Natural gas production station process unit integrity digital intelligent diagnosis method, system and equipment and storage medium

Abstract

The invention relates to the technical field of leakage detection, in particular to a digital intelligent diagnosis method, system and equipment for integrity of a process device of a natural gas production station and a storage medium. The digital intelligent diagnosis method for the integrity of the process device of the natural gas production station comprises the following steps: acquiring structural parameter information of a to-be-detected gas pipeline; constructing a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected according to the structure parameter information; collecting pipeline operation data of the gas pipeline to be detected; performing analog simulation on a pipeline leakage process by using the pipeline operation data and the three-dimensional pipeline leakage geometric model so as to determine fluid flow state information in the gas pipeline to be detected; and judging whether the gas pipeline to be detected leaks or not according to the fluid flowing state information to obtain a gas pipeline integrity diagnosis result. According to the invention, the convenience of monitoring the integrity of the pipeline by a worker can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of leak detection, and in particular to a digital intelligent diagnosis method, system, equipment and storage medium for the integrity of process equipment at a natural gas production station. Background Art

[0002] Due to their underground installation and complex operating environments, urban gas pipelines present high leakage risks, hidden accidents, and difficulty in real-time monitoring. Existing leak detection technologies primarily rely on negative pressure wave or acoustic wave methods, but these single methods are susceptible to environmental interference, have high rates of missed and false alarms, and struggle to accurately locate leaks. Furthermore, traditional detection systems suffer from low data acquisition efficiency and lack the ability to couple and analyze multiple parameters (such as pressure, acoustic waves, and temperature), resulting in insufficient detection sensitivity. Summary of the Invention

[0003] The present application aims to at least solve the technical problems existing in the prior art, and provide a method, system, equipment and storage medium for digital diagnosis of the integrity of process equipment in a natural gas production station, and in particular relates to digital diagnosis of the integrity of gas pipelines in process equipment in a natural gas production station.

[0004] In a first aspect, the present invention provides a method for digitally diagnosing the integrity of process equipment at a natural gas production station, comprising:

[0005] Obtaining structural parameter information of the gas pipeline to be inspected;

[0006] Construct a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on the structural parameter information;

[0007] Collect pipeline operation data of the gas pipeline to be inspected;

[0008] The pipeline leakage process is simulated using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected;

[0009] The gas pipeline integrity diagnosis result is obtained by judging whether the gas pipeline to be inspected is leaking based on the fluid flow state information.

[0010] In a second aspect, the present invention provides a digital intelligent diagnostic system for process equipment integrity at a natural gas production station, the system comprising:

[0011] An acquisition module is used to obtain structural parameter information of the gas pipeline to be detected;

[0012] An acquisition module, used to collect pipeline operation data of the gas pipeline to be inspected;

[0013] A model building module is used to build a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on structural parameter information;

[0014] The simulation module is used to simulate the pipeline leakage process using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected;

[0015] The output module is used to determine whether the gas pipeline to be inspected is leaking based on the fluid flow state information and obtain the gas pipeline integrity diagnosis result.

[0016] In a third aspect, the present invention provides an electronic device, comprising:

[0017] at least one processor; and,

[0018] a memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the above-mentioned digital intelligent diagnosis method for the integrity of process equipment at a natural gas production site.

[0020] In a fourth aspect, the present invention also provides a computer-readable storage medium, in which at least one computer program is stored. The at least one computer program is executed by a processor in an electronic device to implement the above-mentioned digital intelligent diagnosis method for the integrity of process equipment at a natural gas production station.

[0021] In summary, this application has the following beneficial technical effects:

[0022] A three-dimensional pipeline leakage geometric model is constructed through structural parameter information, and pipeline operation data is collected in real time. The pipeline operation data and the three-dimensional pipeline leakage geometric model are used to simulate the state of the internal flow field of the gas pipeline to be inspected. It can automatically calculate whether the gas pipeline to be inspected is leaking based on the pipeline operation data, so that the staff can monitor the integrity of the pipeline; by analyzing the pressure fluctuation data and acoustic wave characteristics of the pipeline during operation, it can efficiently identify the leakage state and locate the position of the pipeline leakage, thereby improving the safe operation level of the gas pipeline. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of a flow chart of a method for digitally diagnosing the integrity of process equipment at a natural gas production station according to one embodiment of the present invention;

[0024] Figure 2 It is a schematic diagram of the three-dimensional pipeline leakage geometric model;

[0025] Figure 3 A grid diagram of a gas pipeline to be inspected provided in one embodiment of the present invention;

[0026] Figure 4 Schematic diagram of the arrangement of numerical probes;

[0027] Figure 5 The dynamic changes of pressure (left) and velocity (right) at the pipeline leakage location;

[0028] Figure 6 The noise intensity distribution diagram near the leakage port before and after leakage;

[0029] Figure 7 A schematic structural diagram of an electronic device for implementing the digital and intelligent diagnosis method for process equipment integrity at a natural gas production station provided in one embodiment of the present invention.

[0030] Reference numerals: 10, processor; 11, memory; 12, communication bus; 13, communication interface.

[0031] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0032] The following describes embodiments of the present invention in detail. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended only to explain the present invention and are not to be construed as limiting the present invention.

[0033] In the description of the present invention, it should be understood that the terms "longitudinal", "transverse", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating the orientation or position relationship, are based on the orientation or position relationship shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention.

[0034] In the description of the present invention, unless otherwise specified and limited, it should be noted that the terms "installed", "connected" and "connected" should be understood in a broad sense. For example, it can be a mechanical connection or an electrical connection, or it can be the internal communication between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0035] Reference Figure 1The figure shows a flow chart of a method for digitally diagnosing the integrity of a natural gas production station process unit according to one embodiment of the present invention. Digitally diagnosing the integrity of a natural gas production station process unit includes a gas pipeline, a compressor, a gas storage device, and a filtration and separation device. In this embodiment, the gas pipeline is the gas pipeline, and the method for digitally diagnosing the integrity of the gas pipeline is improved. The method includes:

[0036] S1. Obtain structural parameter information of the gas pipeline to be inspected.

[0037] Specifically, the structural parameter information is a parameter representing physical information such as the structure and material of the gas pipeline to be inspected; the structural parameter information includes pipeline material (such as steel pipe, plastic pipe or composite material pipe, etc.), pipeline specifications (such as pipeline inner diameter, pipeline outer diameter, pipeline wall thickness), working pressure (the pressure range that the pipeline can withstand during normal operation), design pressure (the maximum pressure that the pipeline can withstand), pipeline connection method (such as threaded connection and welding, etc.) and transmission medium type (such as natural gas, liquefied petroleum gas, etc.), etc.

[0038] S2. Construct a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on the structural parameter information.

[0039] Specifically, 3D modeling software such as 3D Studio Max or VUE front-end 3D CAD can be used to build a three-dimensional pipeline leakage geometric model based on structural parameter information, or CFD (computational fluid dynamics) method can be used to represent the gas pipeline to be inspected in the form of a three-dimensional geometric grid.

[0040] S3. Collect pipeline operation data of the gas pipeline to be inspected.

[0041] Pipeline operation data includes a sequence of pressure fluctuation signals, acoustic wave signals, and pressure differential signals within the pipeline to be inspected. In this embodiment, the pipeline operation data is collected by sensors installed at designated locations on the gas pipeline to be inspected. Specifically, the pressure sensor collects pressure signals in real time at a set frequency to obtain a sequence of pressure fluctuation signals; the differential pressure sensor collects pressure differential signals, and the acoustic wave sensor collects acoustic wave signals.

[0042] In a preferred implementation of this embodiment, the digital intelligent diagnosis method for process equipment integrity at a natural gas production station further includes:

[0043] S31 , respectively amplifying the pressure fluctuation signal sequence, the sound wave signal sequence, and the pressure difference signal sequence.

[0044] Specifically, a preamplifier is used to amplify the analog signals collected by the pressure sensor, differential pressure sensor, and acoustic wave sensor. The preamplifier can amplify the weak leakage signals collected by the sensors. Since the leakage signal generated by a pipeline leak is inherently very weak, preamplification is necessary to avoid distortion during subsequent transmission when using this signal for detection and processing. In a preferred embodiment of this embodiment, since the collected leakage signal contains background noise and signals in some unwanted frequency bands, a separator is used to process the amplified analog signal to obtain a denoised analog signal. The separator extracts the useful signal frequency band, reduces out-of-band noise, and minimizes the possibility of frequency aliasing, ensuring smooth sampling. After denoising the amplified analog signal, an analog-to-digital converter is used to convert the denoised analog signal into a digital signal. The analog quantity of the leakage condition is also converted into a digital quantity to facilitate processing of pipeline operation data by a computer device (such as a host computer system).

[0045] S32. Integrate the amplified pressure fluctuation signal sequence, the acoustic wave signal sequence, and the pressure difference signal sequence to obtain a simulation data set, and use the simulation data set and the three-dimensional pipeline leakage geometric model to simulate the pipeline leakage process.

[0046] The simulation data set includes a digital signal set corresponding to each analog signal in the pressure fluctuation signal sequence, the sound wave signal sequence and the pressure difference signal sequence.

[0047] S4. Simulate the pipeline leakage process using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine fluid flow state information inside the gas pipeline to be inspected.

[0048] In this embodiment, computational fluid dynamics (CFD) is used to construct a three-dimensional pipeline leakage geometric model. The flow of the fluid inside the gas pipeline to be inspected is simulated based on the three-dimensional pipeline leakage geometric model and pipeline operation data. CFD (Computational Fluid Dynamics) is a computational method that uses mathematical methods to solve engineering problems related to fluid flow. When constructing a pipeline leakage model, simulation and analysis can be performed using CFD. The specific steps include establishing a geometric grid, selecting a solver, determining boundary conditions, solving and analyzing the equations, and verifying the results. Using CFD technology, computers can be used to analyze and display flow field phenomena, enabling flow field predictions in a relatively short period of time. CFD simulations can help understand fluid dynamics problems, provide guidance for experiments, and offer references for design, thereby saving time, manpower, and resources. The essence of CFD is solving equations. The appropriate model is selected for a specific physical flow phenomenon, and then the equations are solved to produce various field results.

[0049] Taking the leakage of natural gas pipelines of common sizes in cities as an example, a physical geometric model is established, such as Figure 2 The urban pipeline selected for study has a diameter of 150 mm. To minimize the impact of inlet and outlet boundary conditions on the flow field at the leak location during CFD calculations, the length of each end of the pipeline extends by more than six pipe diameters, resulting in a total pipe length of 2000 mm. The leak opening is located at the center of the pipeline, with a circular geometry, a 4 mm diameter, and a height extending by more than three times the diameter. The total length of the injection zone is 15 mm.

[0050] This application uses CFD software FLUENT to simulate and analyze the gas pipeline leakage process, and uses pre-processing software ICEM to model the flow field of pipeline leakage and establish a spatial discrete grid of the pipeline model, such as Figure 3 ICEM stands for The Integrated Computer Engineering and Manufacturing code for Computational Fluid Dynamics.

[0051] ICEM is mainly used for grid generation in CFD (computational fluid dynamics) simulations. It provides functions ranging from geometry creation, grid division, pre-processing condition setting to post-processing. First, the gas pipeline to be inspected is divided into several spatially discrete grids according to the physical spatial distribution. Spatial discretization is to divide the spatially continuous computational domain into many subdomains and determine the nodes in each area to generate a grid. The control equation is then discretized on the grid, that is, the control equation in the partial differential format is converted into a set of algebraic equations at each node. O-type grids are used in both circular pipes and leakage sections to ensure that the minimum angle of the grid is not less than 30°. Considering the influence of the boundary layer, all near-wall grids are encrypted.

[0052] Specifically, the steps of simulating the pipeline leakage process using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected include:

[0053] S41. Determine the boundary conditions of the three-dimensional pipeline leakage geometric model, the turbulence model, and the physical time step during simulation based on the pipeline operation data.

[0054] Specifically, the boundary conditions need to reflect the actual physical scenario (e.g., in a gas pipeline simulation, the inlet flow velocity = the economic flow velocity of 15 m / s).

[0055] The pipeline working condition simulated in this embodiment is a 0.8MPa urban medium-pressure gas pipeline, and the flow rate is selected as the economic flow rate of the gas network, 15m / s. In an example of this embodiment, the boundary conditions are set as follows: the inlet boundary is given a velocity inlet (15m / s), the outlet boundary is a pressure outlet (0.8MPa), and the leak port is set to a pressure outlet (1atm) after opening. 1atm refers to 1 standard atmospheric pressure, and 1atm is equal to 101325 Pascals (Pa); all wall surfaces are no-slip smooth walls; the inlet boundary represents the starting position of the fluid entering the calculation domain, and the outlet boundary represents the position where the fluid leaves the calculation domain. In the specific implementation process, the boundary conditions can be fine-tuned according to actual conditions, and this embodiment does not impose any restrictions.

[0056] The time term in steady-state and transient calculations uses automatic time stepping. The convergence criteria for the physical time step in steady-state calculations are that the difference between the inlet and outlet flow fields is less than ±0.5%, and the residual error of the flow field monitoring parameters is less than 10 -6 In transient calculations, the physical time step is set to 10 -4 s, 30 virtual time steps are set in each physical time step to ensure that all parameter residuals in each physical time step converge to 1×10 -4 the following.

[0057] In order to study the pressure and acoustic wave signal characteristics generated during the leakage process, a large number of numerical probes were arranged around the leakage port and in the pipeline. The five typical locations used for analysis in this embodiment are as follows: Figure 4 P0 is the middle position of the leak, which is used to monitor the pressure pulsation and noise level at the leak site. d1 The position of the leak port downstream of the leak port is 1 times the leak port diameter. d2 It is the position of one pipe diameter downstream of the leak, used to examine the pressure attenuation around the leak. u1 、P u2 For the corresponding P d1 、P d2 Upstream position, P d1 、P d2 Used to examine the attenuation of sound waves around a sound source.

[0058] S42. Use the three-dimensional pipeline leakage geometric model to calculate the stable flow field of the pipeline when there is no leakage, which is used as the initial condition for the transient simulation.

[0059] First, a pressure-based steady-state solver is used to calculate the steady flow field of the pipeline when there is no leakage, so as to obtain the steady-state flow field distribution of the gas pipeline to be inspected. This includes but is not limited to the steady-state distribution of parameters such as velocity field, pressure field, and temperature field (for example, the pressure gradient of the gas in the pipeline when it is flowing steadily).

[0060] Afterwards, the turbulence characteristic parameters of the steady flow field are calculated using a turbulence model. The turbulence characteristic parameters of the steady flow field include the steady-state values ​​of the turbulent kinetic energy (k) and the turbulent dissipation rate (ε). The turbulence model uses the standard k-ε two-equation model widely used in engineering. The standard k-ε two-equation model is based on two transport equations and solves k and ε for the wall. The extended wall function is used for wall treatment. The near-wall viscous region is calculated using a grid solver. When the grid is refined along the wall normal, the result deteriorates due to the reduced y+ value of the dense grid. The y+ value is a dimensionless parameter used to describe the boundary layer characteristics in fluid flow. When the y+ value is less than the reference value (the reference value is 15 in the preferred embodiment of this embodiment), an unbounded error will gradually occur in the wall shear force. The extended wall function does not rely on the wall law and is very suitable for complex flows, especially low Reynolds number flow problems. Since leakage causes local high subsonic / supersonic speeds, compressibility is considered in the calculation and the energy equation is used. In terms of sound simulation, the broadband noise model in the acoustic model is used in steady-state calculations to preliminarily predict the noise intensity level (dB). The broadband noise model is an effective noise model for steady-state calculations, with the advantage of minimal computational effort. The pressure pulsation near the sound source is solved through CFD calculations, and the process of noise propagation to the receiver is obtained from the analytical solution of the wave equation. The time term of the steady-state calculation uses an automatic time step, and the convergence criterion is that the difference in the inlet and outlet flow fields is less than ±0.5%, and the residual error of the flow field monitoring parameters is less than 10 -6 .

[0061] When using a grid solution to calculate the viscous area near the wall, the spatial discretization method is used to transform the continuous control equation into a discrete algebraic equation on the grid nodes. In this embodiment, the spatial discretization method is mainly used to control the discretization of the equation and the difference of variables:

[0062] Among them, the discretization of the control equation is to discretize the convection terms (such as velocity gradient) and diffusion terms (such as viscous stress) in the Navier-Stokes equations at the grid nodes; variable interpolation is to calculate the variable values ​​(such as velocity, pressure, k / ε) between adjacent grids through the second-order upwind scheme to ensure accuracy and stability.

[0063] S43. Based on the initial conditions of the transient leakage simulation, a three-dimensional pipeline leakage geometric model is used to simulate the transient flow field from closing to opening of the leakage port to determine the pressure fluctuation and noise intensity change at the moment of pipeline leakage and obtain model simulation data.

[0064] The model simulation data includes reference pressure fluctuation data and reference noise intensity change data at the moment of pipeline leakage; the actual pressure fluctuation data and actual noise intensity change data of the gas pipeline to be tested at each time point are determined based on the pipeline operation data.

[0065] The transient simulation is based on the steady-state simulation. The time term uses the first-order implicit advance method and the physical time step is set to 10 -4 s, set 30 virtual time steps in each physical time step to ensure that all parameter residuals in each physical time step converge to 10 -4 Below. The sound simulation uses the Ffowcs-Williams & Hawkings (FW-H) aeroacoustic model. The acoustic analogy model can solve the pressure pulsations near the sound source through CFD calculations, and the FW-H equation (Ffowcs-Williams & Hawkings equation) is used to obtain the process of noise propagation to the receiver. The FW-H equation is essentially a non-homogeneous wave equation and can be obtained through the continuity equation and the NS equation. The NS equation is the momentum balance equation for viscous fluid; the full English name of the NS equation is Navier-Stokesequations, which is translated into Navier-Stokes equations in Chinese.

[0066] S44. Compare the model simulation data and the pipeline operation data to obtain a comparison result, and determine the fluid flow state information inside the gas pipeline to be inspected based on the comparison result.

[0067] First, a steady-state simulation is performed, and then the transient flow field in the pipeline is simulated using the stable flow field as the initial field. If the transient flow field converges after 0.01s (the monitoring parameters change periodically), the transient flow field in the pipeline is stable at this time, that is, there is no leakage in the gas pipeline to be detected; if a stable state is not formed in the pipeline and there are significant fluctuation characteristics, it indicates that there is a leakage in the pipeline.

[0068] refer to Figure 5 and Figure 6 ,in, Figure 5 is the dynamic change process of pressure and velocity at the pipeline leakage location, where Figure 5 The left picture shows the dynamic change of pressure at the pipeline leakage location. Figure 5 The right picture in the figure shows the dynamic change of the velocity at the pipeline leakage location. Figure 6 is the noise intensity distribution near the leak before and after the leak, where Figure 6 The left picture in the figure shows the noise intensity distribution near the leak before leakage. Figure 6 The right figure in the figure shows the noise intensity distribution near the leak opening after a leak. The instant the leak opens, a transient pressure drop occurs within the leak opening, causing a dramatic negative pressure fluctuation at the leak location within the pipeline. The velocity within the leak opening gradually increases, forming a high-speed jet. During this process, the flow field experiences unsteady fluctuations for a period of time. When the flow field stabilizes again, the local air velocity within the leak opening increases, generating very strong noise.

[0069] Specifically, the steps of comparing the model simulation data and the pipeline operation data to obtain a comparison result, and determining the fluid flow state information inside the gas pipeline to be inspected according to the comparison result include:

[0070] S441 : Compare the reference pressure fluctuation data and the actual pressure fluctuation data to obtain a first comparison result.

[0071] The reference pressure fluctuation data can be set by the staff according to the structure, material, length and transmission medium of the pipeline. In the preferred implementation of this embodiment, CFD technology is used to simulate the changes in the internal pressure of the pipeline under different working conditions and different leakage diameters to obtain the change curve of the internal pressure of the pipeline. The reference pressure fluctuation change data is formulated based on the change curve of the internal pressure of the pipeline under different working conditions and different leakage diameters and the actual working conditions to improve the accuracy of the leakage detection results.

[0072] Compare the difference between the reference pressure fluctuation data and the actual pressure fluctuation data. If the first comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the first preset reference value, it indicates that the flow field inside the pipeline to be detected is a stable flow field, and the fluid flow state information inside the gas pipeline to be detected is that the fluid in the pipeline is not leaking; if the first comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is greater than or equal to the first preset reference value, it indicates that the stable flow inside the pipeline to be detected has changed, and there is a possibility of leakage of the medium in the pipeline.

[0073] S442: Compare the reference noise intensity change data and the actual noise intensity change data to obtain a second comparison result.

[0074] The reference noise intensity change data can also be set by the staff according to the structure, material, length and transmission medium of the pipeline. In the preferred implementation of this embodiment, CFD technology is used to simulate the changes in the internal noise of the pipeline under different pipeline pressures and working conditions, and the change curves of the internal noise of the pipeline under different pipeline pressures and working conditions are obtained; the reference noise intensity change data are formulated based on the change curves of the internal noise of the pipeline under different pipeline pressures and working conditions and the actual working conditions to improve the accuracy of the leakage detection results.

[0075] The difference between the reference noise intensity change data and the actual noise intensity change data corresponding to each time step is compared in turn. If the second comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the second preset reference value, it indicates that the flow field inside the pipeline to be detected is a stable flow field, and the fluid flow state information inside the gas pipeline to be detected is that the fluid in the pipeline is not leaking; if the second comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is greater than or equal to the second preset reference value, it indicates that the stable flow inside the pipeline to be detected has changed, and there is a possibility of leakage of the medium in the pipeline.

[0076] S443: Determine the fluid flow state information inside the gas pipeline to be inspected according to the first comparison result and the second comparison result.

[0077] If the first comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the first preset reference value, and / or the second comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the second preset reference value, then the fluid flow state information inside the gas pipeline to be detected is that the fluid in the pipeline is leaking out.

[0078] If the first comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is greater than or equal to the first preset reference value, and the second comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is greater than or equal to the second preset reference value, then the fluid flow state information inside the gas pipeline to be detected is that the fluid in the pipeline is not leaking.

[0079] S5. Determine whether the gas pipeline to be inspected is leaking based on the fluid flow state information, and obtain a gas pipeline integrity diagnosis result.

[0080] In another embodiment of the present application, when the gas pipeline integrity diagnosis result is that the gas pipeline has a leak, the method further includes:

[0081] S6. For each digital signal in the simulation data set, the signal in the pipeline operation data is analyzed in the time domain and the frequency domain to extract the leakage characteristic parameters.

[0082] The leakage characteristic parameters include the pressure wave attenuation rate, the acoustic wave spectrum peak and the signal propagation time difference. Among them, the pressure wave attenuation gradient is used to reflect the pressure drop rate near the leakage port. The leakage location and leakage diameter range are determined according to the acoustic wave spectrum peak. The signal propagation time difference is the acoustic wave propagation path difference.

[0083] S7. Determine the position coordinates of the pipeline leakage point based on the three-dimensional pipeline leakage geometric model and leakage characteristic parameters.

[0084] Specifically, the location coordinates of the pipeline leakage point are determined based on the three-dimensional pipeline leakage geometric model and leakage characteristic parameters, including:

[0085] S71. Use the pressure wave attenuation rate, acoustic wave spectrum peak, signal propagation time difference, and three-dimensional pipeline leakage geometric model to simulate the pipeline leakage process to determine the synchronous change relationship between the pressure fluctuation and noise intensity at the pipeline leakage port, and establish the association rules between the pipeline leakage flow field and the acoustic field.

[0086] S72. Determine the position coordinates of the pipeline leakage point according to the association rules between the pipeline leakage flow field and the acoustic field and the leakage characteristic parameters.

[0087] When a pipeline leaks, changes in the flow field directly affect the distribution of the acoustic field. The shape and size of the leak hole, as well as parameters such as the flow rate and pressure of the fluid, all influence the characteristics of the sound source and the distribution of the acoustic field. For example, the larger the cross-sectional area of ​​the leak hole and the closer it is to a circle, the faster the gas pressure drops, and the greater the flow rate, sound power level, and sound pressure. Changes in the acoustic field can also reflect the state of the flow field. By measuring the characteristics of the acoustic field, flow field parameters such as flow rate and pressure can be indirectly understood. For example, the shape and size of the leak hole can be inferred by analyzing the sound power level and sound pressure spectrum. By analyzing the association rules between the pipeline leakage flow field and the acoustic field, the leak point can be more accurately located, improving the accuracy of gas pipeline integrity diagnosis results.

[0088] Based on the same inventive concept, an embodiment of the present invention provides a digital intelligent diagnostic system for the integrity of process equipment at a natural gas production station.

[0089] The digital and intelligent diagnosis system for the integrity of process equipment at a natural gas production station described in the present invention can be installed in an electronic device. According to the functions implemented, the digital and intelligent diagnosis system for the integrity of process equipment at a natural gas production station includes an acquisition module, an acquisition module, a model building module, a simulation module, and an output module, wherein the acquisition module can acquire the structural parameter information of the gas pipeline to be detected; the acquisition module can acquire the pipeline operation data of the gas pipeline to be detected; the model building module can construct a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on the structural parameter information; the simulation module can simulate the pipeline leakage process using the pipeline operation data and the three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be detected; the output module can determine whether the gas pipeline to be detected is leaking based on the fluid flow state information, and obtain the gas pipeline integrity diagnosis result.

[0090] The module described in the present invention may also be referred to as a unit, which refers to a series of computer program segments that can be executed by a processor of an electronic device and can complete fixed functions, and is stored in a memory of the electronic device.

[0091] The various variations and specific examples of the digital and intelligent diagnosis method for the integrity of natural gas production station process equipment provided in the above embodiments are also applicable to the digital and intelligent diagnosis system for the integrity of natural gas production station process equipment in this embodiment. Through the above detailed description of the digital and intelligent diagnosis method for the integrity of natural gas production station process equipment, those skilled in the art can clearly know the implementation method of the digital and intelligent diagnosis system for the integrity of natural gas production station process equipment in this embodiment. For the sake of brevity of the specification, it will not be described in detail here.

[0092] This application also discloses an electronic device, such as Figure 7 Figure 2 is a schematic diagram of the structure of an electronic device for implementing a method for digitally diagnosing the integrity of process equipment at a natural gas production station, according to one embodiment of the present invention. The electronic device may include at least one processor 10, a memory 11 communicatively coupled to the at least one processor, a communication bus 12, and a communication interface 13. The electronic device may also include a computer program stored in the memory 11 and executable on the processor 10, such as a program for implementing a method for digitally diagnosing the integrity of process equipment at a natural gas production station.

[0093] Among them, in some embodiments, the processor 10 can be composed of an integrated circuit, for example, it can be composed of a single packaged integrated circuit, or it can be composed of multiple integrated circuits packaged with the same function or different functions, including one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and a combination of various control chips. The processor 10 is the control core (Control Unit) of the electronic device, which uses various interfaces and lines to connect the various components of the entire electronic device, and executes or executes the programs or modules stored in the memory 11 (for example, a method for executing digital diagnosis of the integrity of process equipment at a natural gas production site, etc.), and calls the data stored in the memory 11 to execute various functions of the electronic device and process data.

[0094] The memory 11 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a mobile hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a magnetic memory, a disk, an optical disk, etc. In some embodiments, the memory 11 may be an internal storage unit of an electronic device, such as a mobile hard disk of the electronic device. In other embodiments, the memory 11 may also be an external storage device of an electronic device, such as a plug-in mobile hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device. Furthermore, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 can not only be used to store application software and various types of data installed in the electronic device, such as the code of the method program for digital diagnosis of the integrity of process equipment at a natural gas production station, but can also be used to temporarily store data that has been output or is to be output.

[0095] The communication bus 12 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus may be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0096] The communication interface 13 is used for communication between the above-mentioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a WI-FI interface, a Bluetooth interface, etc.), which is generally used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a display (Display), an input unit (such as a keyboard (Keyboard)), optionally, the user interface may also be a standard wired interface, a wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, and an OLED (Organic Light-Emitting Diode, organic light-emitting diode) touch device, etc. Among them, the display may also be appropriately referred to as a display screen or a display unit, for displaying information processed in the electronic device and for displaying a visual user interface.

[0097] Figure 7 Only the electronic device with components is shown, and it can be understood by those skilled in the art that Figure 7The structure shown does not constitute a limitation of the electronic device, and may include fewer or more components than shown, or combine certain components, or arrange the components differently. For example, although not shown, the electronic device may also include a power supply (such as a battery) to power each component. Preferably, the power supply can be logically connected to at least one processor 10 through a power management device, so that functions such as charging management, discharging management, and power consumption management are implemented through the power management device. The power supply may also include one or more DC or AC power supplies, recharging devices, power failure detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include a variety of sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be repeated here.

[0098] It should be understood that the embodiment is for illustration only and the scope of the patent application is not limited to this structure.

[0099] Furthermore, if the module / unit integrated into the electronic device is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile.

[0100] The present application provides a computer-readable storage medium, including, for example, any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a mobile hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM). The computer-readable storage medium stores a computer program capable of being loaded by a processor and executing the method for digitally diagnosing the integrity of process equipment at a natural gas production station according to the above-described embodiment.

[0101] Throughout this specification, reference to terms such as "one embodiment," "some embodiments," "example," "specific example," "one implementation," "a preferred implementation," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0102] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to the embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the claims and their equivalents.

Claims

1. A digital intelligence diagnosis method for the integrity of process equipment at a natural gas production station, characterized by: The method comprises: Obtaining structural parameter information of the gas pipeline to be inspected; Construct a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on the structural parameter information; Collect pipeline operation data of the gas pipeline to be inspected, the pipeline operation data including pressure fluctuation signal sequence, sound wave signal sequence and pressure difference signal sequence inside the pipeline to be inspected; The pipeline leakage process is simulated using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected; The gas pipeline integrity diagnosis result is obtained by judging whether the gas pipeline to be inspected is leaking based on the fluid flow state information.

2. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 1, characterized in that: The method of simulating the pipeline leakage process by using pipeline operation data and a three-dimensional pipeline leakage geometric model includes: Amplifying the pressure fluctuation signal sequence, the sound wave signal sequence and the pressure difference signal sequence respectively; The amplified pressure fluctuation signal sequence, acoustic wave signal sequence and pressure difference signal sequence are integrated to obtain a simulation data set, and the pipeline leakage process is simulated using the simulation data set and a three-dimensional pipeline leakage geometric model.

3. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 1 or 2, characterized in that: When the gas pipeline integrity diagnosis result indicates that the gas pipeline has a leak, the method further includes: Analyze the signals in the pipeline operation data in the time domain and frequency domain respectively to extract leakage characteristic parameters; The location coordinates of the pipeline leakage point are determined based on the three-dimensional pipeline leakage geometric model and leakage characteristic parameters.

4. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 3, characterized in that: The leakage characteristic parameters include the pressure wave attenuation rate, the acoustic wave spectrum peak, and the signal propagation time difference. The method of determining the position coordinates of the pipeline leakage point based on the three-dimensional pipeline leakage geometric model and the leakage characteristic parameters includes: The pipeline leakage process is simulated using the pressure wave attenuation rate, acoustic wave spectrum peak, signal propagation time difference, and a three-dimensional pipeline leakage geometric model to determine the synchronous change relationship between the pressure fluctuation and noise intensity at the pipeline leakage point, and to establish the correlation rules between the pipeline leakage flow field and the acoustic field. The location coordinates of the pipeline leakage point are determined based on the association rules between the pipeline leakage flow field and the acoustic field and the leakage characteristic parameters.

5. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 1, characterized in that: The method of simulating the pipeline leakage process using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected includes: Determine the boundary conditions, turbulence model, and physical time step of the 3D pipeline leakage geometry model based on pipeline operation data; The three-dimensional pipeline leakage geometric model is used to calculate the steady flow field of the pipeline when there is no leakage, which is used as the initial condition for transient simulation. Based on the initial conditions of the transient leakage simulation, a three-dimensional pipeline leakage geometry model is used to simulate the transient flow field from the closing to the opening of the leak port to determine the pressure fluctuation and noise intensity change at the moment of pipeline leakage and obtain model simulation data; The model simulation data and pipeline operation data are compared to obtain a comparison result, and the fluid flow state information inside the gas pipeline to be inspected is determined based on the comparison result.

6. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 5, characterized in that: The model simulation data includes reference pressure fluctuation data and reference noise intensity change data at the moment of pipeline leakage; the actual pressure fluctuation data and actual noise intensity change data of the gas pipeline to be tested at each time point are determined based on the pipeline operation data; The comparison model simulation data and pipeline operation data are compared to obtain a comparison result, and the fluid flow state information inside the gas pipeline to be inspected is determined according to the comparison result; including: Comparing the reference pressure fluctuation data with the actual pressure fluctuation data to obtain a first comparison result; Comparing the reference noise intensity change data with the actual noise intensity change data to obtain a second comparison result; The fluid flow state information inside the gas pipeline to be inspected is determined according to the first comparison result and the second comparison result.

7. The method for digital diagnosis of process equipment integrity at a natural gas production station according to claim 6, characterized in that: If the first comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the first preset reference value, and / or the second comparison result is that the difference between the reference pressure fluctuation data and the actual pressure fluctuation data is less than the second preset reference value, then the fluid flow state information inside the gas pipeline to be detected is that the fluid in the pipeline is leaking out.

8. A natural gas production station process equipment integrity digital intelligent diagnosis system, used to implement the natural gas production station process equipment integrity digital intelligent diagnosis method according to any one of claims 1 to 7, characterized in that: include: An acquisition module is used to obtain structural parameter information of the gas pipeline to be detected; An acquisition module, used to collect pipeline operation data of the gas pipeline to be inspected; A model building module is used to build a three-dimensional pipeline leakage geometric model of the gas pipeline to be detected based on structural parameter information; The simulation module is used to simulate the pipeline leakage process using pipeline operation data and a three-dimensional pipeline leakage geometric model to determine the fluid flow state information inside the gas pipeline to be inspected; The output module is used to determine whether the gas pipeline to be inspected is leaking based on the fluid flow state information and obtain the gas pipeline integrity diagnosis result.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor (10); and, a memory (11) communicatively coupled to the at least one processor (10); Wherein, the memory (11) stores a computer program that can be executed by the at least one processor (10), and the computer program is executed by the at least one processor (10) so that the at least one processor (10) can execute the digital intelligent diagnosis method for the integrity of the process equipment of the natural gas production station as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program; when the computer program is executed by the processor, the digital intelligent diagnosis method for the integrity of the process equipment of the natural gas production station is implemented as described in any one of claims 1 to 7.

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