in that, The communication module includes a wireless communication unit, a wired communication unit, and a remote management unit; The wireless communication unit includes NB-IoT and LoRa. NB-IoT uses low-power wide-area network communication technology for remote data transmission, and LoRa is used for long-distance communication; The wired communication unit includes an RS485 interface and an Ethernet interface. The RS485 interface uses differential signal transmission technology for communication with industrial equipment, and the Ethernet interface is used for communication with the upper computer; The remote management unit includes OTA over-the-air download and fault diagnosis. OTA uses remote firmware update technology to remotely update the system software, and the fault diagnosis module is used to diagnose system faults.

6. Calibration method for an ultrasonic gas meter with a new calibration model, characterized in that, For the ultrasonic gas meter with a novel calibration model according to any one of claims 1-5, it includes the following steps: S1. Initial calibration Equipment installation: Install the ultrasonic gas meter on the test bench; Initial data collection: Turn on the gas flow, and collect the initial ultrasonic propagation time data, the upstream time t1 and the downstream time t2, through the ultrasonic sensor; Static calibration: According to the standard gas flow rate, under static conditions, by comparing the true flow rate value Q 实际 and the measured flow rate value Q 测量 to determine the calibration coefficient K such that the calculation formula satisfies: ； S2. Dynamic calibration Environmental data collection: During actual use, collect the environmental parameters affecting the flow measurement in real time, including the temperature T, the pressure P, and the gas composition C; Error modeling: Use a machine learning model to analyze the collected environmental data and establish a measurement error model. The error correction formula is: ； Among them, f is a compensation function obtained through machine learning training and is used to correct the measurement error caused by environmental changes; S3. Real-time calibration Flow calculation and error correction: During normal use, calculate the ultrasonic propagation time difference t2−t1 to obtain the real-time flow rate Q, and combine the error correction model: ； Among them, Q corrected is the corrected flow rate value; S4. Online learning and model update Data feedback and model optimization: Use the data collected for a long time to continuously optimize the error compensation model, compare the newly collected temperature, pressure, and gas composition data with the actual measurement values, and use them to train and update the machine learning model to make the error compensation function f more accurate; Adaptive adjustment: After the model is optimized, apply the calibration model to the ultrasonic gas meter through OTA remote firmware update to ensure that the gas meter can adapt to environmental changes; S5. Fault detection and self-diagnosis Fault monitoring: Monitor the status of the ultrasonic sensor in real time, including the signal strength and the sensor operating temperature, and start the self-diagnosis program when an abnormal signal strength or abnormal environmental parameters are detected; Alarm and Maintenance: When major deviations or faults are detected, alarm information is sent to the remote server through the communication module.

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