Gas flow metering terminal based on remote communication

Abstract

The present application relates to the technical field of gas pipe network monitoring and metering, and discloses a gas flow metering terminal based on remote communication, comprising an intelligent analysis and early warning platform and the gas flow metering terminal. A multi-range collaborative metering module is arranged in the terminal and is composed of different pipe diameter ultrasonic flow meters and independent cut-off valves in parallel; the fluid state is mapped by extracting ultrasonic acoustic characteristics, and the cloud end blockage alarm logic is matched with the upstream valve action period to eliminate system false alarms caused by fluid transmission time difference; according to the boundary reconstruction instruction, the valve is controlled to switch between opening and closing to measure the gas data collected by the small pipe diameter measuring branch alone, and the reconstruction parameters are provided for the platform to perform regional balance calculation and solve the measurement drift defect caused by the flow fluctuation; the module is adjusted to a high-frequency sampling state to cooperate with the execution of pipe network micro-perturbation detection, and the transient waveform parameters are extracted for the platform to complete the abnormal source space pipe length distance accurate solution.

Description

Technical Field

[0001] This invention relates to the field of gas pipeline network monitoring and metering technology, specifically a gas flow metering terminal based on remote communication. Background Technology

[0002] The digital operation of gas pipeline networks relies heavily on gas flow metering terminals based on remote communication. In typical regional balance monitoring scenarios, metering terminals distributed across various nodes of the pipeline network periodically collect gas flow data and transmit it back to the cloud platform. The platform then compares the total input gas volume with the accumulated gas volume at each output node, thereby enabling pipeline transmission differential calculation and status monitoring.

[0003] However, in long-term actual operation, pipeline fluids may experience free droplet precipitation and compositional changes due to gas source switching or drastic changes in ambient temperature. Such unsteady changes in the flow field directly interfere with the physical sound transmission rate and trigger the adjustment actions of pipeline equipment. Existing monitoring systems lack a coordinated understanding of local characteristic parameters and the overall physical action cycle. When upstream valves in the pipeline perform adjustment actions in response to changes in gas quality, there is an inevitable fluid dynamic transmission time difference in the transmission of pressure waves and flow changes to downstream remote metering nodes. If the system continues to use data with spatiotemporal misalignment to perform strict balance calculations, it is very easy to trigger false alarms in the regional balance judgment logic due to the time lag of the data.

[0004] With the dramatic fluctuations in regional gas load, local flow rates in the pipeline network may drop sharply at certain times. Existing single-diameter metering terminals are often forced to operate at the lower limit of their range or even in dead zones when faced with low flow conditions. Due to the inherent physical range ratio limit of the instrument, the collected flow parameters will experience severe accuracy drift. This type of hardware topology with fixed physical boundaries cannot adapt to changes in the flow environment, causing the differential calculation mechanism originally used to diagnose the physical health status of the pipeline network to completely fail due to the distortion of the basic collected data. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a gas flow metering terminal based on remote communication. This solves the problems of existing gas metering terminals in complex pipeline network conditions, such as frequent false alarms and failures of the regional balance monitoring mechanism due to fluid transmission time difference and instrument accuracy drift, and the inability of the fixed low-frequency sampling mechanism to capture micro-perturbation wave characteristics, which leads to the failure of physical location of pipeline network anomaly sources.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a gas flow metering terminal based on remote communication, comprising: a multi-range collaborative metering module, a remote communication module, and a logic control unit. The multi-range collaborative metering module includes a first-diameter ultrasonic flow meter and a second-diameter ultrasonic flow meter connected in parallel via a manifold, and independent shut-off valves respectively located on the corresponding pipeline branches of the first-diameter and second-diameter ultrasonic flow meters. The upper limit of the measurement range of the first-diameter ultrasonic flow meter is greater than the upper limit of the measurement range of the second-diameter ultrasonic flow meter. The multi-range collaborative metering module is used to periodically collect gas flow data and the sound velocity of the pipeline medium at a first sampling frequency, and extract the underlying acoustic characteristic parameters of the first-diameter and second-diameter ultrasonic flow meters. The underlying acoustic characteristic parameters include ultrasonic signal gain and signal-to-noise ratio.

[0007] The remote communication module includes a built-in battery power supply circuit and a wireless data transmission circuit, which is connected to the multi-range collaborative metering module. It is used to send the gas flow data, the pipeline medium sound velocity and the underlying acoustic characteristic parameters to the remote intelligent analysis and early warning platform, and to receive collaborative control commands issued by the intelligent analysis and early warning platform.

[0008] The logic control unit is connected to the independent shut-off valve of the remote communication module and the multi-range collaborative metering module respectively. It is used to control the opening and closing of the independent shut-off valve according to the parsed collaborative control command to realize branch switching. When receiving the corresponding command, it forces the sampling frequency of the multi-range collaborative metering module to be adjusted from the low-power first sampling frequency to a second sampling frequency greater than the first sampling frequency. Thus, when the electric flow regulating valve upstream of the pipeline performs gas quality change feedforward control and active micro-disturbance detection, it performs collaborative metering operation.

[0009] The multi-range collaborative metering module is configured to continuously acquire the gas flow data upon receiving a gas quality change feedforward control trigger command. The gas quality change feedforward control is triggered by the intelligent analysis and early warning platform when it determines that the signal-to-noise ratio is lower than a preset baseline signal-to-noise ratio threshold and the ultrasonic signal gain is higher than a preset baseline gain alarm threshold. For this unsteady flow field environment, the gas flow data continuously uploaded by the remote communication module during the gas quality change feedforward control period is configured to allow the intelligent analysis and early warning platform to pause triggering of abnormal output alarm logic for this area during the adjustment cycle of issuing an increase opening command to the upstream electric flow regulating valve, thereby eliminating false alarms caused by fluid dynamic time differences.

[0010] The collaborative control command includes an adaptive boundary reconstruction command. This command is generated by the intelligent analysis and early warning platform during regional balance monitoring, based on the determination result that the actual relative transmission difference rate of the region exceeds the theoretical maximum allowable synthetic error limit. The actual relative transmission difference rate of the region is generated by the intelligent analysis and early warning platform using the uploaded gas flow data to perform a deviation calculation involving the total gas input volume of the region and the cumulative gas volume of each output node. In response to the adaptive boundary reconstruction command, the logic control unit controls the independent shut-off valve of the branch where the first diameter ultrasonic flow meter is located to close, and simultaneously controls the independent shut-off valve of the branch where the second diameter ultrasonic flow meter is located to open. This puts the multi-range collaborative metering module in a working state where the second diameter ultrasonic flow meter with a smaller diameter is solely responsible for data acquisition. This allows the intelligent analysis and early warning platform to re-execute the regional balance verification and restore the branch to its state of continuity before receiving the command after the calculation cycle ends.

[0011] The theoretical maximum permissible synthesis error limit is obtained by calculating the following preset synthesis limit mathematical model: ; In the formula, To calculate the theoretical maximum permissible synthesis error limit; The inherent accuracy parameters of the regional input node flow meters are obtained by entering them according to the actual flow calibration and verification certificate of the corresponding flow meters. For the first The inherent accuracy parameters of each output node flow meter are obtained by entering them according to the corresponding flow meter's factory actual flow calibration and verification certificate. Input the total gas volume for the region within the preset time window, and obtain it by integrating the historical metering data collected from the region input nodes; For the first The cumulative gas volume of each output node within the corresponding time window is obtained by scoring based on the historical data records uploaded by the corresponding node. The total number of output nodes in the region is obtained based on the fixed node parameter configuration in the pipeline spatial topology database.

[0012] The coordinated control command also includes a high-frequency sampling command, which corresponds to the active perturbation detection. In response to the high-frequency sampling command, the logic control unit controls the multi-range coordinated metering module to perform high-frequency data acquisition at the second sampling frequency during the period when a transient flow perturbation wave propagates downstream in the pipeline network. This data is extracted from the perturbation waveform sequence, the perturbation wave arrival timestamp, and the waveform attenuation amplitude, and uploaded synchronously. The detection data uploaded by the remote communication module is configured to allow the intelligent analysis and early warning platform to perform cross-correlation function calculations on the injected characteristic control signal and the received perturbation waveform sequence to extract the time delay of the reflected wave. Based on the time delay and the sound velocity of the pipeline medium, a base distance is calculated. The waveform attenuation amplitude is then used to perform nonlinear compensation calibration on the base distance to determine the spatial physical pipe length distance of the pipeline anomaly source.

[0013] The spatial physical pipe length of the pipeline anomaly source is calculated based on the following compensation and correction model: ; In the formula, The spatial physical pipe length distance of the calculated pipeline anomaly source; The base distance is obtained by algebraically multiplying the extracted reflected wave time delay with the speed of sound in the uploaded pipeline medium. The dimensionless correction weighting factor is generated by extracting the attenuation coefficient through regression analysis and performing dimension conversion based on the energy attenuation characteristic curve of the same material pipe section measured in the actual flow test field of the pipeline network. It is then persistently stored in the system constant database. The logarithmic attenuation of the transient wave propagation is calculated by the logarithmic ratio of the initial injected equivalent amplitude and the waveform attenuation amplitude measured at the terminal. The preset reference attenuation decibel value is used to normalize the actual attenuation, and is obtained based on a preset standard constant (e.g., 60dB).

[0014] This invention provides a gas flow metering terminal based on remote communication. It has the following advantages: 1. This invention extracts the ultrasonic signal gain and signal-to-noise ratio to map the fluid component state, combines it with feedforward control logic to maintain the gas flow parameter acquisition operation, and instructs the remote platform to block the transmission error alarm during the upstream regulating valve's execution cycle, thereby eliminating false alarms in regional balance determination caused by the physical transmission time difference of fluid in the pipeline network.

[0015] 2. In this invention, the execution command controls the first diameter shut-off valve to close and the second diameter shut-off valve to open, changing the pipeline conduction state so that the fluid enters the second diameter ultrasonic flow meter to complete the measurement. The output reconstructed parameters are used for remote execution area balance verification, solving the defect of transmission error calculation failure caused by measurement value drift due to changes in operating conditions.

[0016] 3. According to the instructions, the present invention switches the module sampling frequency from the first sampling frequency to the second sampling frequency, and performs micro-disturbance detection in conjunction with the upstream regulating valve. It extracts and uploads the micro-disturbance wave feature parameters for the platform to substitute into the model for distance calculation, thereby making up for the defect of anomaly source localization failure caused by the omission of waveform details in the low-frequency sampling mechanism. Attached Figure Description

[0017] Figure 1 This is a block diagram of the overall system architecture of the gas flow metering terminal based on remote communication according to the present invention. Figure 2 This is a schematic diagram of the pipeline topology of the multi-range collaborative metering module of the present invention; Figure 3 This is a flowchart of the gas mass change feedforward control logic of the present invention; Figure 4 This is a flowchart of the adaptive boundary reconstruction and branch switching control of the present invention; Figure 5 This is a flowchart of the active perturbation detection and anomaly source localization solution of the present invention; Figure 6 This is a schematic diagram of the high and low frequency sampling and waveform attenuation timing of the perturbation detection signal of the present invention. Detailed Implementation

[0018] The technical solutions in 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.

[0019] Please see the appendix Figure 1 To be continued Figure 6 This invention provides a gas flow metering terminal based on remote communication. The terminal is deployed at the metering node of the natural gas transmission and distribution pipeline network to perform online acquisition of fluid state parameters, monitoring of the underlying equipment status, and bidirectional data interaction with the cloud-based intelligent analysis and early warning platform.

[0020] The gas flow metering terminal based on remote communication may include the following core components: a multi-range collaborative metering module, a remote communication module, and a logic control unit.

[0021] The multi-range collaborative metering module includes a fluid transport pipeline assembly and a sensing and measurement assembly. The multi-range collaborative metering module has an upstream manifold, a downstream manifold, and a main measurement branch and a secondary measurement branch connecting the upstream and downstream manifolds. A first-diameter ultrasonic flow meter is installed on the main measurement branch, and a second-diameter ultrasonic flow meter is installed on the secondary measurement branch. The first-diameter ultrasonic flow meter and the second-diameter ultrasonic flow meter are physically connected in parallel through the upstream and downstream manifolds. The pipe diameter and upper limit of the measurement range of the first-diameter ultrasonic flow meter are both larger than those of the second-diameter ultrasonic flow meter, thus forming a metering architecture that meets the requirements of different flow ranges. The system incorporates dynamic range switching logic: when the real-time monitored flow rate is lower than 1.2 times the lower limit of the first-diameter ultrasonic flow meter's range, a low flow switching threshold is triggered, and the system controls the main measurement branch to shut down and the auxiliary measurement branch to open; when the real-time monitored flow rate is higher than 1.5 times the lower limit of the first-diameter ultrasonic flow meter's range, a high flow switching threshold is triggered, and the system controls the auxiliary measurement branch to shut down and the main measurement branch to open. A hysteresis interval is provided between the two to prevent frequent switching. Specifically, the physical span of this hysteresis interval is set between 1.2 and 1.5 times the lower limit of the first-diameter ultrasonic flow meter's range. When the pipeline flow fluctuates within this interval, the system forcibly maintains the current branch's open state until the flow rate exceeds the upper and lower limit thresholds and the duration exceeds a 3-minute anti-shaking cycle before allowing hardware switching. By uniformly anchoring the switching benchmarks of the main and auxiliary branches to the absolute lower limit of the first-diameter ultrasonic flow meter, the continuity of the hysteresis interval and the control loop are ensured.

[0022] In normal operating mode, the multi-range collaborative metering module is in the default single-path operation mode, meaning the first independent shut-off valve of the main measurement branch is open and the second independent shut-off valve of the auxiliary measurement branch is closed. In this mode, the total gas flow calculation logic is: directly taking the instantaneous flow rate of the main path measured by the first-diameter ultrasonic flow meter as the total gas flow rate of this node. Correspondingly, when a low flow switching threshold or adaptive boundary reconstruction command is triggered, causing the auxiliary measurement branch to open and the main measurement branch to close, the total gas flow calculation logic switches to: directly taking the instantaneous flow rate of the auxiliary path measured by the second-diameter ultrasonic flow meter as the total gas flow rate of this node.

[0023] A first independent shut-off valve corresponding to a first-diameter ultrasonic flow meter is connected in series on the main measuring branch, and a second independent shut-off valve corresponding to a second-diameter ultrasonic flow meter is connected in series on the secondary measuring branch. Both the first and second independent shut-off valves include a motor drive mechanism. The motor drive mechanism responds to an external voltage signal to actuate the valve core, thereby independently controlling the physical connection and disconnection of the main and secondary measuring branches, realizing the path switching of fluid between ultrasonic flow meters of different diameters. When performing metering branch switching, the logic control unit follows the timing rule of opening before closing: first, an opening command is sent to the motor drive mechanism of the branch to be connected, and after waiting for 3 seconds to ensure that the valve of the branch to be connected is fully opened and a stable flow field is established, a closing command is sent to the motor drive mechanism of the original connected branch, thereby avoiding medium interruption or pipeline pressure shock during the switching process.

[0024] The remote communication module includes a built-in battery power supply circuit and a wireless data transmission circuit. The built-in battery power supply circuit is connected to the power supply terminals of the multi-range collaborative metering module, the wireless data transmission circuit, and the logic control unit through power cables to maintain the basic power consumption for the independent operation of the entire terminal. The wireless data transmission circuit relies on the radio frequency antenna to establish a wide area network communication link with the intelligent analysis and early warning platform, carrying the uplink transmission of monitoring data and the downlink reception of control commands.

[0025] The multi-range collaborative metering module is internally equipped with an ultrasonic signal transceiver control chip and a digital signal processing chip. The ultrasonic signal transceiver control chip is directly connected to the ultrasonic transducer via an analog front-end to handle physical pulse transmission and reception. Its digital output is connected to the digital signal processing chip via an SPI bus. The detection and extraction algorithm firmware is burned into the on-chip flash memory built into the digital signal processing chip. Both the first-diameter and second-diameter ultrasonic flow meters adopt a dual-channel cross-beam ultrasonic structure. The ultrasonic transducers are installed at a 45-degree angle to the pipe axis on the inner wall of the pipe to fully cover the fluid cross-section. The multi-range collaborative metering module periodically excites the ultrasonic transducers to transmit and receive ultrasonic pulse sequences at a first sampling frequency, and collects gas flow data and the sound velocity of the pipeline medium by combining the time-difference method measurement principle.

[0026] The acoustic fundamental calculation model used for measuring the sound velocity of pipeline media is shown in the following formula:

[0027] In the formula, Defined as the velocity of sound in the pipeline medium. Defined as the physical line segment length of the acoustic channel between the ultrasonic transducer probes, this parameter is obtained by inputting the structural measurement data from the factory flow calibration stage of the multi-range collaborative metering module into the firmware. Defined as the propagation time of an ultrasonic pulse in the downstream direction of the fluid in a pipe. Defined as the propagation time of an ultrasonic pulse in the counter-current direction of the fluid in a pipe. and The values ​​are obtained in real time by the high-speed timer inside the ultrasonic signal transceiver control chip during the first sampling frequency period.

[0028] Meanwhile, for a single channel, the linear velocity of the fluid flowing through the channel... The solution model is as follows:

[0029] In the formula, The length of the vocal tract. The angle between the ultrasonic transducer channel and the central axis of the pipe. For the time of reverse propagation, This refers to the time of downstream propagation.

[0030] Due to the adoption of a dual-channel cross-beam acoustic channel structure, the multi-range collaborative metering module calculates the linear velocity of the first channel separately. With the linear velocity of the second channel The average fluid linear velocity inside the pipe was calculated by applying the Gauss-Jacobi numerical integration method for weighted averaging. The synthesis formula is: The weighting coefficients are derived using Gaussian integral polynomials based on the dimensionless coordinate position of the sound channel from the center plane of the pipe to eliminate the integration error of the asymmetric velocity profile. Then, the average fluid linear velocity inside the pipe is used as the weighting coefficient. Replacement of mono linear velocity Substitute this into the subsequent instantaneous flow model.

[0031] Obtaining linear velocity Then, combined with the cross-sectional area inside the pipe and Reynolds number-related velocity profile correction factor The instantaneous flow rate of the pipe section was calculated. The model is:

[0032] Among them, the velocity profile correction factor Based on pipeline Reynolds number Dynamically calculated to obtain: when the Reynolds number When in laminar flow, take a fixed value. When the Reynolds number When in a turbulent state, the velocity distribution is obtained by fitting a power-law velocity distribution model of fully developed turbulence, and its calculation equation is: The power exponent With Reynolds number The number increases logarithmically as it increases, and this mapping relationship is pre-stored in the device's lookup table matrix; the Reynolds number calculation formula is... ,in For the density of natural gas, The inner diameter of the pipe. The above physical property parameters, representing the dynamic viscosity of natural gas, are pre-entered into the terminal firmware.

[0033] During the synchronization process of extracting time difference parameters, the multi-range collaborative metering module utilizes its built-in signal conditioning circuit and digital signal processing firmware to extract the underlying acoustic characteristic parameters of the first-diameter ultrasonic flow meter and / or the second-diameter ultrasonic flow meter. These underlying acoustic characteristic parameters include ultrasonic signal gain and signal-to-noise ratio (SNR). Ultrasonic signal gain represents the analog amplification factor automatically applied to bring the amplitude of the ultrasonic electrical signal at the receiving end to a predetermined threshold. This predetermined threshold is set to 50% of the full-scale voltage of the analog-to-digital converter; that is, the amplification factor automatically increases when the peak value of the received signal envelope is lower than this fixed reference voltage. The SNR represents the ratio of the effective acoustic signal power to the ambient noise power within the received signal's frequency band. These two parameters directly map the density changes and impurity precipitation states of the gas medium inside the pipeline network. Specifically, when droplet impurities are released from the pipeline fluid, physical scattering causes the SNR to decrease linearly. When the gas density in the pipeline network decreases due to compositional changes, the acoustic coupling efficiency deteriorates, and the automatic gain control circuit exponentially increases the ultrasonic signal gain to maintain the threshold.

[0034] The data interface of the remote communication module connects to the output terminal of the multi-range collaborative metering module. The remote communication module reads gas flow data, pipeline medium sound velocity, and the aforementioned underlying acoustic characteristic parameters in real time. It encrypts and packages this data according to the agreed communication protocol. Specifically, it adopts the MQTT Internet of Things communication protocol and uses the AES-128 symmetric encryption algorithm to encrypt the data payload. The data frame structure includes a frame header, timestamp, device ID, encrypted monitoring data payload, and CRC16 checksum. It is sent to the remote intelligent analysis and early warning platform through a wireless data transmission circuit and listens to the wireless channel in real time to receive collaborative control commands issued by the intelligent analysis and early warning platform after calculation.

[0035] The logic control unit is equipped with an instruction parsing program. The input pins of the logic control unit are connected to the data bus of the remote communication module. The output pins of the logic control unit are respectively connected to the motor drive mechanism of the first independent shut-off valve and the second independent shut-off valve in the multi-range collaborative metering module. According to the parsed collaborative control instruction logic, the logic control unit outputs a switch control signal with a specific timing to control the opening and closing of the corresponding independent shut-off valve to realize the switching of the metering branch.

[0036] The logic control unit is also connected to the clock configuration register of the multi-range collaborative metering module. When the logic control unit receives the corresponding collaborative control command, it writes a new frequency count value to the clock configuration register, forcibly shortening the acquisition cycle of the multi-range collaborative metering module. This causes the sampling frequency to be adjusted from the lower first sampling frequency under normal conditions to a second sampling frequency that is higher than the first sampling frequency. The first sampling frequency is set to 1Hz to reduce normal power consumption, and the second sampling frequency is set to 100Hz to capture high-frequency characteristic signals. This prompts the gas flow metering terminal to enter a high-frequency monitoring state, so that when the electric flow regulating valve upstream of the pipeline performs gas quality change feedforward control and active micro-disturbance detection, it can perform high-frequency collaborative metering operations and complete the acquisition of dense data samples.

[0037] In this embodiment, the intelligent analysis and early warning platform continuously receives the underlying acoustic characteristic parameters reported by the remote communication module to perform real-time monitoring of the fluid composition status in the pipeline network. When the natural gas medium inside the pipeline undergoes component state migration or free droplet precipitation, the sound transmittance of the flow field experiences a downward step, and the ultrasonic signal dissipates energy in the propagation path. In order to maintain the receiver's level amplitude at the trigger threshold, the automatic gain control circuit inside the multi-range collaborative metering module spontaneously increases the gain of the analog amplifier circuit, forming an upward-biased ultrasonic signal gain. At the same time, the physical scattering of sound waves by droplets and the additional broadband noise power introduced by fluid phase change cause the signal-to-noise ratio in the receiving frequency band to fluctuate downwards.

[0038] The intelligent analysis and early warning platform internally hosts a state assessment algorithm program. This program cyclically reads the latest underlying acoustic feature parameters uploaded by the terminal and performs logical threshold comparison operations for preset system parameters. The state assessment algorithm program's internal storage area pre-loads a baseline signal-to-noise ratio (SNR) threshold and a baseline gain alarm threshold. The intelligent analysis and early warning platform executes the following air quality change feedforward trigger logic: When the intelligent analysis and early warning platform determines that the currently received SNR is lower than the baseline SNR threshold and that the currently received ultrasonic signal gain is higher than the baseline gain alarm threshold, and this dual threshold breach condition is continuously met for 5 consecutive sampling cycles as a jitter stabilization judgment rule, the intelligent analysis and early warning platform outputs an internal trigger signal, triggering the system to enter the air quality change feedforward control process.

[0039] The baseline signal-to-noise ratio threshold and the baseline gain alarm threshold are determined based on historical data samples collected from the target pipeline nodes under steady-state operating conditions. The selection rule for historical data samples is to extract steady-state periodic data of the target pipeline nodes in the most recent 30 natural days where no equipment alarms or pressure regulating valve actions have occurred. and Specifically, the unbiased sample standard deviation calculation formula is used for the solution. The intelligent analysis and early warning platform establishes an acoustic parameter baseline model for pipeline measurement points, and the parameter calculation formula is shown below:

[0040]

[0041] In the formula, Defined as a preset baseline signal-to-noise ratio threshold. Defined as a preset reference gain alarm threshold, Defined as the total number of acoustic feature data samples collected during the historical steady-state operation period, this value is obtained by accessing historical stored records in the pipeline network database. Defined as the first The steady-state signal-to-noise ratio value obtained from the second acquisition. Defined as the first The gain value of the steady-state ultrasonic signal acquired in the first acquisition. Defined as the statistical standard deviation of the historical steady-state signal-to-noise ratio sample. Defined as the statistical standard deviation parameter of historical steady-state gain samples; the intelligent analysis and early warning platform uses the above calculation formula to establish the state judgment boundary and filter out parameter fluctuation interference caused by conventional flow field pulsation.

[0042] In this invention, after the intelligent analysis and early warning platform triggers the gas quality change feedforward control process, the fluid state inside the pipeline undergoes a non-steady-state phase transition. The multi-range collaborative metering module, relying on its built-in fault-tolerant measurement firmware, shields the hardware self-test reset command triggered by the underlying acoustic distortion. Specifically, the firmware program acquires the envelope signal of the ultrasonic received echo in real time and compares it with the standard reference lossless envelope curve pre-stored in the memory. The standard reference lossless envelope curve is subjected to 1000 continuous ultrasonic transceiver tests in a pure steady-state flow field environment within a standard sonic nozzle gas flow standard device during the factory calibration stage of the multi-range collaborative metering module. Ideal acoustic waveforms are acquired, their envelope sequences are extracted and arithmetically averaged, and then written as a fixed baseline into the on-chip read-only memory of the digital signal processing chip.

[0043] The acoustic signal envelope distortion rate is defined as the integral of the absolute difference in amplitude between the measured envelope curve and the standard reference envelope curve in the corresponding time series within the current sampling period, divided by the total integral area of ​​the standard reference envelope curve. When the firmware program determines that the acoustic signal envelope distortion rate exceeds 50% within three consecutive sampling periods, it initiates the shielding logic, temporarily suspends the software-level self-test reset logic triggered by the acoustic measurement channel signal-to-noise ratio exceeding the limit, and continues to feed the system watchdog timer to maintain the basic operation of the microprocessor. The intelligent analysis and early warning platform continuously monitors the real-time acoustic parameters and transmission error status of the pipeline network. When the received underlying signal-to-noise ratio rises above the reference signal-to-noise ratio threshold for 10 consecutive sampling periods, and the calculated actual relative transmission error rate of the region recovers to within the theoretical maximum allowable synthesis error limit, the system determines that the fluid phase change interference has disappeared and automatically triggers the exit mechanism: it issues a command to control the electric flow regulating valve to close the previously increased compensation opening, ending the gas quality change feedforward control process; after the terminal confirms that the gas quality change feedforward control has ended and the acoustic envelope has returned to normal for 10 consecutive periods, it exits the shielding logic. The logic control unit outputs a control level to instruct the multi-range collaborative metering module to maintain continuous acquisition of gas flow data during gas quality change feedforward control, force the ultrasonic transducer to continuously perform the transmission and reception of detection signals, generate continuous gas flow data on the time axis, and continuously push a set of measurement results containing flow field state fluctuations to the intelligent analysis and early warning platform through the remote communication module.

[0044] The intelligent analysis and early warning platform receives continuously uploaded gas flow data from the remote communication module during gas quality change feedforward control and initiates a valve collaborative scheduling program for the pipeline network area. The platform issues an opening increase command to the upstream electric flow regulating valve. This command includes an equivalent heat compensation gas volume adjustment value calculated by multiplying the current relative differential flow rate by the pipeline's rated flow rate, and then multiplying by the reciprocal of the ratio of the current gas calorific value to the standard calorific value (i.e., the calorific value compensation coefficient), measured in real-time by an online gas chromatograph. The online gas chromatograph is physically deployed on the bypass sampling branch of the pipeline network's input manifold and connected to the regional industrial control gateway via an RS485 bus. It uploads real-time analyzed gas component and calorific value data to the intelligent analysis and early warning platform's database at a sampling cycle of 5 minutes, providing a real-time data source for calculating the calorific value compensation coefficient. The electric flow regulating valve is controlled to gradually open in 5% increments within a 2-minute adjustment cycle to compensate for calorific value losses caused by component phase changes. During the physical adjustment cycle of the electric flow regulating valve executing the opening increase command, a sudden step change in flow occurs in a local area of ​​the pipeline network. This results in a numerical imbalance caused by the hydrodynamic time difference between the accumulated gas volume at the area's input and the node's output. The intelligent analysis and early warning platform invokes the alarm management program, and based on the gas quality change timestamp attached to the received batch of gas flow data, it pauses the triggering of abnormal transmission alarms for that area, suspends the pipeline leakage judgment logic mechanism under normal conditions, and sets the pause duration to 1.5 times the characteristic fluid propagation time of that pipeline area. The characteristic fluid propagation time of the pipeline area is defined as the time quotient obtained by dividing the total physical length of the main pipeline in the target pipeline area by the average real-time fluid velocity of the main pipeline under the current operating conditions. This time represents the basic time required for fluid to be transported from the inlet to the outlet of the target area. After the pause duration ends, if the actual relative transmission difference rate of the area falls back to within the theoretical maximum allowable synthetic error limit for three consecutive calculation cycles, the normal leakage judgment logic mechanism is restored to avoid false alarms caused by data delays under pipeline feedforward regulation conditions.

[0045] In this embodiment, the remote communication module continuously uploads gas flow data to the intelligent analysis and early warning platform according to the system clock cycle. The intelligent analysis and early warning platform receives gas flow data from the total input node and each distributed output node within the region, and performs deviation calculation for the system's cumulative flow parameter. The intelligent analysis and early warning platform uses a numerical integration program to calculate the total gas input volume and the cumulative gas volume of each output node within a preset time window. The preset time window uses a sliding time window with a step size of 1 hour and a total window span of 24 hours as the calculation benchmark to generate the comparison parameter for regional balance monitoring: the actual relative transmission difference rate of the region. This deviation calculation process executes the following mathematical model:

[0046] In the formula, Defined as the actual relative transport deficit rate of the region; Defined as the total gas volume input in the region within a preset time window, this parameter is calculated by integrating the data reporting records of gas meters at the main pipeline nodes in the region. Defined as the first The cumulative gas volume of each output node within the corresponding time window is calculated by integrating the data records synchronously uploaded by the gas flow metering terminals at each distribution node. Defined as the total number of physical output nodes within the region, this value is obtained based on the fixed node parameters in the pipeline space topology database.

[0047] In this invention, the underlying microprocessor of the intelligent analysis and early warning platform performs parallel statistical synthesis calculations on the measurement deviations of instruments at pipeline nodes. The intelligent analysis and early warning platform extracts the inherent accuracy parameters of the flow meters at each node within the pipeline network from the database, performs mathematical square root synthesis, and dynamically calculates the theoretical maximum permissible synthesis error limit related to the current actual flow conditions of the pipeline network. The calculation model for the theoretical maximum permissible synthesis error limit is shown in the following formula:

[0048] In the formula, Defined as the theoretical maximum permissible synthesis error limit; Defined as the inherent accuracy parameter of the area input main pipe flow meter. Defined as the first The inherent accuracy parameters of each output node flow meter are obtained by entering the system database based on the maximum permissible error limit specified in the relevant flow meter's factory actual flow calibration and verification certificate. The component weighting factor represents the proportion of the mathematical impact of changes in flow at a single node on the overall regional pipeline material balance.

[0049] The intelligent analysis and early warning platform's internal logic judgment program reads the calculated actual relative transmission rate of the region and the theoretical maximum permissible synthetic error limit, and performs a logical threshold comparison operation. When the intelligent analysis and early warning platform determines that the actual relative transmission rate of the region is greater than the theoretical maximum permissible synthetic error limit, and this out-of-tolerance state is maintained continuously for 3 data update cycles in the preset anti-jitter judgment logic, the system determines that the current pipeline flow loss exceeds the nominal error boundary of the hardware instrument. The intelligent analysis and early warning platform then generates a corresponding adaptive boundary reconstruction instruction, and on this basis, synchronously retrieves the variance of the underlying acoustic characteristic parameters of each output node in the region over the past 24 hours, locks the node with the largest variance drift as the suspected source of measurement distortion, and then sends the collaborative control instruction to the remote communication module at the suspected regional node through the wide area network data communication link.

[0050] The logic control unit inside the gas flow metering terminal parses the received adaptive boundary reconstruction command, responds to the internal state machine triggering mechanism, and executes hardware control actions. The logic control unit outputs a closing drive level to the motor drive mechanism of the first independent shut-off valve through the internal data bus, controlling the independent shut-off valve of the branch where the first diameter ultrasonic flow meter is located to close; the logic control unit simultaneously outputs a conducting drive level to the motor drive mechanism of the second independent shut-off valve, controlling the independent shut-off valve of the branch where the second diameter ultrasonic flow meter is located to open.

[0051] The pipe diameter of the first-diameter ultrasonic flow meter is larger than that of the second-diameter ultrasonic flow meter. After the aforementioned valve linkage control is executed, the fluid channels inside the multi-range collaborative metering module undergo physical reconstruction, and all the fluid flows into the secondary measurement branch. The multi-range collaborative metering module then enters a working state where the second-diameter ultrasonic flow meter alone performs gas flow data acquisition, utilizing the high responsiveness of the second-diameter ultrasonic flow meter for low-velocity flow field regions to capture parameters.

[0052] The multi-range collaborative metering module continuously collects gas flow data under this single branch conduction state and uploads data packets and records them via the remote communication module. The intelligent analysis and early warning platform extracts the data sources collected within this working time window and re-executes the regional balance calculation task for this pipeline area. After completing this round of regional balance calculation, the intelligent analysis and early warning platform, after extracting the data collected from the secondary branch, synchronously retrieves the inherent accuracy parameters of the second-diameter ultrasonic flow meter calibrated at the factory from the database, and applies them to the formula for calculating the synthetic error limit. or Replace the parameters with the inherent accuracy parameters of the second-diameter ultrasonic flow meter, re-execute the root sum-square (RSS) synthesis calculation, and generate the updated theoretical maximum permissible synthesis error limit for the secondary route under the current operating state. If the recalculated regional actual relative transport rate falls back to within the updated theoretical maximum permissible synthesis error limit for the secondary route, it proves that the original out-of-tolerance data belongs to the measurement distortion of the main measurement branch at low flow rates, and the state assessment is valid.

[0053] The system then generates and sends a status recovery command to the remote communication module. The logic control unit parses the status recovery command, outputs a reverse switching drive level, controls the independent shut-off valve of the branch where the second diameter ultrasonic flow meter is located to close, and controls the independent shut-off valve of the branch where the first diameter ultrasonic flow meter is located to open. After completing the adaptive diagnosis, the intelligent analysis and early warning platform sends a recovery command, which restores the multi-range collaborative metering module to the initial branch conduction state before receiving the adaptive boundary reconstruction command. That is, it restores to the default single-path conduction working mode where the first independent shut-off valve of the main measurement branch is open and the second independent shut-off valve of the auxiliary measurement branch is closed, thereby forming a closed loop of system scheduling operation.

[0054] In this invention, an intelligent analysis and early warning platform is equipped with a pipeline anomaly diagnosis algorithm. The platform executes this algorithm in real time, determining if the pipeline sub-segment where the gas flow metering terminal is located meets preset anomaly conditions. These conditions are: the variance of the instantaneous flow data reported by any gas flow metering terminal within the sub-segment fluctuates more than twice the historical steady-state variance mean of that node within three consecutive minutes; or the instantaneous difference between the inflow and outflow at the two ends of the sub-segment instantaneously exceeds 5% of the rated flow. When either condition is met, the system initiates an active perturbation detection process. For the abnormal pipeline sub-segment, the platform generates a digital characteristic control signal based on the pipeline's hydrodynamic characteristics. This digital characteristic control signal is a square wave pulse drive signal with a fixed frequency between 0.5Hz and 2Hz, a duty cycle of 50%, and a duration of 10 seconds, corresponding to a perturbation amplitude of ±2% for the valve opening. The platform then injects this characteristic control signal into the electric flow regulating valve upstream of the sub-segment via an industrial control network.

[0055] The servo drive mechanism inside the electric flow regulating valve receives the characteristic control signal and drives the valve core to perform reciprocating throttling regulation actions according to the signal command. The physical throttling action of the electric flow regulating valve disturbs the steady-state gas flow field in the pipeline network, thereby exciting a broadband aerodynamic noise wave that propagates downstream. This broadband aerodynamic noise wave, as an acoustic perturbation signal, propagates downstream in the pipeline network as the algebraic sum of the gas medium sound velocity and the fluid linear velocity. At the synchronization time node of the injected characteristic control signal, the intelligent analysis and early warning platform forces the intelligent analysis and early warning platform system clock to achieve microsecond-level synchronization with the local clock of each gas flow metering terminal by sending a time-aligned broadcast packet based on PTP (Precise Time Protocol, IEEE 1588 standard) and combining the underlying hardware timestamp marking technology. Subsequently, a high-frequency sampling command corresponding to the active perturbation detection task is generated and sent to each gas flow metering terminal distributed in the pipeline sub-segment.

[0056] In this embodiment, the remote communication module within the gas flow metering terminal receives a high-frequency sampling command, triggering a hardware interrupt to wake up the logic control unit. The logic control unit reads the control word from the high-frequency sampling command and then writes a frequency modification command to the clock configuration register of the multi-range collaborative metering module, forcibly adjusting the sampling frequency of the internal analog-to-digital converter from the first sampling frequency to the second sampling frequency. The hardware conditions for the system to maintain the second sampling frequency must satisfy the following perturbation waveform capture rule:

[0057] In the formula, Defined as the second sampling frequency set by the logic control unit; Defined as the highest effective frequency component contained in the transient flow micro-perturbation wave sequence excited upstream of the pipeline, this parameter is pre-calculated based on the slope of the characteristic control signal injected into the electric flow regulating valve by the intelligent analysis and early warning platform. By adjusting the sampling frequency, the multi-range collaborative metering module has sufficient time-domain resolution to completely preserve the time-varying characteristics of the acoustic signal.

[0058] During the period when transient flow perturbation waves are excited and propagated within the pipeline network, the logic control unit maintains the multi-range collaborative metering module to continuously collect data at the second sampling frequency. The logic control unit internally activates a perturbation time window countdown mechanism. When the preset 30-second maximum perturbation observation time window is reached, or when the digital signal processing chip successfully extracts the waveform attenuation amplitude of the effective reflected wave and completes data packetization, the preset condition for the digital signal processing chip to determine that the effective reflected wave has been extracted is: the signal amplitude obtained by performing envelope detection operation in real time exceeds the preset reflection wave determination threshold. The preset reflection wave determination threshold is set to 3 times the extracted basic ambient sound pressure level parameter (i.e., the root mean square value of the background noise). After the determination condition is met, the logic control unit automatically writes a reset instruction to the clock configuration register, forcibly reducing the sampling frequency of the analog-to-digital converter from the second sampling frequency back to the low-power first sampling frequency, thereby forming a closed-loop exit of the high-frequency sampling state. The high-frequency detection signal here is specifically an AC voltage signal sequence converted from the energy leakage component of the broadband acoustic pressure fluctuation of the fluid inside the pipe within the resonant frequency band of the transducer (100kHz to 1MHz), acquired by the ultrasonic transducer receiver. This is an electrical signal generated by broadband high-frequency noise modulated by a low-frequency throttling action (0.5Hz to 2Hz) coupled to the piezoelectric ceramic of the ultrasonic transducer. The digital signal processing chip of the multi-range collaborative metering module performs envelope detection on the acquired high-frequency detection signal in real time, monitors the signal energy step point, and extracts the timestamp of the modulated low-frequency acoustic perturbation wavefront arriving on the absolute time axis of the multi-range collaborative metering module. The multi-range collaborative metering module synchronously executes a waveform amplitude extremum extraction algorithm to calculate the waveform attenuation amplitude of the corresponding received waveform. The above waveform attenuation amplitude calculation model follows the mathematical formula:

[0059] In the formula, Defined as the attenuation amplitude of the extracted waveform; Defined as the instantaneous acoustic piezoelectric signal sequence within the time window of the transient current micro-perturbation wave corresponding to the acquired high-frequency detection signal; Defined as the baseline environmental sound pressure level parameter of the pipeline sub-segment under steady-state flow field conditions before the injection of perturbation signals, this parameter is obtained by extracting the envelope peak value of the pipeline's background environmental noise electrical signal within 5 seconds before the terminal receives the high-frequency sampling command. This allows the formula to be uniformly defined as the absolute difference between the peak value of the perturbation signal and the peak value of the background noise, used to rigorously characterize the net peak amplitude of the effective perturbation signal exceeding the background, thus eliminating the interference of background noise on the extraction of perturbation amplitude. The multi-range collaborative metering module completes the hardware-level extraction of the above characteristic parameters and generates a data packet with a standard structure.

[0060] The logic control unit reads data from the internal buffer of the multi-range collaborative metering module and pushes it to the remote communication module via the internal data bus. The remote communication module combines the extracted timestamp, waveform attenuation amplitude, and the completely recorded perturbation waveform sequence into a single packet and uploads it synchronously to the remote intelligent analysis and early warning platform.

[0061] In this embodiment, the intelligent analysis and early warning platform receives the perturbation waveform sequence, timestamp, waveform attenuation amplitude, and pipeline medium sound velocity uploaded by the remote communication module. The intelligent analysis and early warning platform then calls the location calculation program in its internal storage unit to initiate the anomaly source location calculation task. The platform reads the control command issuance records from the database and extracts the time-axis waveform data sequence corresponding to the injected characteristic control signals.

[0062] The central processing unit of the intelligent analysis and early warning platform performs cross-correlation function calculations on the injected characteristic control signal and the received perturbation waveform sequence. The cross-correlation function calculation model is expanded according to the following mathematical equation:

[0063] In the formula, Defined as the cross-correlation function value at the corresponding time offset; Defined as the time offset of the independent variable; Defined as the integration time window length, this parameter is set according to the waveform truncation frame length in the system communication protocol; Defined as a time-domain function of the characteristic control signal injected into the intelligent analysis and early warning platform; Defined as the time-domain function of the perturbation waveform sequence received and uploaded by the gas flow metering terminal. The intelligent analysis and early warning platform executes an extreme value search algorithm to traverse the time offsets to find the peak point of the cross-correlation function. The time offset corresponding to the peak point is extracted as the time delay of the reflected wave. This reflected wave is formed when the transient flow perturbation wave propagating downstream encounters an acoustic impedance change interface caused by an anomaly source in the pipeline (such as a pipe wall rupture or leak point or a liquid accumulation blockage section), resulting in physical reflection and reverse propagation to the metering terminal. The system calculates the difference between the timestamp of the received direct wave of the perturbation and the timestamp of the received reflected wave through the cross-correlation algorithm, which is taken as the effective time delay and marked as [missing information]. .

[0064] The intelligent analysis and early warning platform reads the sound velocity of the pipeline medium and calculates the basic distance based on the time delay of the reflected wave and the sound velocity of the pipeline medium. In this scenario, the electric flow regulating valve is located upstream, and the gas flow metering terminal is located upstream of the anomaly source. The transient flow perturbation wave is generated by the regulating valve, flows downstream through the metering terminal (generating a direct wave timestamp), continues downstream to the anomaly source where it is reflected, and the reflected wave flows backward through the metering terminal again. Therefore, this time difference... This represents the reflected wave traveling twice the round trip distance from the terminal to the anomaly source and back to the terminal. Therefore, the basic distance calculation model executes the following mathematical equation, introducing... A coefficient is used to calculate the one-way distance:

[0065] In the formula, Defined as basic distance; Defined as the velocity of sound in the pipeline medium measured and uploaded by the gas flow metering terminal in the aforementioned workflow; Defined as the time delay of the reflected wave extracted from the cross-correlation calculation. The base distance reflects the length of the lossless wave propagation path under ideal fluid conditions in the pipeline network.

[0066] The intelligent analysis and early warning platform invokes a nonlinear correction algorithm module to correct the base distance using waveform attenuation amplitude and a preset fluid dissipation nonlinear compensation factor, thus calculating the spatial physical pipe length of the pipeline anomaly source. Because micro-perturbations exhibit energy dissipation along the pipeline path during long-distance propagation, and the wave velocity attenuation due to pipe wall friction is nonlinearly positively correlated with propagation distance, relying solely on time calculations will result in an underestimated distance due to wavefront distortion. Therefore, positive compensation based on the waveform attenuation degree is necessary. The spatial physical pipe long-distance compensation correction model uses the following mathematical expression:

[0067] In the formula, Defined as the spatial physical pipe length distance of the final calculated pipeline anomaly source; Defined as the logarithmic attenuation of transient wave propagation, its calculation formula is: ,in The attenuation amplitude of the terminal's measured waveform, as calculated above; The initial injection equivalent amplitude of the electric flow control valve under the current perturbation opening is calculated and issued in advance by the intelligent analysis and early warning platform based on the sound pressure-voltage mapping coefficient and perturbation opening of the control valve as specified by the factory. Defined as a system-preset reference attenuation decibel reference value, used to normalize the actual attenuation of micro-perturbation waves, the reference attenuation decibel reference value is preset to 60dB; Defined as a preset fluid dissipation nonlinear compensation factor, this factor is generated through regression analysis fitting based on the energy attenuation characteristic curves of pipe sections of the same material measured in a pipeline network actual flow test field. The specific test conditions involve injecting standard micro-perturbation waves under a pipeline network static pressure of 0.1 MPa to 0.4 MPa, and applying an exponential decay model. The measured amplitude was fitted using least squares regression (where...) For the distance of transmission Amplitude at decay point For the initial injection amplitude, (For sound wave attenuation coefficient), extract the attenuation coefficient. As this factor (i.e. However, considering dimensional consistency, a standard reference distance is introduced into the revised formula. (Constant, take 1 meter) Convert the exponential decay coefficient into a dimensionless corrected weighting factor. (Right now The value ranges from 0.01 to 0.05 and is persistently stored in the constant database of the intelligent analysis and early warning platform. After obtaining the corrected spatial physical pipe length, the intelligent analysis and early warning platform calls the spatial topology database of the GIS geographic information system that is connected to the system. Taking the absolute latitude and longitude of the gas flow metering terminal through which the perturbation probe wave flows as the starting coordinates in three-dimensional space, it performs surface path integration offset addressing according to the calculated spatial physical pipe length along the pre-imported pipeline topology and vector physical path (including bend and elevation change information), calculates the absolute geographic latitude and longitude coordinates of the corresponding endpoint, and then outputs the spatial physical pipe length of the pipeline anomaly source with coordinate labels, ending the entire anomaly source location calculation process and generating an anomaly location report data table.

[0068] In this embodiment, the logic control unit inside the gas flow metering terminal is constructed using a microcontroller integrated chip. The microcontroller integrated chip includes a central processing unit (CPU), read-only memory (ROM), random access memory (RAM), and various digital interface peripherals. The data bus of the microcontroller integrated chip is connected to the registers of the multi-range collaborative metering module, performing read operations on flow rate and underlying acoustic characteristic data. The control pins of the microcontroller integrated chip are connected to the motor drive circuits of the first and second independent shut-off valves, executing the output of switching control commands. The microcontroller integrated chip inside the logic control unit also utilizes a digital signal processor (DSP) or a field-programmable gate array (FPGA) for equivalent circuit-level chip replacement to achieve the same hardware control logic.

[0069] In this invention, the intelligent analysis and early warning platform is built using a server computing cluster and non-volatile storage media. The non-volatile storage media contains embedded computer program instructions including gas mass change feedforward control, adaptive boundary reconstruction, and anomaly source localization calculation. The central processing unit within the server computing cluster reads the computer program instructions from the non-volatile storage media and performs numerical calculations and communication scheduling operations according to the processes described in the aforementioned embodiments. The intelligent analysis and early warning platform utilizes a multi-threaded concurrency mechanism to process the data streams uploaded from various distributed nodes in real time, outputting diagnostic results and collaborative control instructions.

[0070] To maintain the timing consistency of the system under high-frequency sampling conditions during active perturbation detection, the total response time of the logic control unit for hardware interrupts and task scheduling must satisfy a specific underlying timing constraint model. This underlying timing constraint model follows the mathematical relationship:

[0071] In the formula, Defined as the total response time for the logic control unit to execute actions; Defined as hardware interrupt latency, this parameter is obtained by consulting the chip hardware datasheet based on the system clock cycle and instruction pipeline architecture of the microcontroller chip. Defined as the execution time of the interrupt service routine that reads data from the terminal's internal communication buffer; Defined as the time overhead of task scheduling and instruction parsing in the internal operating system of the logic control unit; Defined as the second sampling frequency switched after the multi-range collaborative metering module receives the high-frequency sampling command. The logic control unit satisfies the above timing constraint model boundary, eliminating communication congestion and data frame loss during the high-frequency detection signal acquisition process.

Claims

1. A gas flow metering terminal based on remote communication, characterized in that, include: A multi-range collaborative metering module includes a first-diameter ultrasonic flow meter and a second-diameter ultrasonic flow meter connected in parallel, and independent shut-off valves respectively installed on the corresponding pipeline branches of the first-diameter ultrasonic flow meter and the second-diameter ultrasonic flow meter; the multi-range collaborative metering module is used to collect gas flow data and pipeline medium sound velocity at a first sampling frequency, and extract the underlying acoustic characteristic parameters of the first-diameter ultrasonic flow meter and the second-diameter ultrasonic flow meter, the underlying acoustic characteristic parameters including ultrasonic signal gain and signal-to-noise ratio; The remote communication module is connected to the multi-range collaborative metering module and is used to send the gas flow data, the pipeline medium sound velocity and the underlying acoustic characteristic parameters to the intelligent analysis and early warning platform, and to receive the collaborative control commands issued by the intelligent analysis and early warning platform. The logic control unit is connected to the independent shut-off valve of the remote communication module and the multi-range collaborative metering module, respectively. It is used to control the opening and closing of the independent shut-off valve according to the collaborative control command to realize branch switching. When receiving the corresponding command, it adjusts the sampling frequency of the multi-range collaborative metering module from the first sampling frequency to a second sampling frequency greater than the first sampling frequency, so as to perform collaborative metering operation when the electric flow regulating valve upstream of the pipeline performs gas quality change feedforward control and active micro-disturbance detection.

2. The gas flow metering terminal based on remote communication according to claim 1, characterized in that, The multi-range collaborative metering module is configured to maintain continuous acquisition of the gas flow data during the gas quality change feedforward control. The gas mass change feedforward control is triggered by the intelligent analysis and early warning platform when it determines that the signal-to-noise ratio is lower than a preset reference signal-to-noise ratio threshold and the ultrasonic signal gain is higher than a preset reference gain alarm threshold.

3. The gas flow metering terminal based on remote communication according to claim 2, characterized in that, The gas flow data uploaded by the remote communication module during the gas quality change feedforward control is configured to allow the intelligent analysis and early warning platform to suspend triggering of abnormal transmission alarms for the region during the adjustment cycle of issuing an opening increase command to the electric flow regulating valve.

4. The gas flow metering terminal based on remote communication according to claim 1, characterized in that, The collaborative control instructions include adaptive boundary reconstruction instructions; the adaptive boundary reconstruction instructions are generated by the intelligent analysis and early warning platform when the actual relative transmission rate of the judgment area is greater than the theoretical maximum permissible synthetic error limit, wherein the theoretical maximum permissible synthetic error limit is a synthetic limit value dynamically calculated based on the inherent accuracy parameters of the flow meters at each node in the pipeline network.

5. The gas flow metering terminal based on remote communication according to claim 4, characterized in that, The gas flow data uploaded by the remote communication module is configured to be used by the intelligent analysis and early warning platform to perform deviation calculations involving the total gas input volume of the region and the cumulative gas volume of each output node, so as to generate the actual relative transmission difference rate of the region for comparison.

6. The gas flow metering terminal based on remote communication according to claim 4, characterized in that, The logic control unit is configured to perform the following actions in response to the adaptive boundary reconstruction instruction: The independent shut-off valve of the branch where the first diameter ultrasonic flow meter is located is closed, and the independent shut-off valve of the branch where the second diameter ultrasonic flow meter is located is opened. Since the pipe diameter of the first-diameter ultrasonic flow meter is larger than that of the second-diameter ultrasonic flow meter, the multi-range collaborative metering module is in a state where the second-diameter ultrasonic flow meter alone performs gas flow data acquisition, so that the intelligent analysis and early warning platform can re-execute the regional balance calculation, and after the calculation cycle ends, it will return to the branch conduction state before receiving the adaptive boundary reconstruction command.

7. The gas flow metering terminal based on remote communication according to claim 1, characterized in that, The coordinated control command includes a high-frequency sampling command, which corresponds to the active micro-perturbation detection. The high-frequency sampling command is generated by the intelligent analysis and early warning platform when it determines that the pipeline sub-network segment where the gas flow metering terminal is located meets the abnormal preset conditions, and injects a characteristic control signal into the electric flow regulating valve upstream of the pipeline sub-network segment to excite transient flow micro-perturbation waves.

8. The gas flow metering terminal based on remote communication according to claim 7, characterized in that, The logic control unit is configured to perform the following actions in response to the high-frequency sampling command: During the period when the transient flow micro-perturbation wave is excited in the pipeline network, the multi-range collaborative metering module is controlled to collect data at the second sampling frequency; The multi-range collaborative metering module collects high-frequency detection signals containing perturbation waveform sequences, extracts the timestamp of the transient flow perturbation wave arriving at the multi-range collaborative metering module and the waveform attenuation amplitude, and synchronously uploads the perturbation waveform sequence, the timestamp and the waveform attenuation amplitude to the intelligent analysis and early warning platform through the remote communication module.

9. The gas flow metering terminal based on remote communication according to claim 8, characterized in that, The perturbation waveform sequence, the timestamp, the waveform attenuation amplitude, and the sound velocity of the pipeline medium uploaded by the remote communication module are configured for the intelligent analysis and early warning platform to perform location calculation, which includes: The time delay of the reflected wave is extracted by performing a cross-correlation function calculation on the injected characteristic control signal and the received perturbation waveform sequence. The basic distance is calculated based on the time delay of the reflected wave and the sound velocity of the pipeline medium. The basic distance is then corrected using the waveform attenuation amplitude and a preset fluid dissipation nonlinear compensation factor to solve for the spatial physical pipe length of the pipeline anomaly source.

10. The gas flow metering terminal based on remote communication according to claim 1, characterized in that, The remote communication module includes a built-in battery power supply circuit and a wireless data transmission circuit; the multi-range collaborative metering module is connected in parallel to the first diameter ultrasonic flow meter and the second diameter ultrasonic flow meter through a manifold, and the upper limit of the measurement range of the first diameter ultrasonic flow meter is greater than the upper limit of the measurement range of the second diameter ultrasonic flow meter.

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