A device, method, apparatus, and medium for monitoring liquid droplet content in a gas pipeline

Abstract

The application discloses a kind of gas pipeline liquid drop content monitoring device, method, equipment and medium, and the technical field belongs to gas transportation technology.Gas pipeline liquid drop content monitoring device includes control unit, signal management unit, detection pipeline and signal transceiver component;Signal transceiver component includes N signal input probe, signal receiving probe, signal input channel and signal output channel, signal input probe and signal receiving probe are set in detection pipeline, and the first end of signal input channel and signal output channel is connected with signal management unit;Signal management unit is used to feed into N radio frequency input signals to detection pipeline by signal input probe, and also be used to receive N radio frequency acquisition signals by signal receiving probe;Control unit is used to calculate the liquid drop content in detection pipeline according to N radio frequency acquisition signals.The application can realize non-intrusive liquid drop content online detection, reduce the influence on pipeline gas flow.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas transportation, in particular to a device and method for monitoring liquid droplet content in a gas pipeline, an electronic device and a storage medium. BACKGROUND

[0002] In the process of gas transportation, in order to detect the content and concentration of liquid impurities, it is necessary to detect and analyze the gas-liquid two-phase flow in the pipeline, so as to obtain the physical property parameters of the contained impurities.

[0003] In the related art, a liquid detection device is usually used to detect the liquid droplet content in the gas pipeline. The device adopts a separate detection method to separate the liquid from the gas, and then detects the quality of the liquid. However, the above-mentioned scheme uses a blocking detection structure to detect the liquid droplet content, which affects the flow system in the pipeline and cannot realize online non-intrusive real-time detection.

[0004] Therefore, how to realize non-intrusive online detection of liquid droplet content and reduce the impact on the gas flow in the pipeline is a technical problem to be solved by those skilled in the art at present. SUMMARY

[0005] The purpose of the present application is to provide a device and method for monitoring liquid droplet content in a gas pipeline, an electronic device and a storage medium, which can realize non-intrusive online detection of liquid droplet content and reduce the impact on the gas flow in the pipeline.

[0006] To solve the above technical problems, the present application provides a device for monitoring liquid droplet content in a gas pipeline, comprising: a control unit, a signal management unit, a detection pipeline and a signal transceiving assembly;

[0007] The signal transceiving assembly comprises N signal input probes, N signal receiving probes, N signal input channels and N signal output channels. The signal input probes and the signal receiving probes are arranged in the detection pipeline. The first ends of the signal input channels and the signal output channels are connected to the signal management unit. The second end of the ith signal input channel is connected to the ith signal input probe. The second end of the ith signal output channel is connected to the ith signal receiving probe. Wherein, N≥2, 1≤i≤N.

[0008] The signal management unit is configured to feed N radio frequency input signals to the detection pipeline through the signal input channels and the signal input probes, and to receive N radio frequency collection signals through the signal receiving probes and the signal output channels. The signal management unit is further configured to transmit the N radio frequency collection signals to the control unit. The signal frequency range of the radio frequency input signal fed by the ith signal input probe is the same as the signal frequency range of the radio frequency collection signal received by the ith signal receiving probe.

[0009] The control unit is configured to calculate the liquid droplet content in the detection pipeline according to the N pieces of radio frequency acquisition signals.

[0010] Optionally, the signal input probe and the signal receiving probe are probes with preset end faces; the preset end faces are H-shaped end faces, M-shaped end faces or U-shaped end faces.

[0011] Optionally, an angle between the signal input probe and a first axis is 45°, and an angle between the signal receiving probe and a second axis is 45°; a distance between any point on the first axis and all the signal input probes is the same, and a distance between any point on the second axis and all the signal receiving probes is the same.

[0012] Optionally, the control unit is provided with a convolutional neural network model.

[0013] Correspondingly, the control unit comprises:

[0014] a signal screening subunit configured to select one piece of radio frequency acquisition signal meeting a preset constraint condition from the N pieces of radio frequency acquisition signals as a preferred signal by using the convolutional neural network model;

[0015] a data calculation subunit configured to calculate the liquid droplet content in the detection pipeline according to the preferred signal.

[0016] Optionally, the data calculation subunit is configured to calculate the liquid droplet content in the detection pipeline according to amplitude variation information and phase variation information of the preferred signal.

[0017] Optionally, a signal frequency range of the first signal input channel and the first signal output channel is 0-3 GHz, a signal frequency range of the second signal input channel and the second signal output channel is 8 GHz-15 GHz, and a signal frequency range of the third signal input channel and the third signal output channel is 18 GHz-25 GHz.

[0018] Optionally, the detection pipeline is provided with connecting flanges at two ends, which are configured to connect the detection pipeline and a gas pipeline.

[0019] The application further provides a liquid droplet content monitoring method in a gas pipeline, which is applied to a control unit of the above-mentioned liquid droplet content monitoring device in a gas pipeline and comprises the following steps.

[0020] receiving N pieces of radio frequency acquisition signals transmitted by the signal receiving management unit;

[0021] calculating the liquid droplet content in the detection pipeline according to the N pieces of radio frequency acquisition signals.

[0022] The application further provides a storage medium, which stores a computer program, and the computer program realizes the steps of the gas pipeline liquid droplet content monitoring method when executed.

[0023] The application further provides an electronic device, which comprises a memory and a processor, the memory stores a computer program, and the processor realizes the steps of the gas pipeline liquid droplet content monitoring method when calling the computer program in the memory.

[0024] The gas pipeline liquid droplet content monitoring device provided by the application comprises a control unit, a signal management unit, a detection pipeline and a signal transceiving assembly. A plurality of signal input probes and signal receiving probes in the signal transceiving assembly are arranged inside the detection pipeline. The signal management unit feeds a radio frequency input signal to the detection pipeline and receives a radio frequency collection signal from the signal receiving probes, so as to calculate the liquid droplet content in the detection pipeline based on the radio frequency collection signal. In the application, the arrangement of the signal input probes and the signal receiving probes does not interfere with the gas flow in the pipeline, and the transmission of the radio frequency signal also does not change the flow path or speed of the gas, thereby ensuring the normal operation of the pipeline system and the stability of the gas flow. In the above scheme, the liquid droplet content is determined based on the signal received by the signal receiving probes, which can determine the current liquid droplet content in the pipeline in an online detection manner. Therefore, the application can realize non-intrusive online detection of the liquid droplet content and reduce the influence on the gas flow in the pipeline. The application further provides a gas pipeline liquid droplet content monitoring method, a storage medium and an electronic device, which have the above beneficial effects, and details are not described herein. BRIEF DESCRIPTION OF DRAWINGS

[0025] In order to more clearly illustrate the embodiments of the application, the drawings required in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0026] Figure 1 A structural schematic diagram of a gas pipeline liquid droplet content monitoring device provided by an embodiment of the application;

[0027] Figure 2 A structural schematic diagram of a signal transceiving assembly provided by an embodiment of the application;

[0028] Figure 3 A first direction appearance schematic diagram of a natural gas pipeline liquid droplet content monitoring device provided by an embodiment of the application;

[0029] Figure 4A second direction appearance schematic view of a natural gas pipeline liquid drop content monitoring device provided by the embodiment of the application;

[0030] Figure 5 An H-shaped end surface appearance schematic view provided by the embodiment of the application;

[0031] Figure 6 A signal local oscillator and data processing unit structure schematic view provided by the embodiment of the application;

[0032] Figure 7 A convolutional neural network model data processing flowchart provided by the embodiment of the application;

[0033] Figure 8 A natural gas pipeline internal liquid drop content microwave detection system working flowchart provided by the embodiment of the application;

[0034] Figure 9 A natural gas pipeline internal liquid drop content microwave detection system working flowchart provided by the embodiment of the application. DETAILED DESCRIPTION

[0035] To make the purpose, technical solutions and advantages of the embodiments of the application clearer, the technical solutions in the embodiments of the application will be described clearly and completely below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are some embodiments of the application, rather than all the embodiments of the application. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative work fall within the protection scope of the application.

[0036] Please see the following Figure 1 , Figure 1 A gas pipeline internal liquid drop content monitoring device structure schematic view provided by the embodiment of the application.

[0037] The gas pipeline internal liquid drop content monitoring device comprises a control unit 101, a signal management unit 102, a detection pipeline 103 and a signal transceiver assembly 104. The signal management unit 102 is connected with the signal transceiver assembly 104, and the signal management unit 102 is connected with the control unit 101. The signal transceiver assembly 104 is used for transmitting a radio frequency signal to the detection pipeline 103 and receiving a returned signal. The detection pipeline is provided with a connecting flange at both ends, which is used for connecting the detection pipeline and a gas pipeline.

[0038] Specifically, the signal transceiving assembly comprises N signal input probes, N signal receiving probes, N signal input channels and N signal output channels, the signal input probes and the signal receiving probes are arranged in the detection pipeline, and N≥2. The number of the signal input probes and the signal receiving probes can be set according to actual conditions (for example, 2, 3 or 4), and the corresponding frequency range of the probes can also be selected considering economy and actual conditions. The signal input probes and the signal receiving probes can be high-voltage probes, which are a kind of detection and measurement devices used in high-voltage environments, one end of which is welded to the detection pipeline, and the other end is connected with the signal channel.

[0039] The signal input probes correspond to the signal input channels one by one, and the signal receiving probes correspond to the signal output channels one by one. Each signal input channel and each signal output channel comprises a first end and a second end. Please refer to Figure 2 , Figure 2 A structure diagram of a signal transceiving assembly provided by the embodiment of the application is shown in the figure, A represents a signal input probe, and B represents a signal receiving probe. The first end of the signal input channel and the first end of the signal output channel are connected with the signal management unit, the second end of each signal input channel is connected with the corresponding signal input probe, and the second end of each signal output channel is connected with the corresponding signal receiving probe. Specifically, the second end of the ith signal input channel is connected with the ith signal input probe, and the second end of the ith signal output channel is connected with the ith signal receiving probe; 1≤i≤N.

[0040] The signal management unit, also known as a signal local oscillator and processing unit, is used for feeding N radio frequency input signals to the detection pipeline through the signal input channel and the signal input probe, receiving N radio frequency collection signals through the signal receiving probe and the signal output channel, and transmitting the N radio frequency collection signals to the control unit; wherein the signal frequency range of the radio frequency input signal fed by the ith signal input probe is the same as the signal frequency range of the radio frequency collection signal received by the ith signal receiving probe.

[0041] In the embodiment, the signal management unit can transmit a radio frequency input signal to the corresponding signal input probe through each signal input channel, so that the signal input probe feeds the radio frequency input signal into the detection pipeline; the transmission path of the radio frequency input signal is the first end of the signal input channel, the second end of the signal input channel, the signal input probe and the detection pipeline in sequence.

[0042] In the embodiment, the signal management unit can also receive a radio frequency collection signal received by the corresponding signal receiving probe through each signal output channel, so as to receive the reflection result of the radio frequency input signal. The transmission path of the radio frequency collection signal is the detection pipeline, the signal receiving probe, the second end of the signal output channel, the first end of the signal output channel in sequence.

[0043] The control unit is configured to calculate the liquid droplet content in the detection pipeline based on the N-channel radio frequency collection signals. After receiving the N-channel radio frequency collection signals transmitted by the signal management unit, the control unit can calculate the liquid droplet content in the detection pipeline using part of the radio frequency collection signals or all of the radio frequency collection signals.

[0044] Specifically, the embodiment can perform necessary processing on the collected radio frequency signals, such as filtering, amplification, and the like. The features related to the liquid droplet content can be extracted from the processed radio frequency signals. These features can include amplitude variation, phase variation, frequency offset, and the like. The embodiment can use experimental data or theoretical models to establish a mapping relationship between the liquid droplet content and the radio frequency signal features. Based on the mapping relationship, the liquid droplet content corresponding to the actually collected radio frequency collection signals can be calculated.

[0045] The monitoring device for the liquid droplet content in the gas pipeline provided by the embodiment includes a control unit, a signal management unit, a detection pipeline, and a signal transceiver assembly. The plurality of signal input probes and signal receiving probes in the signal transceiver assembly are arranged inside the detection pipeline. The signal management unit feeds radio frequency input signals into the detection pipeline and receives radio frequency collection signals from the signal receiving probes, so as to calculate the liquid droplet content in the detection pipeline based on the radio frequency collection signals. In the embodiment, the arrangement of the signal input probes and the signal receiving probes does not interfere with the gas flow in the pipeline. The transmission of the radio frequency signals also does not change the flow path or speed of the gas, thereby ensuring the normal operation of the pipeline system and the stability of the gas flow. In the above scheme, the liquid droplet content is determined based on the signals received by the signal receiving probes, which can determine the current liquid droplet content in the pipeline in an online detection manner. Therefore, the embodiment can realize non-intrusive online detection of the liquid droplet content, and reduce the influence on the gas flow in the pipeline.

[0046] As for the Figure 1 For further introduction of the corresponding embodiment, the signal input probe and the signal receiving probe are probes with a preset end face. The preset end face is an H-shaped end face, an M-shaped end face, or a U-shaped end face, i.e., the signal input probe can be a probe with an H-shaped end face, an M-shaped end face, or a U-shaped end face, and the signal receiving probe can be a probe with an H-shaped end face, an M-shaped end face, or a U-shaped end face.

[0047] The H-shaped end face can improve the sensitivity and reduce interference. The principle is that, compared with a circular end face, the H-shaped end face probe has a smaller end area, so that the energy can be concentrated in a smaller area and the electric field strength is enhanced. In addition, due to the multiple edges and unique shape of the H-shaped signal channel, a more complete electric field structure can be formed, effectively reducing the influence of external interference signals and improving the stability and accuracy of the signals. Therefore, the microwave signal has higher sensitivity and stronger anti-interference ability. Experiments have proved that the H-shaped end face signal has higher sensitivity and stronger anti-interference ability.

[0048] As for Figure 1 For further introduction of the corresponding embodiment, the control unit is provided with a convolutional neural network model, and the control unit comprises a signal screening subunit and a data calculation subunit.

[0049] The signal screening subunit is configured to select one radio frequency acquisition signal meeting a preset constraint condition from the N radio frequency acquisition signals as a preferred signal by using the convolutional neural network model. As a feasible implementation manner, the preset constraint condition is a constraint condition related to signal sensitivity; and the convolutional neural network model can be used to detect the sensitivity of each radio frequency acquisition signal, and the radio frequency acquisition signal with the maximum sensitivity can be selected as the preferred signal.

[0050] The data calculation subunit is configured to calculate the liquid droplet content in the detection pipeline according to the preferred signal. Specifically, the data calculation subunit is configured to calculate the liquid droplet content in the detection pipeline according to the amplitude change information and the phase change information of the preferred signal. A mathematical model between the liquid droplet content and the amplitude change information and the phase change information can be established in advance in this embodiment. This mathematical model can be obtained by fitting experimental data, and reflects the influence of liquid droplets on the radio frequency signal. In this embodiment, the amplitude change information and the phase change information collected in real time can be input into the mathematical model, and the liquid droplet content can be calculated. This method combines the non-contact measurement of the radio frequency signal and the accurate calculation of the mathematical model, and realizes the online detection of the liquid droplet content in the pipeline.

[0051] In this embodiment, the amplitude and the phase are combined together, and either a simple function fitting or a complex algorithm can be used. The purpose is to improve the accuracy of measurement after combining the two parameters.

[0052] The dielectric constant of the liquid phase in the pipeline and the dielectric constant of the gas phase and the volume fraction of different components determine the dielectric constant of the mixture . Among them, the dielectric constant of the liquid phase has a huge impact Therefore, the volume fraction q of the liquid phase component is defined as the concentration data. The amplitude and the phase of the microwave sweep signal emitted by the probe change with the mixed dielectric constant of the gas-liquid two-phase flow.

[0053] ;

[0054] Among them, is the dielectric constant of the liquid phase, is the dielectric constant of the gas phase. is the mass concentration of the liquid phase, is the mass concentration of the gas phase.

[0055] ;

[0056] ;

[0057] in The component medium loss factor, For component energy storage characteristics, λ is the incident wavelength, and d is the differential symbol.

[0058] This embodiment defines the amplitude-phase joint parameters. Liquid phase concentration , where x represents the preset coefficient and f represents the relational function.

[0059] When the dielectric constants of each component in the liquid phase are known, the concentration of each component in the liquid phase can be obtained through amplitude and phase.

[0060] As for Figure 1 In a further description of the corresponding embodiment, the angle between the signal input probe and the first axis is 45°, and the angle between the signal receiving probe and the second axis is 45°; wherein, the distance from any point on the first axis to all the signal input probes is the same, and the distance from any point on the second axis to all the signal receiving probes is the same. The first axis is the relative spatial position axis of the signal receiving probes, and the second axis is the relative spatial position axis of the signal input probes.

[0061] As for Figure 1 As further described in the corresponding embodiment, the signal frequency range of the first signal input channel and the first signal output channel is [0 GHz, 3 GHz], the signal frequency range of the second signal input channel and the second signal output channel is [8 GHz, 15 GHz], and the signal frequency range of the third signal input channel and the third signal output channel is [18 GHz, 25 GHz].

[0062] The process described in the above embodiments is illustrated below through examples in practical applications.

[0063] With the acceleration of industrialization and urbanization, the uneven geographical distribution of natural gas has become increasingly prominent. To address the huge demand for natural gas, the construction and maintenance of natural gas pipelines have become paramount. Due to technological limitations, natural gas carries micron-sized droplet impurities, which pose hazards during pipeline transportation. It is necessary to monitor the content and concentration of these droplet impurities in high-pressure natural gas pipelines in real time to ensure pipeline transportation safety and assess the efficiency of filter separators. Therefore, the detection of droplet impurities within pipelines has become a crucial requirement for industrial production and safety management. Compared to traditional detection technologies, microwave technology offers advantages such as high speed, high efficiency, online non-invasive detection, and the absence of radioactivity and pollution.

[0064] Microwave technology is increasingly widely used in the detection field. In the detection of multiphase materials in a pipeline, microwave signals are transmitted through the wall of the pipeline, and the reflected signals are received by a receiver, so as to analyze the composition information of the multiphase materials in the pipeline. At present, there are many detection methods for the oil and gas industry, such as ultrasonic method, electrical resistance tomography method, electrical capacitance tomography method, computer tomography method, etc., but the effect is not ideal under the high pressure condition of the natural pipeline and the relatively poor environment on site, such as the pressure of the second West-East Gas Transmission Pipeline can reach 10 MPa, and the interference of factors such as on-site noise is large. The existing light scattering method also has its shortcomings, such as the window is easy to be contaminated, is limited by pressure bearing capacity, cannot be operated for a long period, etc., which makes it difficult to monitor the natural gas in the pipeline for a long time and automatically, in addition, the light scattering method also needs to be modified in design.

[0065] Natural gas is generally transported to the whole country through high-pressure gas transmission pipelines after being collected and processed at the wellhead. In the study of natural gas flowing through each link, in order to detect the content and concentration of liquid impurities, the gas-liquid two-phase flow flowing in the pipeline needs to be detected and analyzed to obtain the physical property parameters of the impurities contained. In the study of natural gas transportation links, a monitoring device suitable for various natural gas transportation and processing links is needed to monitor the liquid droplets and other impurities carried by natural gas in the pipeline in real time.

[0066] Through the online real-time monitoring of liquid droplet impurities contained in natural gas in the pipeline, evaluation basis can be provided for the separation efficiency of natural gas transportation, and the subsequent natural gas transportation, processing, storage and other process links can be guided, potential safety hazards such as pipeline corrosion and gas leakage can be found, and corresponding measures can be taken to avoid accidents. The automation monitoring of the pipeline transportation process is promoted, and the economy and reliability of the pipeline transportation are improved. However, the existing detection methods applied in the oil and gas industry at present are not ideal, and cannot meet the needs of efficient and accurate long-time online monitoring of high-pressure natural gas gathering and transportation pipelines.

[0067] The natural gas liquid content detection device in the related art adopts a separation type detection method, separates liquid from natural gas, and then detects the quality of the liquid, which can accurately detect the liquid, but is still a blocking type detection, affecting the flow system in the pipeline. It cannot realize online non-intrusive real-time detection. The separation type detection principle in the above related technology hinders the normal flow of natural gas in the gas pipeline, which affects the normal operation of the pipeline. The detection accuracy of the above related technology is greatly affected by the separation effect of liquid from natural gas, and the separation efficiency of the device needs to be checked frequently, which cannot realize long-term measurement; at the same time, it is affected by the temperature on site and the gas-liquid flow rate in the pipeline, resulting in a decrease in detection accuracy. The above related technology needs to go through a separation process for a period of time before detecting the quality of the liquid, so it does not have real-time performance and cannot reflect the liquid content of natural gas in the pipeline in real time.

[0068] To solve the technical problems in the above related art, the embodiment provides a gas pipeline liquid droplet content monitoring scheme based on microwave detection technology. The scheme is suitable for an online non-intrusive liquid droplet impurity content detection device with wide application scenarios and accurate detection, which can detect various liquid phase impurities such as liquid droplets or oil mist contained in high-pressure pipelines in real time.

[0069] The natural gas pipeline liquid droplet content monitoring device provided in the embodiment is suitable for detecting various liquid phase impurities in high-pressure natural gas pipelines, and can measure liquid droplets in the gas-liquid two-phase flow system in the natural gas pipeline in real time, online, multi-frequency band and high precision. The existing detection device solves the problems of contact type and separation type measurement of liquid phase impurities in the natural gas pipeline, slow measurement speed, and inability to realize long-term automatic real-time monitoring.

[0070] Please refer to Figure 3 and Figure 4 , Figure 3 Figure 1 is a first direction appearance schematic view of a natural gas pipeline liquid droplet content monitoring device provided by the embodiment of the present application, Figure 4 Figure 2 is a second direction appearance schematic view of a natural gas pipeline liquid droplet content monitoring device provided by the embodiment of the present application.

[0071] Figure 3 and Figure 4In the figure, 1 represents the control unit (i.e. remote control machine), 2 represents the power supply and remote transmission facility, 3 represents the explosion-proof meter head, 4 represents the signal local oscillator and processing unit (i.e. signal management unit), 5 represents the connecting flange, 6 represents the detection pipeline, 7 represents the feeding signal high-voltage probe (i.e. signal input probe), 8 represents the 8-15 GHz signal input channel, 9 represents the 18-25 GHz signal input channel, 10 represents the 0-3 GHz signal input channel, 11 represents the power supply and communication optical fiber line, 12 represents the real-time display screen, 13 represents the receiving signal high-voltage probe (i.e. signal receiving probe), 14 represents the 0-3 GHz signal output channel, 15 represents the 18-25 GHz signal output channel, and 16 represents the 8-15 GHz signal output channel. The natural gas pipeline liquid droplet content monitoring device includes three feeding signal high-voltage probes and three receiving signal high-voltage probes. In this embodiment, the natural gas pipeline liquid droplet content monitoring device contains three signal frequency ranges of 0-3 GHz, 8-15 GHz and 18-25 GHz. The probe coupling line and the axis form an angle of 45°, and other values between 10° and 60° can also be set according to the actual situation.

[0072] The feeding signal high-voltage probe and the signal input channel are used as the multi-band detection unit, and the receiving signal high-voltage probe and the signal output channel are used as the multi-band detection unit.

[0073] The control unit 1 can control the working state of the overall system by remotely monitoring the signal local oscillator and processing unit, control the sending and receiving of the local oscillator signal, and jump feeding and collecting microwave signals in time, and can set the system monitoring time. The explosion-proof meter head and the real-time display screen are connected above the local oscillator and processing unit, which can display the main parameter information set by the control software in real time, and facilitate the on-site personnel to check the system monitoring state. The signal input channel and the signal output channel adopt stable phase radio frequency cables, which are connected with the signal local oscillator and processing unit, and are used to ensure low delay, high precision and stable transmission of the signal. The feeding signal high-voltage probe and the receiving signal high-voltage probe are a group of high-voltage probes, which are connected with the pipeline and the signal transmission cable. The coupling line of each probe and the axis form an angle of 45°, thereby increasing the propagation distance of the microwave signal in the pipeline. The detection pipeline can be connected to the on-site high-pressure pipeline to be measured through the connecting flange, and the system device can be connected to the on-site power supply and remote transmission facility through the power supply and communication optical fiber line.

[0074] The natural gas high-pressure pipeline liquid droplet monitoring device provided in this embodiment is designed with pressure-resistant sealing as a whole. Since the oil and gas high-pressure transportation pipeline is usually greater than 7 MPa, the multi-band detection unit adopts a sealing probe that can withstand a high pressure of greater than 20 MPa, which ensures the sealing of its own structure and accurate coupling with the pipeline, and can ensure the normal transmission of the microwave sweep signal while not interfering with the normal flow of the multiphase flow in the pipeline. Each unit is connected by a line and is not disturbed by the on-site environment, and can detect the liquid impurities in the gas-liquid two-phase flow system in the natural gas pipeline online and in real time.

[0075] The feeding signal high-voltage probe and the receiving signal high-voltage probe adopt an H-shaped end face design, as shown in Figure 5 Figure 5 An appearance schematic diagram of an H-shaped end face provided by an embodiment of the present application. The H-shaped end face refers to the end face of the cavity in the receiving signal high-voltage probe being H-shaped. The H-shaped end face design can improve the sensitivity of the signal, reduce the interference from external conditions, and ensure the air tightness of the high-voltage pipeline while realizing high-precision non-invasive detection.

[0076] The signal local oscillator and the data processing unit are connected with the on-site power supply and remote transmission device and the three groups of signal transceiving probes. Please refer to Figure 6 Figure 6 A structure schematic diagram of a signal local oscillator and a data processing unit provided by an embodiment of the present application.

[0077] 4-55 is a communication network port and a power supply interface connected with the on-site power supply and remote transmission device 2, 4-1, 4-2, and 4-3 are 0~3GHz microwave oscillators, 4-9, 4-10, and 4-11 are 8~15GHz microwave oscillators, 4-17, 4-18, and 4-19 are 18~25GHz microwave oscillators, 4-1 sends 0~3GHz sweep frequency signals for output work, 4-9 sends 8~15GHz sweep frequency signals for output work, 4-17 sends 18~25GHz sweep frequency signals for output work, 4-2 and 4-3 are used as the first and second intermediate frequency local oscillators of the frequency band, for receiving link down-conversion, 4-10, 4-11, 4-18, and 4-19 are also used as the first and second intermediate frequency local oscillators to send intermediate frequency signals for frequency conversion. 4-4, 4-5, 4-6, 4-12, 4-13, 4-14, 4-20, 4-21, and 4-22 are filters for suppressing harmonic output mixing spur, and 4-7, 4-8, 4-15, 4-16, 4-23, and 4-24 are power division amplifiers for amplifying the local oscillator source, transmission output power, and local oscillator signals in common with the receiving branch. 4-1~4-24 jointly form a local oscillator module.

[0078] ​​4-34, 4-44, 4-54 are directional couplers for signal distribution, 4-31, 4-32, 4-33, 4-41, 4-42, 4-43, 4-51, 4-52, 4-53 are mixers for transmitting first high frequency output mixing and receiving input second intermediate frequency mixing, 4-28, 4-29, 4-30, 4-38, 4-39, 4-40, 4-48, 4-49, 4-50 are filters, 4-25, 4-26, 4-27, 4-35, 4-36, 4-37, 4-45, 4-46, 4-47 are demodulators for demodulating the filtered signal into i / q signal output, 4-25~4-34 constitute 0~3GHz frequency band reference signal demodulation straight line, reference reflection signal demodulation straight line and reference reflection signal demodulation straight line, 4-35~4-44 constitute 8~15GHz frequency band reference signal demodulation straight line, reference reflection signal demodulation straight line and reference reflection signal demodulation straight line, 4-45~4-54 constitute 18~25GHz frequency band reference signal demodulation straight line, reference reflection signal demodulation straight line and reference reflection signal demodulation straight line.

[0079] 4-56 is an ICP / IP communication module, externally connected to a host computer, 4-57 is a network connector, 4-58 is an ADC chip for receiving branch intermediate frequency demodulation analog-to-digital conversion, 4-59 is a DAC chip for forming intermediate frequency modulation signal, 4-60, 4-61 are FPGA chip and ARM chip for logic control and floating point calculation, 4-62 is a TCXO reference clock as system clock and phase-locked loop reference clock, 4-63 and 6-64 are resistance and capacitance elements. 4-56~4-64 and other communication and data processing elements are located on a multi-layer integrated circuit board, and the signal data is transmitted to the control unit after processing.

[0080] The control unit includes a human-computer interaction module and a neural network module, and the demodulated multi-band reference signal, reference reflection signal, backhaul received signal and other signal data are transmitted to the control unit after analysis. The neural network module of the control unit processes the received data to obtain target sample data, 70% as a training set, 20% as a validation set, and 10% as a test set. The neural network model is trained using the signal fluctuation of each frequency band collected under different scenarios, so as to automatically select the best frequency band signal data for different liquid substances under different test object conditions. After the convolutional neural network model output result is verified, the data analysis result is output by the human-computer interaction module, and the data processing flow is as shown in Figure 7 Figure 7 ​A convolutional neural network model data processing flowchart is provided in the embodiments of the present application. The specific process is as follows: signals under three different frequency bands are obtained, the microwave signal demodulation data is input into the convolutional layer and the pooling layer to extract the sequence local features, the eigenvalue of the dielectric constant is taken as the label by using the full connection layer, the MSE (mean square error loss function) and the MAE (mean absolute error loss function) are taken as the loss function to judge the model precision, and the full connection layer is connected with the output layer. The trained convolutional neural network model can be embedded into a human-computer interaction module. The best frequency band signal data can be obtained after the probe frequency band signal data is input into the human-computer interaction module.

[0081] The signal local oscillator and the processing unit analyze the amplitude and phase change parameters of each frequency band, and the two parameters are associated in one formula to obtain the concentration and content information. The change of the two parameters of each frequency band will obtain the corresponding concentration and content information. In order to improve the measurement accuracy, it is necessary to select a best frequency band, and the concentration and content information measured by the frequency band are the most accurate.

[0082] The convolutional neural network model can determine which is the best frequency band signal. The basis of this determination is that the amplitude of the change of the two parameters of which frequency band is the largest, and which frequency band reacts more strongly and changes more sensitively compared with the reference signal (when the pipeline is not filled with gas). Therefore, this frequency band is considered to be the best frequency band. The purpose of training the neural network model also includes improving the screening speed. This is to automatically and quickly complete the screening process in different scenarios and in the face of different liquid phase impurities (because the dielectric constants of different liquid phase impurities are different, therefore the amplitude of the change of the two parameters and the reaction sensitivity of the microwave signal used for testing will also be different).

[0083] The embodiment collects microwave data through a pipeline high-voltage probe. After demodulating the data, the amplitude and phase changes caused by the change of dielectric constant of the gas-liquid flow system are obtained, so as to analyze the content and concentration of the liquid phase in the pipeline. Combined with deep learning technology, a convolutional neural network model is trained, a data analysis algorithm is established, and the best frequency band is demodulated, so as to realize automatic and efficient real-time monitoring of liquid phase impurities in the natural gas pipeline. After receiving the control software instruction, each radio frequency output probe feeds the three radio frequency signals into the pipeline through the high-voltage probe. The three radio frequency signals refer to: the local oscillator unit in the 0GHz-3GHz frequency band generates a 0GHz-3GHz sweep signal for output work, generates a 1.9GHz-2.6GHz sweep signal for three channels, and serves as the first intermediate frequency local oscillator; generates a 1.2GHz fixed frequency for three channels, and serves as the second intermediate frequency local oscillator; the local oscillator unit in the 8GHz-15GHz frequency band generates a 8GHz-15GHz sweep signal for output work, generates a 9.9GHz-12.6GHz sweep signal for three channels, and serves as the first intermediate frequency local oscillator; generates a 3.2GHz fixed frequency for three channels, and serves as the second intermediate frequency local oscillator; the local oscillator unit in the 18GHz-25GHz frequency band generates a 18GHz-25GHz sweep signal for output work, generates a 18.9GHz-22.6GHz sweep signal for three channels, and serves as the first intermediate frequency local oscillator; generates a 5.2GHz fixed frequency for three channels, and serves as the second intermediate frequency local oscillator; the multi-channel radio frequency signal is mixed and converted by the receiving unit, so as to quickly process the signal. After the radio frequency receiving probe receives the sweep signal and is detected by the control software, the radio frequency signal is converted and demodulated, and the target data is imported into the trained convolutional neural network model and the best test frequency band is selected. In the embodiment, the first local oscillator radio frequency and the second local oscillator radio frequency used for frequency conversion in each frequency band can be replaced by other intermediate frequency bands according to economy and reliability, and the three radio frequency signals can also be replaced by other multi-channel signals.

[0084] The embodiment adopts frequency hopping data sampling and analysis with a set time interval. The time hopping data collection and analysis refers to setting the data collection and processing interval time by the control system, such as 5s, 10s, etc., that is, feeding in the signal and analyzing once every 5s or 10s, which improves the detection efficiency and saves energy in long-term monitoring of pipeline operation, thereby realizing long-term online pipeline monitoring in an efficient and energy-saving manner. The detection results are reflected in the control software after being analyzed by the data analysis module and the neural network module, realizing small detection error, fast speed, and real-time performance.

[0085] See Figure 8 , Figure 8The working principle diagram of the natural gas pipeline liquid drop content monitoring device provided by the embodiment of the application is shown in the figure, and the ARM+FPGA embedded processing system, the local oscillator module, the high-voltage probe, the pipeline flowing liquid phase detection module, the wave detection module, the frequency conversion module, the demodulation module, the data analysis module, the neural network module, the man-machine interaction module, and the power supply and communication module are shown.

[0086] The coaxial coupling of each group of high-voltage sealed probes in the detection unit ensures the accurate propagation of the signal. On the basis of the array arrangement of the detection device, the fixed angle of the radio frequency probe and the frequency receiving probe is set to 45°, which increases the propagation distance of the microwave signal in the pipeline, is conducive to obtaining more data information of the gas-solid two-phase flow or the gas-liquid two-phase flow in the pipeline, and at the same time reduces the interference caused by the reflection of the microwave signal in the pipeline.

[0087] After the local oscillator unit receives the signal of the control software, the high-voltage probe feeds each frequency band microwave signal into the pipeline, the receiving unit frequency demodulates the swept frequency signal, and then the data processing unit performs ADC waveform acquisition, DAC waveform output, and FFT calculation of frequency Doppler, phase and amplitude. After the detection data is preprocessed into target data, the neural network model is input into the trained convolutional neural network model, and the neural network model output data is stored in the control unit. The test data is stored in the form of tables, images, etc. in the background and labeled with the working time of the test start and end. In the control software and the test pipeline table header, the working condition of the oil and gas transportation pipeline can be viewed online in real time.

[0088] Please refer to Figure 9 , Figure 9 The working flow chart of the natural gas pipeline liquid drop content microwave detection system provided by the embodiment of the application is as follows:

[0089] The microwave signal frequency band detection time interval is set, the high-voltage probe of each frequency band feeds the frequency band swept frequency microwave signal into the pipeline, the corresponding frequency band signal receiving probe receives the swept frequency signal in the pipeline, the demodulated swept frequency signal obtains the data information of the impurities in the multiphase flow system, the control software combines the network to quickly process the data, and the liquid phase impurity concentration and content in the pipeline are reflected in real time. The above process can also input the target data into the pre-trained convolutional neural network model after obtaining the data information of the impurities in the multiphase flow system by demodulating the swept frequency signal, and the control software combines the network to quickly process the data, and the liquid phase impurity concentration and content in the pipeline are reflected in real time.

[0090] The embodiment provides a kind of liquid drop content monitoring device in natural gas pipeline, using microwave detection technology, contain multiple microwave frequency range, cooperate with microwave pipeline test tool fixture to carry out online microwave data acquisition to the liquid drop impurities in the pipeline flowing in multiple field scenes such as wellhead, end oil remover after etc., qualitative and quantitative analysis is carried out to the liquid drop impurities in the pipeline flowing by data processing, real-time online non-invasive monitoring.Oil remover is used to remove liquid hydrocarbon (usually oil and water) from natural gas equipment, usually installed at the end of natural gas pipeline system or the inlet of natural gas processing equipment.Liquid drop content monitoring device includes host computer and detection system.Detection system includes control unit, multi-band detection unit, receiving unit and data processing unit.Control unit passes digital signal to detection unit, detection unit receives demodulation digital signal and then feeds radio frequency signal to pipeline by high-voltage probe, working radio frequency signal passes through microwave detector to reflect working condition to control software, then phase amplitude information is generated by two-phase flow in pipeline.Receiving unit receives the sweep signal of detection unit and carries out filtering and conversion, finally data processing unit demodulates signal to pipeline internal two-phase flow impurity data information and records and analyzes by combining neural network model.Microwave detector is a two-terminal device for detecting and converting radio frequency signals.In radio frequency circuit and radio frequency system, microwave detector can detect the transmission power level of radio frequency signal in a specific frequency range.Filtering is the operation of filtering specific band frequency in signal, and is an important measure to suppress mixing spur and prevent interference.

[0091] The specific implementation of the liquid drop content monitoring device in natural gas pipeline provided by the embodiment is as follows:

[0092] Step 1, after connecting power supply and communication facilities, check whether the connection between detection pipeline and field pipeline to be detected is sealed.

[0093] Step 2, use host computer control software to issue control instructions, manually or set running time limit, select whether sweep signal time interval frequency hopping scanning and interval time, while frequency single frequency point operation or cyclic scanning operation can be set, sweep step can be set to integer multiple of 1KHz, maximum limit is 10MHz.

[0094] Step 3, after waiting for detection, start recording detection data and starting time.

[0095] Step 4, real-time view data analysis algorithm and neural network model output main data parameters.

[0096] Step 5, save detection record file stored in background after ending detection.

[0097] The natural gas pipeline liquid droplet content monitoring device provided in the embodiment has a working temperature range and a storage temperature range of -20℃ to +70℃. The surface of the device is subjected to oxidation treatment, and the detection performance parameters of the whole machine are as follows:

[0098] AC power supply: 220±30V;

[0099] Power consumption: ≤100W;

[0100] External output and receiving frequency range: 9.6GHz~22.2GHz;

[0101] Sweeping step: ≥1Hkz, ≤10MHz;

[0102] Frequency switching time: ≤30us;

[0103] Single frequency point output width: 80us;

[0104] Receiving sensitivity: -70dBm;

[0105] Receiving dynamic range: ≥77dBc;

[0106] Receiving image rejection: ≥60dBc;

[0107] In-band spurious: ≤60dBc;

[0108] Demodulation resolution: amplitude 0.2dB; phase: 0.25°;

[0109] Material: aluminum alloy.

[0110] The detection device provided in the embodiment adopts a microwave detection method, has high detection speed and high precision, and does not affect the normal operation of the pipeline. The device as a whole adopts pressure-resistant design, can be applied to high-pressure natural gas pipelines, and solves the defects of the existing detection methods, such as blocked detection and lack of real-time performance. The probe adopts H-shaped end face design to reduce the interference of the field environment and improve the signal receiving and transmitting sensitivity. The fixed angle of the radio frequency probe and the receiving frequency probe is set to 45°, which increases the propagation distance of the microwave signal in the pipeline and reduces the interference of reflection, and improves the detection precision. The detection device contains three signal frequency ranges of 0~3GHz, 8~15GHz and 18~25GHz, and is suitable for detecting a wide variety of liquid substances. It can be applied in the pipeline of the natural gas wellhead and subsequent processing, storage and other links, for example, the liquid phase impurities in the wellhead high water content natural gas are mainly water droplets, and the oil mist is mainly before and after the oil remover. The natural gas wellhead refers to the outlet part of the natural gas extraction well on the ground. The water content in the natural gas extracted from the ground is relatively large. The signal local oscillator and the processing unit jump in time to feed and collect the microwave signal, and can set the system monitoring time. Combined with the neural network model, the best frequency band demodulation data is selected, and the liquid phase impurities in the natural gas pipeline can be automatically and real-timely monitored for a long time. The embodiment can realize online real-time monitoring of the liquid phase impurities contained in the natural gas in the pipeline, and can provide evaluation basis for natural gas transportation and processing separation efficiency. The arrayed multi-band detection device can select the frequency scanning band with pertinence according to the different states and different properties of the liquid phase impurities in the actual application scene, realizes fast detection speed while ensuring the accuracy of the detection structure. It has real-time performance, can be used for online measurement and long-term monitoring in industrial field, has fast signal processing speed, high anti-interference performance and reliability, and can adapt to harsh industrial application environment. The software and hardware structure of the detection device is simple, and is convenient to use, maintain and manage.

[0111] The embodiment adopts microwave detection technology, and arrayed microwave resonance probe realizes non-invasive online measurement of liquid content concentration in high-pressure pipeline gas, does not affect the flow system in the pipeline, and realizes multi-band and high-precision measurement. The sweep signal range is large, can adapt to more application scenes, and has real-time performance.

[0112] The embodiment optimizes the structure of the high-pressure sealed probe device, uses an H-shaped end face resonant probe, improves the sensitivity of the probe, sets the fixed angle of the radio frequency probe and the frequency receiving probe to 45°, increases the propagation distance of the microwave signal in the pipeline, is conducive to the collection of the microwave signal and reduces the reflection of the microwave signal on the inner wall of the pipeline. The embodiment realizes efficient and long-term detection by frequency hopping sampling and processing data in time. The embodiment combines deep learning technology and deep convolutional neural network in signal processing, outputs data processing results through the data processing algorithm of the trained neural network model, provides technical support for adapting to various liquid detection substances in the field, and can realize automatic monitoring of the state of the flowing substances in the pipeline. The embodiment processes each signal, shortens the signal processing time, improves the signal processing efficiency, processes multiple signals through the signal processing algorithm, improves the resistance of the detection system to interference, and is conducive to improving the reliability and stability of the system.

[0113] The gas pipeline liquid droplet content monitoring method provided by the embodiment of the application is applied to a control unit of the gas pipeline liquid droplet content monitoring device, and includes the following steps.

[0114] Receiving N radio frequency collection signals transmitted by the signal management unit.

[0115] According to the N radio frequency collection signals, the liquid droplet content in the detection pipeline is calculated.

[0116] The gas pipeline liquid droplet content monitoring device applied by the embodiment includes a control unit, a signal management unit, a detection pipeline, and a signal transceiver assembly. Multiple signal input probes and signal receiving probes in the signal transceiver assembly are arranged inside the detection pipeline. The signal management unit feeds radio frequency input signals into the detection pipeline and receives radio frequency collection signals from the signal receiving probes, so as to calculate the liquid droplet content in the detection pipeline based on the radio frequency collection signals. In the embodiment, the arrangement of the signal input probes and the signal receiving probes does not interfere with the gas flow in the pipeline, and the transmission of the radio frequency signals does not change the flow path or speed of the gas, thereby ensuring the normal operation of the pipeline system and the stability of the gas flow. In the above scheme, the liquid droplet content is determined based on the signals received by the signal receiving probes, which can determine the current liquid droplet content in the pipeline in an online detection manner. Therefore, the embodiment can realize non-intrusive online detection of the liquid droplet content and reduce the influence on the gas flow in the pipeline.

[0117] Further, the signal input probe and the signal receiving probe are probes with a preset end face; wherein the preset end face is an H-shaped end face, an M-shaped end face, or a U-shaped end face.

[0118] Further, the angle between the signal input probe and the first axis is 45°, and the angle between the signal receiving probe and the second axis is 45°; wherein the distance from any point on the first axis to all the signal input probes is the same, and the distance from any point on the second axis to all the signal receiving probes is the same.

[0119] Further, the liquid droplet content in the detection pipeline is calculated according to the N-channel radio frequency acquisition signals, comprising:

[0120] The 1-channel radio frequency acquisition signal meeting the preset constraint condition is selected from the N-channel radio frequency acquisition signals as the preferred signal by using the convolutional neural network model.

[0121] The liquid droplet content in the detection pipeline is calculated according to the preferred signal.

[0122] Further, the liquid droplet content in the detection pipeline is calculated according to the preferred signal, comprising:

[0123] The liquid droplet content in the detection pipeline is calculated according to the amplitude change information and the phase change information of the preferred signal.

[0124] Further, the signal frequency range of the first signal input channel and the first signal output channel is 0-3 GHz, the signal frequency range of the second signal input channel and the second signal output channel is 8 GHz-15 GHz, and the signal frequency range of the third signal input channel and the third signal output channel is 18 GHz-25 GHz.

[0125] Further, the detection pipeline is provided with a connecting flange at both ends for connecting the detection pipeline and the gas pipeline.

[0126] Since the embodiments of the method part correspond to the embodiments of the device part, the embodiments of the method part are described in the description of the embodiments of the device part, and will not be described here.

[0127] The application also provides a storage medium having a computer program stored thereon, which can implement the steps provided by the above embodiments when executed. The storage medium can include: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0128] The application also provides an electronic device, which can include a memory and a processor, the memory has a computer program stored therein, and the processor can implement the steps provided by the above embodiments when invoking the computer program in the memory. Of course, the electronic device can also include various network interfaces, power supplies, and other components.

[0129] The various embodiments are described in the specification by way of progressive progression, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be mutually referred to. For the device disclosed by the embodiments, since it corresponds to the method disclosed by the embodiments, the description is relatively simple, and the relevant parts can be referred to the method part. It should be pointed out that, for those skilled in the art, without departing from the principles of the application, some improvements and modifications can be made to the application, and these improvements and modifications also fall within the protection scope of the application.

[0130] It should also be noted that in the specification, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or device including the element.

Claims

1. A device for monitoring the liquid droplet content of a gas pipeline, characterised in that, The application relates to a signal detection device for detecting liquid droplets in a gas pipeline. The device comprises a control unit, a signal management unit, a detection pipeline and a signal transceiving assembly. The signal transceiving assembly comprises N signal input probes, N signal receiving probes, N signal input channels and N signal output channels, the signal input probes and the signal receiving probes are arranged in the detection pipeline, the first ends of the signal input channels and the signal output channels are connected with the signal management unit, the second end of the ith signal input channel is connected with the ith signal input probe, and the second end of the ith signal output channel is connected with the ith signal receiving probe; wherein N>=2, 1<=i<=N. The signal management unit is used for feeding N radio frequency input signals into the detection pipeline through the signal input channels and the signal input probes, receiving N radio frequency collection signals through the signal receiving probes and the signal output channels, and transmitting the N radio frequency collection signals to the control unit; wherein the signal frequency range of the radio frequency input signal fed by the ith signal input probe is the same as that of the radio frequency collection signal received by the ith signal receiving probe. The control unit is used for calculating the liquid droplet content in the detection pipeline according to the N radio frequency collection signals. A convolutional neural network model is arranged in the control unit. Correspondingly, the control unit comprises: a signal screening subunit used for selecting one radio frequency collection signal meeting a preset constraint condition from the N radio frequency collection signals as an optimal signal by using the convolutional neural network model; a data calculation subunit used for calculating the liquid droplet content in the detection pipeline according to the optimal signal. The data calculation subunit is used for calculating the liquid droplet content in the detection pipeline according to the amplitude change information and the phase change information of the optimal signal. The process of calculating the liquid droplet content by the data calculation subunit comprises: pre-establishing a mathematical model between the liquid droplet content and the amplitude change information and the phase change information; inputting the amplitude change information and the phase change information into the mathematical model to obtain the liquid droplet content by calculation. The formula corresponding to the mathematical model comprises: ； ； ； ； ； wherein is the mixture dielectric constant, is the liquid phase dielectric constant, is the gas phase dielectric constant; is the mass concentration of the liquid phase, is the mass concentration of the gas phase, is the component dielectric loss factor, is the component energy storage characteristic, is the incident wavelength, is the differential sign, is the amplitude, is the phase, is the amplitude-phase joint parameter, is the preset coefficient, is the liquid phase concentration, f is a relationship function.

2. The apparatus for monitoring the content of liquid droplets in a gas pipeline according to claim 1, characterized in that, The signal input probes and the signal receiving probes are probes with preset end faces; wherein the preset end faces are H-shaped end faces, M-shaped end faces or U-shaped end faces.

3. The apparatus for monitoring the liquid droplet content of a gas pipeline according to claim 1, wherein The included angle between the signal input probes and the first axis is 45 degrees, and the included angle between the signal receiving probes and the second axis is 45 degrees; wherein the distance between any point on the first axis and all the signal input probes is the same, and the distance between any point on the second axis and all the signal receiving probes is the same.

4. The apparatus for monitoring the liquid droplet content in a gas pipeline according to claim 1, wherein The signal frequency range of the first signal input channel and the first signal output channel is 0-3 GHz, the signal frequency range of the second signal input channel and the second signal output channel is 8 GHz-15 GHz, and the signal frequency range of the third signal input channel and the third signal output channel is 18 GHz-25 GHz.

5. The apparatus for monitoring the liquid droplet content of a gas pipeline according to claim 1, wherein The two ends of the detection pipeline are provided with connecting flanges for connecting the detection pipeline and the gas pipeline.

6. A method of monitoring the liquid droplet content of a gas pipeline, characterised by, The control unit applied to the monitoring device of the liquid droplet content in the gas pipeline according to any one of claims 1 to 5, the monitoring method of the liquid droplet content in the gas pipeline comprises: Receiving the N-way radio frequency acquisition signals transmitted by the signal management unit; According to the N-way radio frequency acquisition signals, the liquid droplet content in the detection pipeline is calculated.

7. An electronic device, comprising: The memory and the processor are included, the computer program is stored in the memory, and the processor calls the computer program in the memory to realize the steps of the liquid droplet content method in the gas pipeline in claim 6.

8. A storage medium, characterized by The computer executable instructions are stored in the storage medium, the computer executable instructions are loaded and executed by the processor, and the steps of the liquid droplet content method in the gas pipeline in claim 6 are realized.

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