Intelligent gas self-closing valve capable of monitoring running state in real time

Abstract

The invention relates to the technical field of fuel gas safety control, and particularly discloses an intelligent fuel gas self-closing valve for real-time operation state monitoring, the intelligent fuel gas self-closing valve comprises a state monitoring system, the state monitoring system comprises a gas pressure waveform of a fuel gas channel in a gas supply recovery stage, a rising stage of the gas pressure waveform is subjected to parameter gradient analysis, and the rising stage of the gas pressure waveform is subjected to parameter gradient analysis; establishing an impact characteristic matrix; constructing a diaphragm-airflow coupling dynamic model, and judging whether the diaphragm has a water hammer impact risk or not; if yes, the minimum diaphragm effective impact force is extracted, and a real-time damping opening degree instruction is output; controlling a multi-stage flow channel based on the damping opening instruction, carrying out fluid kinetic energy vortex dissipation analysis on the flow channel, and judging whether a deformation analysis signal is triggered or not; and if triggering, performing material deformation analysis on the diaphragm to obtain a theoretical deviation of the diaphragm, positioning a dissipation flow weak link of the flow channel, and establishing a dynamic correction model for the dissipation weak link to adjust the distribution of the flow passage area of the flow channel.

Description

Technical Field

[0001] The present invention relates to the technical field of gas safety control, and in particular to an intelligent gas self-closing valve capable of real-time operating status monitoring. Background Art

[0002] The gas self-closing valve is a core component of gas terminal safety. It senses pipeline pressure changes through the diaphragm and automatically closes the valve under abnormal working conditions. The structural integrity of the diaphragm directly determines the reliability of the self-closing valve.

[0003] In actual use, during the gas supply restoration phase after a gas outage for maintenance or equipment restart, pipeline pressure can rise rapidly from the shutoff state. This high-speed filling of the pipeline by gas can easily cause a water hammer effect. This produces a transient high-pressure shock that directly impacts the diaphragm of the self-closing valve. The diaphragm has a defined yield strength limit, and the instantaneous force of the water hammer shock often exceeds the safe range, causing the diaphragm to deform, crack, or suffer fatigue damage. This can lead to self-closing valve failure and potentially create a gas leak.

[0004] To this end, the present invention provides an intelligent gas self-closing valve with real-time operating status monitoring. Summary of the Invention

[0005] The purpose of the present invention is to provide an intelligent gas self-closing valve with real-time operating status monitoring to solve the above-mentioned background problems.

[0006] The purpose of the present invention can be achieved through the following technical solutions: A smart gas self-closing valve with real-time operating status monitoring includes a status monitoring system, which includes the following modules: Transient capture module: This module obtains the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising section of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs an impact feature matrix. Impact prediction module: By combining coupled dynamics theory with the impact characteristic matrix, a diaphragm-airflow coupled dynamics model is constructed to obtain impact judgment characteristics and determine whether the diaphragm is at risk of water hammer impact; Damping control module: If there is a risk of water hammer impact, the effective impact force of the diaphragm-airflow coupling dynamic model is extracted, the opening control processing is performed based on the effective impact force and water hammer impact characteristics, and a real-time damping opening instruction is output; Turbulence dissipation module: controls the multi-stage flow channel based on the damping opening instruction, and performs fluid kinetic energy vortex dissipation analysis on the flow channel to obtain the energy attenuation rate. Based on the energy attenuation rate, the diaphragm deformation deviation analysis is performed to determine whether the deformation analysis signal is triggered.

[0007] As a further technical solution of the present invention: the method of performing the parameter gradient analysis is: Collect the gas channel gas pressure at N sampling points during the gas supply recovery phase and output the original gas pressure waveform; The original gas pressure waveform is pre-processed and purified to obtain a gas purification waveform; Obtain the midpoint of the rising segment of the gas purification waveform, and split the rising segment into two segments using the midpoint as the origin to obtain multiple rising sub-segments; Feature extraction is performed on each rising sub-segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak value and waveform jump coefficient of each rising sub-segment as water hammer impact characteristics.

[0008] As a further technical solution of the present invention, the method for determining whether the diaphragm has a water hammer impact risk is as follows: Obtain the impact judgment characteristics output by the diaphragm-airflow coupled dynamic model; A three-level impact criterion is constructed based on the impact judgment characteristics. If the impact judgment characteristics meet the high-risk impact criterion, it is determined that the diaphragm has a water hammer impact risk.

[0009] As a further technical solution of the present invention: the method for obtaining the impact determination feature is: Construct an airflow transient dynamics sub-model, obtain the intrinsic parameters of the gas and diaphragm, combine the water hammer impact characteristics and input them into the airflow transient dynamics sub-model to obtain the transient impact force; An energy transfer coupling interface was constructed to link the airflow transient dynamics sub-model and the diaphragm mechanical response sub-model through the energy transfer coupling interface to obtain the transient deformation stress in the central area of ​​the diaphragm. The instantaneous deformation stress of the diaphragm center area output by the diaphragm-airflow coupling dynamic model, as well as the overpressure time ratio and waveform jump coefficient are integrated as the impact judgment features.

[0010] As a further technical solution of the present invention: the method of performing the opening control process is: Extract the effective impact force that the diaphragm actually bears from the diaphragm-airflow coupled dynamic model; Determine the opening optimization target and constraint conditions of the gas self-closing valve based on the effective impact force and water hammer impact characteristics; Based on the pressure rising rate in the impact characteristic matrix, an opening control strategy is constructed to obtain the valve opening; Verification is performed based on the valve opening combined with the constraint conditions. If the valve opening meets the constraint conditions, the damping opening instruction is output.

[0011] As a further technical solution of the present invention: the method for determining whether to trigger the deformation analysis signal is: Obtain the eddy intensity coefficient and obtain the vortex dissipation coefficient of different levels of flow channels by constructing the energy dissipation equation; Calculate the total dissipation coefficient based on the vortex dissipation coefficient and energy dissipation time of different flow channels; Obtain the initial energy coefficient of water hammer, calculate the difference ratio between the initial energy coefficient and the vortex dissipation coefficient, and obtain the energy attenuation rate; A comparison analysis is performed based on the energy decay rate to determine whether to trigger the deformation analysis signal.

[0012] As a further technical solution of the present invention: the method for obtaining the eddy current intensity coefficient is: Determining the dynamic distribution ratio of the flow area of ​​the multi-stage flow channel based on the damping opening instruction, and controlling the flow state of the multi-stage flow channel based on the dynamic distribution ratio; After obtaining the flow state of the multi-stage flow channel, the pressure pulsation of each flow channel is collected and the standard deviation of the pressure pulsation is calculated; Obtain the water hammer calibration coefficient, multiply the standard deviation of the pressure pulsation of each flow channel by the water hammer calibration coefficient to obtain the vortex intensity coefficient.

[0013] As a further technical solution of the present invention: Dynamic correction module: If triggered, the diaphragm material deformation analysis is performed to obtain the diaphragm theoretical deviation, obtain the eddy current intensity of different flow channels, and perform deviation-eddy current intensity correlation analysis on the diaphragm in combination with the diaphragm theoretical deviation to locate the weak link of dissipative flow in the flow channel. A dynamic correction model is established for the weak link to adjust the distribution of flow channel flow area.

[0014] As a further technical solution of the present invention, the method for locating the weak link of the dissipative flow of the flow channel is: The eddy current intensity and diaphragm theoretical deviation of different flow channels are obtained and correlation analysis is performed to obtain the deviation-eddy current intensity correlation of each flow channel; Screening is performed based on the deviation-vortex intensity correlation of different levels of flow channels to determine the weak links in dissipation of multi-stage flow channels.

[0015] As a further technical solution of the present invention: the method for obtaining the theoretical deviation of the diaphragm is: If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the eddy dissipation coefficient is calculated to obtain the residual energy value; The deviation between diaphragm deformation and residual energy is analyzed based on Hooke's law of material mechanics to obtain the theoretical deviation of the diaphragm.

[0016] Beneficial effects of the present invention: (1) Based on the coupled dynamics theory, a diaphragm-airflow coupled dynamics model is constructed. The instantaneous impact force is calculated through the transient dynamics equation of the airflow. Then, a diaphragm mechanical response sub-model is established based on the thin plate bending theory. The two sub-models are linked through the energy transfer coupling interface, which is conducive to simulating the interaction between the diaphragm and the airflow under water hammer impact. At the same time, the diaphragm stress output by the model is combined with the overpressure time ratio and waveform jump coefficient in the impact characteristic matrix to construct a three-level impact criterion including high risk, medium risk and low risk. This is conducive to determining whether the diaphragm has the risk of water hammer impact, warning the diaphragm overload risk in advance, and protecting the diaphragm from impact damage.

[0017] (2) The optimization goal is to minimize the effective impact force of the diaphragm and the impact characteristics from the high-risk judgment criteria. At the same time, the triple constraint conditions of the opening change rate, the target opening, and the adaptive diaphragm stress state are set to achieve the safety of the opening control. The dynamic opening control method is conducive to alleviating the force of the water hammer impact on the diaphragm, and can also reduce the new airflow disturbance caused by the sudden change of the opening, thereby ensuring the smooth operation of the gas channel.

[0018] (3) The vortex dissipation coefficient of each flow channel is calculated through the energy dissipation equation, and the total value of the dissipation coefficient is obtained by summing the sum and multiplying it with the energy dissipation time. The energy attenuation rate is compared with the initial energy coefficient of the water hammer, and the dissipation effect of the water hammer energy can be monitored in real time. When the energy attenuation rate is lower than the threshold, the deformation analysis signal is triggered, which can timely detect the insufficient dissipation situation and reduce the deformation caused by the incompletely attenuated water hammer energy acting on the diaphragm. The vortex dissipation of the multi-stage flow channel further weakens the water hammer impact force, provides an additional protective barrier for the diaphragm, and improves the resistance of the self-closing valve to water hammer impact.

[0019] (4) The residual energy value is obtained by calculating the difference between the initial energy of the water hammer and the vortex dissipation energy, and the theoretical deviation of the diaphragm is obtained by combining Hooke's law of material mechanics; the weak link of dissipation is located by the deviation-vortex intensity correlation formula, and a dynamic correction model is established for different weak links, which is fed back to the multi-stage flow channel control link to adjust the flow area distribution; the targeted correction method can make up for the shortcomings of flow channel dissipation, balance the dissipation capacity of flow channels at all levels, reduce the overall dissipation failure caused by local weakness, maintain the water hammer protection effect of the self-closing valve for a long time, reduce equipment failure caused by the decline of dissipation capacity, and extend the service life of the self-closing valve. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The present invention will be further described below with reference to the accompanying drawings.

[0021] Figure 1 This is a module diagram of an intelligent gas self-closing valve with real-time operating status monitoring according to the present invention; Figure 2 This is a flow chart of the present invention for constructing a membrane-airflow coupling dynamics model; Figure 3This is a flow chart of whether the present invention is a deformation analysis signal. DETAILED DESCRIPTION

[0022] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0023] Example 1: Please refer to Figure 1 As shown, the present invention is an intelligent gas self-closing valve with real-time operating status monitoring. The intelligent gas self-closing valve includes a status monitoring system, which includes the following modules: Transient capture module: This module obtains the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising section of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs an impact feature matrix. The method for obtaining the gas pressure waveform of the gas channel during the gas supply recovery phase is as follows: Preferably, the gas pressure of the gas channel at N sampling points during the gas supply recovery phase is collected by a miniature piezoresistive pressure sensor in the intelligent gas self-closing valve, and the original gas pressure waveform is output; It should be noted that the micro piezoresistive pressure sensor monitors at a low sampling rate under normal conditions. When it detects that the pipeline pressure has risen from the gas outage state (≤0.01 bar) to the start threshold (≥0.05 bar), it is determined that the gas supply recovery phase has begun and immediately switches to 10kHz high-frequency sampling (for 500ms to cover the water hammer transient process) to record the pressure-time waveform data in real time; where N = 5000; The original gas pressure waveform is subjected to two-stage pre-processing and purification to obtain a gas purification waveform; Among them, the two-stage preprocessing method is: The first stage uses the sliding window method to perform median filtering on the original gas pressure waveform to reduce the spike noise generated by pipeline vibration; Among them, the size of the sliding window is 16 sampling points; Based on the gas pressure waveform after the first stage processing, the second stage constructs a fitting baseline by collecting steady-state data with a time length of T. The original gas pressure waveform is corrected by the fitted baseline using a linear trend line to reduce the slow baseline drift caused by temperature drift, thereby obtaining a gas purification waveform. Preferably, T=200ms; Among them, the parameter gradient analysis of the rising section of the gas pressure waveform is performed to obtain the water hammer impact characteristics as follows: Obtain the midpoint of the rising segment of the gas purification waveform, and split the rising segment into two segments using the midpoint as the origin to obtain multiple rising sub-segments; It should be explained that the rising section of the gas purification waveform is the interval from the gas pressure in the fuel gas channel being above the pressure start threshold to the first peak; Feature extraction is performed on each rising sub-segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak and waveform jump coefficient of each rising sub-segment as water hammer impact characteristics; Preferably, the method of extracting the pressure rise rate, overpressure time ratio, waveform curvature peak value and waveform jump coefficient is: Pressure rise rate: Calculate the average slope of the line connecting the starting point and the end point of the rising sub-segment as the pressure rise rate; Overpressure time ratio: Obtain the time length during which the pressure is z times higher than the preset steady-state pressure value to obtain the overpressure duration, and obtain the total time length of the rising section; perform a ratio processing on the overpressure duration and the total time length of the rising section to obtain the overpressure time ratio; Preferably, z=1.5; Waveform curvature peak value: By calculating the waveform curvature of multiple sampling points in the rising sub-segment, the waveform curvature peak value of each rising sub-segment is screened; Waveform jump coefficient: Calculate the sum of squares of the deviations between the pressure of each rising sub-segment and the fitted baseline in the two-stage preprocessing as the waveform jump coefficient; Obtain the water hammer impact characteristics of all rising sub-segments and construct an impact feature matrix including the water hammer impact characteristics; Impact prediction module: By combining coupled dynamics theory with the impact characteristic matrix, a diaphragm-airflow coupled dynamics model is constructed to obtain impact judgment characteristics and determine whether the diaphragm is at risk of water hammer impact; like Figure 2 As shown in Figure 2, the method of constructing the diaphragm-airflow coupled dynamic model is: S201. Constructing an airflow transient dynamics sub-model through an airflow transient dynamics equation, obtaining intrinsic parameters of the gas and the diaphragm, and combining the water hammer impact characteristics to input the airflow transient dynamics sub-model to obtain a transient impact force; Among them, the intrinsic parameters of gas and diaphragm include: gas density , effective force-bearing area A of the diaphragm; The diaphragm shape influence coefficient is multiplied by the gas density, the instantaneous gas flow at time t, and the change in airflow rate before and after the impact at time t to construct the transient dynamics sub-model of the airflow and obtain the instantaneous impact force of the rising sub-segment at time t. ; The diaphragm shape influence coefficient is related to the diaphragm curvature radius and thickness. For example, the flat-bottomed diaphragm takes 1.0, and the curved diaphragm takes 1.6. It should be noted that the instantaneous gas flow rate at time t is obtained in real time through a turbine flow meter, and the difference between the flow rate at time t and the steady-state flow rate before the impact is measured by a real-time flow velocity sensor to obtain the change in the airflow rate before and after the impact at time t. S202. Based on the thin plate bending theory and combined with the instantaneous impact force, a diaphragm mechanical response sub-model is constructed to obtain the instantaneous deformation stress; Obtain the fixed coefficient for circular diaphragm stress calculation, the diaphragm effective radius r, and the Poisson's ratio of the diaphragm material. Multiply the instantaneous impact force at time t of the rising sub-segment by the Poisson's ratio correction term, the square of the diaphragm effective radius r, and the fixed coefficient to obtain the stress distribution coefficient. Get the diaphragm thickness, and multiply the cube of the diaphragm thickness by pi to get the diaphragm range coefficient; The stress distribution coefficient and the diaphragm range coefficient are ratio-processed to construct the diaphragm mechanical response sub-model and obtain the instantaneous deformation stress at the effective radius r of the diaphragm and time t. It should be noted that the Poisson's ratio correction term is obtained by interpolating 1 with the square of the Poisson's ratio of the diaphragm material; Preferably, the fixed coefficient is 0.75; S203, constructing an energy transfer coupling interface, and performing linkage processing on the airflow transient dynamics sub-model and the diaphragm mechanical response sub-model through the energy transfer coupling interface to obtain the transient deformation stress of the central area of ​​the diaphragm; Preferably, the energy transfer coupling interface is constructed in the following manner: Based on the waveform curvature peak of each rising field in the impact characteristic matrix, the dynamic energy transfer coefficient corresponding to different waveform curvature peaks is defined ; It should be noted that the energy transfer coefficient reflects the impact of airflow turbulence on energy transfer efficiency. When the peak value of the waveform curvature is higher than 0.8, the airflow turbulence is judged to be severe, and the energy transfer coefficient η is set to 0.3-0.5 (turbulence dissipation leads to reduced energy transfer efficiency); When the peak value of the waveform curvature is lower than 0.8, the airflow state is determined to be stable and the energy transfer coefficient is Take 0.6-0.8; The effective impact force actually borne by the diaphragm is obtained by multiplying the energy transfer coefficient and the instantaneous impact force at time t. It should be noted that the sub-segment division of the impact characteristic matrix needs to be matched in real time during the coupling process: for the two ascending sub-segments bounded by the midpoint of the ascending segment, sub-segment 1 (the first half of the ascending segment, corresponding to the impact loading stage, the duration of the impact loading stage When the effective impact force is input into the diaphragm mechanical response sub-model, the instantaneous deformation stress in the central area of ​​the diaphragm (the effective radius of the diaphragm is less than or equal to the diaphragm radius) is calculated to realize the construction of the energy transfer coupling interface; Among them, the diaphragm radius is the inherent parameter of the diaphragm, which can be obtained from the parameter manual of the self-closing valve; Sub-segment 2 (the latter half of the ascending phase, corresponding to the shock attenuation phase, the duration of the shock attenuation phase When the effective impact force is input, the edge area of ​​the diaphragm is calculated The stress distribution ensures that the coupled model adapts to the dynamic evolution characteristics of water hammer impact; The instantaneous deformation stress of the diaphragm center area output by the diaphragm-airflow coupling dynamic model is obtained, and the overpressure time ratio and waveform jump coefficient in the impact feature matrix are integrated as the impact judgment feature; It can be understood that the role of integrating impact determination features is: Function 1: The integrated instantaneous deformation stress, overpressure time ratio, and waveform jump coefficient provide the core basis for constructing a three-level impact criterion and determining the diaphragm water hammer impact risk, reducing the limitations of single parameter judgment; Function 2: Provide key parameters for the damping control module to determine the opening optimization target, set the opening change rate and other constraints, and achieve opening adjustment to match the actual impact risk; Among them, the method of determining whether the diaphragm has the risk of water hammer impact is: A three-level impact criterion is constructed based on the impact judgment characteristics. If the impact judgment characteristics meet the high-risk impact criterion, it is determined that the diaphragm has a water hammer impact risk; Preferably, the three-level impact criterion is constructed as follows: High-risk impact criterion (there is a risk of water hammer impact): any of the following conditions are met: The instantaneous deformation stress in the central area of ​​the diaphragm is greater than or equal to 1.2σs; The overpressure time ratio is greater than or equal to 0.8 and the transient deformation stress is greater than or equal to σs; The waveform jump coefficient is greater than or equal to 5000Pa²・s (corresponding to severe pressure fluctuations) and the instantaneous deformation stress is greater than or equal to 1.1σs; Medium risk: The instantaneous deformation stress is between 0.8σs-1.2σs and the overpressure time ratio is between 0.3-0.8; Low risk: The instantaneous deformation stress is less than 0.8σs, and the waveform jump coefficient is less than 2000Pa²・s; Among them, σs is the preset yield strength, which is obtained by looking up the technical manual.

[0024] Example 2: Please refer to Figure 1 As shown, the present invention is an intelligent gas self-closing valve with real-time operating status monitoring. The intelligent gas self-closing valve includes a status monitoring system, and the status monitoring system also includes the following modules: Damping control module: If there is a risk of water hammer impact, the effective impact force of the diaphragm-airflow coupling dynamic model is extracted, the opening control processing is performed based on the effective impact force and water hammer impact characteristics, and a real-time damping opening instruction is output; Among them, the method of opening control based on effective impact force and water hammer impact characteristics is: Extract the effective impact force that the diaphragm actually bears from the diaphragm-airflow coupled dynamic model; S301. Determine an opening optimization target and constraint conditions of the gas self-closing valve based on the effective impact force and water hammer impact characteristics; Among them, the goal of opening optimization is to minimize the effective impact force actually borne by the diaphragm and to ensure that the impact judgment characteristics no longer meet the high-risk impact criterion; Preferably, the constraints include: Constraint 1: The opening change rate is lower than or equal to the preset maximum opening change rate. The overpressure time ratio is dynamically determined based on the impact characteristic matrix. When the overpressure time ratio is higher than 0.8, 3% / ms; When the overpressure time ratio is less than 0.8, the maximum opening change rate is 5% / ms to prevent sudden changes in the opening from causing sudden changes in airflow velocity and triggering new pressure shocks. Constraint 2: The target opening is greater than or equal to 40% (based on the effective force-bearing area A of the diaphragm and the gas density: when the target opening is less than 40%, the flow channel area is too small, which can easily lead to a sudden increase in local pressure, and the compatibility with the three-stage flow channel structure of the turbulence dissipation module is reduced); Constraint three: The opening adjustment must adapt to the current diaphragm stress state. If the effective impact force of the impact loading phase (duration t1 = 20-150ms) in sub-segment 1 (impact loading phase) is greater than or equal to Q times the maximum force allowed by the diaphragm, the initial opening adjustment rate is preferentially reduced. The preferred Q=1.2; Preferably, the maximum force allowed by the diaphragm is set by those skilled in the art based on experience; If the effective impact force in sub-section 2 (impact attenuation stage) is higher than or equal to the maximum force allowed by the diaphragm, the maintenance accuracy after the opening is stabilized should be appropriately improved; S302, constructing an opening control strategy to obtain the valve opening based on the pressure rise rate in the impact characteristic matrix; Preferably, if the pressure rise rate is greater than or equal to 0.5 bar / ms (severe impact scenario), an exponential slow-change adjustment logic is used: combining the current actual valve opening, the target safe opening determined by the effective impact force, and an adjustment coefficient for regulating the rhythm of the opening change (for example, the adjustment coefficient is 0.1-0.3, with a smaller value for more severe impacts). The valve opening is allowed to slowly transition from the current value to the target safe opening, thereby obtaining an adapted valve opening (avoiding instability caused by sudden changes in opening). If the pressure rise rate is lower than 0.5 bar / ms (relatively stable shock scenario), a piecewise linear adjustment logic is used: first, a segmented time node is calculated based on the current actual valve opening, the target safe opening, and the maximum opening change rate determined by the overpressure time ratio. Before this time node, the valve opening is linearly increased at the set maximum speed. After the time exceeds this node, the valve opening is directly adjusted to the target safe opening. S303, verifying based on the valve opening and the constraint conditions, and outputting a damping opening instruction if the valve opening meets the constraint conditions; Preferably, the valve opening outputted by the opening control strategy is verified one by one against the constraints to determine whether the valve opening meets each constraint; If the valve opening meets the constraint conditions, the damping opening instruction is output to control the valve opening; It is understandable that the purpose of outputting the damping opening instruction is: Purpose 1: By dynamically adjusting the valve opening, the effective impact force actually borne by the diaphragm is minimized, and the diaphragm is reduced from deformation, cracking and other damage caused by water hammer impact exceeding the safe force range, thereby directly protecting the structural integrity of the diaphragm; Purpose 2: To provide a control basis for the turbulence dissipation module, and to regulate the flow state of the multi-stage flow channel by outputting real-time opening instructions, thereby laying the foundation for the subsequent analysis of the kinetic energy vortex dissipation of the flow channel fluid and assisting in reducing the impact energy of water hammer.

[0025] Turbulence dissipation module: controls the multi-stage flow channel based on the damping opening instruction, and performs fluid kinetic energy vortex dissipation analysis on the flow channel to obtain the energy attenuation rate. Based on the energy attenuation rate, the diaphragm deformation deviation is analyzed to determine whether the deformation analysis signal is triggered; Determining the dynamic distribution ratio of the flow area of ​​the multi-stage flow channel based on the damping opening instruction, and controlling the flow state of the multi-stage flow channel based on the dynamic distribution ratio; After obtaining the flow state of the multi-stage flow channel, N1 sampling points are set to collect the pressure pulsation of each flow channel at N1 sampling points and calculate the standard deviation of the pressure pulsation; Obtain the water hammer calibration coefficient, multiply the standard deviation of the pressure pulsation of each flow channel by the water hammer calibration coefficient to obtain the vortex intensity coefficient; It should be noted that the water hammer calibration coefficient is calibrated by those skilled in the art through DN15 / DN20 pipeline experiments; Based on the eddy current intensity coefficient, vortex dissipation analysis is performed to obtain the vortex dissipation coefficient of each stage of flow channel; Among them, the method of performing vortex dissipation analysis is: Obtain the dissipation proportional coefficient and the average airflow velocity, and multiply the cube of the average airflow velocity, the dynamic flow area of ​​each stage of the flow channel, the dissipation proportional coefficient, and the square of the eddy intensity coefficient of each stage of the flow channel to obtain the vortex dissipation coefficient of each stage; Preferably, the dissipation proportional coefficient is 0.5 times the gas density; Obtain the energy dissipation time, sum the vortex dissipation power of all stage flow passages, and multiply the summation result by the energy dissipation time to obtain the total dissipation coefficient; Obtain the pipe cross-sectional area, maximum air velocity, and overpressure duration, and multiply the dissipation proportional coefficient by the pipe cross-sectional area, the cube of the maximum air velocity, and overpressure duration to obtain the water hammer initial energy coefficient; Calculate the difference between the initial energy coefficient and the eddy dissipation coefficient to obtain the energy attenuation rate; like Figure 3 As shown, the energy decay rate is compared with a preset energy decay threshold (for example, the energy decay threshold is set to 0.8, that is, deformation analysis is triggered when the decay rate is ≤ 0.8). If the energy decay rate is lower than or equal to the preset energy decay rate threshold, the deformation analysis signal is triggered; If the energy decay rate is higher than a preset energy decay threshold, the change of the energy decay rate continues; It is understandable that the function of determining the triggering signal for deformation analysis is: Function 1: Timely identify the situation of insufficient water hammer energy dissipation, provide trigger signals for subsequent diaphragm material deformation analysis, reduce the overload deformation or damage of the diaphragm caused by incompletely attenuated water hammer energy, and warn of diaphragm safety risks; Function 2: Provide a starting basis for the dynamic correction module, guide the module to locate the weak link of flow channel dissipation through the trigger signal, and then adjust the flow area distribution of the flow channel to optimize the water hammer energy dissipation capacity of the multi-stage flow channel.

[0026] Dynamic correction module: If triggered, the diaphragm material deformation analysis is performed to obtain the diaphragm theoretical deviation, obtain the eddy current intensity of different flow channels, and perform a deviation-eddy current intensity correlation analysis on the diaphragm in combination with the diaphragm theoretical deviation to locate the weak link of dissipative flow in the flow channel. A dynamic correction model is established for the weak link to adjust the distribution of flow channel flow area; Among them, the method of performing material deformation analysis on the diaphragm is: If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the eddy dissipation coefficient is calculated to obtain the residual energy value; Based on Hooke's law of material mechanics, the deviation between diaphragm deformation and residual energy is analyzed to obtain the theoretical deviation of the diaphragm; Those skilled in the art will understand that the residual energy is calculated (the initial energy of the water hammer minus the sum of the vortex dissipation coefficients of each flow channel). Then, based on Hooke's law in material mechanics (stress is proportional to strain, i.e., stress is the elastic modulus of the diaphragm multiplied by the strain), the residual energy is converted into the stress borne by the diaphragm, combining the geometric parameters (effective radius, thickness) and material parameters (such as Poisson's ratio) of the diaphragm. The strain is then derived from the correlation between stress and strain. Finally, based on the geometric law of thin plate deformation (corresponding the strain to the diaphragm deformation and the theoretical deviation), a quantitative relationship between the residual energy and the theoretical deviation of the diaphragm is established, and the theoretical deviation of the diaphragm is then calculated: The method for obtaining the eddy current intensity of different flow channels and performing a deviation-eddy current intensity correlation analysis on the diaphragm in combination with the diaphragm theoretical deviation is as follows: Based on the theoretical deviation of the diaphragm, the dissipation shortcomings of the core flow channel are located, and a dynamic correction model of theoretical deviation-flow channel ratio is established for the dissipation weak link; Among them, the method of locating the dissipation weak link of the core flow channel based on the diaphragm theory deviation is: Based on the correlation analysis between the vortex intensity and the theoretical deviation of the diaphragm at different flow channels, the deviation-vortex intensity correlation of each flow channel is obtained; The method of performing the correlation analysis is as follows: obtaining the vortex intensity of each level of flow channel and the corresponding dynamic flow area of ​​the flow channel; Calculate the product of the vortex intensity of each flow channel and the dynamic flow area of ​​the corresponding flow channel to obtain the single-stage diffusion coefficient; Obtaining a preset safety value of the diaphragm theoretical deviation, performing ratio processing on the diaphragm theoretical deviation and the safety value of the diaphragm theoretical deviation to obtain a safety factor; Calculate the sum of the single-stage diffusion coefficients of all flow channels, multiply the single-stage diffusion coefficient and the safety factor, and then compare the product with the sum of the single-stage diffusion coefficients of all flow channels to obtain the deviation-eddy current intensity correlation of each flow channel. Based on the correlation between the deviation and eddy current intensity of different flow channels, screening is performed to determine the weak links of dissipation in multi-stage flow channels; It can be understood that the method for determining the weak link in dissipation of a multi-stage flow channel is: if the correlation between the deviation and vortex intensity of the third-stage flow channel is higher than 0.5 (the third-stage flow channel has the highest correlation), it means that the vortex intensity of the third-stage flow channel (the core dissipation link) is insufficient and is the main cause of the deviation. Therefore, it is necessary to match the vortex dissipation capacity and deviation of the third-stage flow channel. That is, the weak link in dissipation is the third-stage flow channel. If the sum of the deviation-vortex intensity correlation of the 1st and 2nd stage flow channels is higher than 0.6, it indicates that the 1st and 2nd stage flow channels are not pre-treated enough, resulting in excessive energy transfer to the 3rd stage, which indirectly causes deviation. In this case, the vortex dissipation capacity of the 1st and 2nd stage flow channels needs to be matched with the deviation, and the weak link in dissipation is the 1st and 2nd stage flow channels. Among them, the method of establishing a dynamic correction model of theoretical deviation-flow channel ratio for the dissipation weak link is: If the weak link in dissipation is a level 3 flow channel, obtain the flow channel correction coefficient and turbulence coefficient of the level 3 flow channel, and multiply the flow channel correction coefficient with the turbulence coefficient and the safety factor to obtain the correction amount of the level 3 flow channel; Preferably, the flow channel correction coefficient of the 3-stage flow channel is 0.8; If the weak link in dissipation is the 1st and 2nd level flow passages, when calculating the correction amount for the 1st level flow passage, multiply the safety factor (the ratio of the diaphragm theoretical deviation to the diaphragm theoretical deviation safety value) by the turbulence coefficient of the 1st level flow passage, and then multiply the product by (-0.08). The final result is the correction amount for the 1st level flow passage. When calculating the correction amount for the secondary flow channel, multiply the safety factor (the ratio of the diaphragm theoretical deviation to the diaphragm theoretical deviation safety value) by the turbulence coefficient of the secondary flow channel, and then multiply the product by 0.08. The final result is the correction amount for the secondary flow channel. The turbulence coefficient of the flow channel is set by those skilled in the art. The coefficient of 0.08 is an empirically adapted value verified through numerous experiments and simulations. This allows the correction amount to effectively adjust the flow characteristics of the flow channel under the influence of the safety factor (the ratio of the diaphragm theoretical deviation to the safety value) and the flow channel turbulence coefficient, without causing system instability due to excessive correction amplitude. The correction amount for the first-stage flow channel is negative, and the correction amount for the second-stage flow channel is positive. This is to ensure that the correction amounts for the first and second-stage flow channels form a complementary control logic. This is to make the flow characteristics (such as flow capacity) of the first-stage flow channel inversely adapted to the second-stage flow channel (for example, the first stage is appropriately narrowed and the second stage is appropriately widened), thereby optimizing the overall energy dissipation distribution of the multi-stage flow channel and dynamically correcting weak links in dissipation. It should be noted that the establishment of a dynamic correction model of theoretical deviation-flow channel ratio is achieved based on the process of obtaining the correction amount of the 3-level flow channel and the process of obtaining the correction amount of the 1- and 2-level flow channels; The correction amount obtained based on the dynamic correction model is fed back to the multi-stage flow channel control link to correct the dynamic distribution ratio of the flow area of ​​the flow channel; Those skilled in the art will appreciate that the correction is performed as follows: the dynamic correction model first calculates the flow area correction for each level of flow channels based on the degree of deviation between the vortex intensity coefficient of the core flow channel and the optimal interval, combined with real-time data such as diaphragm deformation and water hammer energy dissipation; these corrections are then fed back to the actuators of the multi-stage flow channels (such as electric control valves) in the form of control instructions, and the actuators adjust their own openings according to the corrections, increasing the flow area ratio of the flow channels with insufficient dissipation to enhance vortex dissipation, and reducing the flow area ratio of the flow channels with excessive dissipation to balance the dissipation level; at the same time, through real-time closed-loop monitoring, continuous iterative corrections are performed until the dynamic distribution ratio of the flow area of ​​the multi-stage flow channels is adapted to the current operating conditions, thereby ensuring that the vortex dissipation capacity of the core flow channels is stable within the preset optimal interval.

[0027] The above is a detailed description of an embodiment of the present invention. However, the content is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. An intelligent gas self-closing valve with real-time operating status monitoring, characterized by: The intelligent gas self-closing valve includes a state monitoring system, which includes the following modules: Transient capture module: This module obtains the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising section of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs an impact feature matrix. Impact prediction module: By combining coupled dynamics theory with the impact characteristic matrix, a diaphragm-airflow coupled dynamics model is constructed to obtain impact judgment characteristics and determine whether the diaphragm is at risk of water hammer impact; Damping control module: If there is a risk of water hammer impact, the effective impact force of the diaphragm-airflow coupling dynamic model is extracted, the opening control processing is performed based on the effective impact force and water hammer impact characteristics, and a real-time damping opening instruction is output; Turbulence dissipation module: controls the multi-stage flow channel based on the damping opening instruction, and performs fluid kinetic energy vortex dissipation analysis on the flow channel to obtain the energy attenuation rate. Based on the energy attenuation rate, the diaphragm deformation deviation analysis is performed to determine whether the deformation analysis signal is triggered.

2. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized by: The method for performing the parameter gradient analysis is: Collect the gas channel gas pressure at N sampling points during the gas supply recovery phase and output the original gas pressure waveform; The original gas pressure waveform is pre-processed and purified to obtain a gas purification waveform; Obtain the midpoint of the rising segment of the gas purification waveform, and split the rising segment into two segments using the midpoint as the origin to obtain multiple rising sub-segments; Feature extraction is performed on each rising sub-segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak value and waveform jump coefficient of each rising sub-segment as water hammer impact characteristics.

3. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized by: The method for determining whether the diaphragm has a water hammer risk is: Obtain the impact judgment characteristics output by the diaphragm-airflow coupled dynamic model; A three-level impact criterion is constructed based on the impact judgment characteristics. If the impact judgment characteristics meet the high-risk impact criterion, it is determined that the diaphragm has a water hammer impact risk.

4. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 3 is characterized by: The method for obtaining the impact judgment feature is: Construct an airflow transient dynamics sub-model, obtain the intrinsic parameters of the gas and diaphragm, combine the water hammer impact characteristics and input them into the airflow transient dynamics sub-model to obtain the transient impact force; An energy transfer coupling interface was constructed to link the airflow transient dynamics sub-model and the diaphragm mechanical response sub-model through the energy transfer coupling interface to obtain the transient deformation stress in the central area of ​​the diaphragm. The instantaneous deformation stress of the diaphragm center area output by the diaphragm-airflow coupling dynamic model, as well as the overpressure time ratio and waveform jump coefficient are integrated as the impact judgment features.

5. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized in that: The method for performing the opening control process is: Extract the effective impact force that the diaphragm actually bears from the diaphragm-airflow coupled dynamic model; Determine the opening optimization target and constraint conditions of the gas self-closing valve based on the effective impact force and water hammer impact characteristics; Based on the pressure rising rate in the impact characteristic matrix, an opening control strategy is constructed to obtain the valve opening; Verification is performed based on the valve opening combined with the constraint conditions. If the valve opening meets the constraint conditions, the damping opening instruction is output.

6. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized by: The method for determining whether to trigger the deformation analysis signal is as follows: Obtain the eddy intensity coefficient and obtain the vortex dissipation coefficient of different levels of flow channels by constructing the energy dissipation equation; Calculate the total dissipation coefficient based on the vortex dissipation coefficient and energy dissipation time of different flow channels; Obtain the initial energy coefficient of water hammer, calculate the difference ratio between the initial energy coefficient and the vortex dissipation coefficient, and obtain the energy attenuation rate; A comparison analysis is performed based on the energy decay rate to determine whether to trigger the deformation analysis signal.

7. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 6 is characterized by: The method for obtaining the eddy current intensity coefficient is: Determining the dynamic distribution ratio of the flow area of ​​the multi-stage flow channel based on the damping opening instruction, and controlling the flow state of the multi-stage flow channel based on the dynamic distribution ratio; After obtaining the flow state of the multi-stage flow channel, the pressure pulsation of each flow channel is collected and the standard deviation of the pressure pulsation is calculated; Obtain the water hammer calibration coefficient, multiply the standard deviation of the pressure pulsation of each flow channel by the water hammer calibration coefficient to obtain the vortex intensity coefficient.

8. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized by: Also includes the following modules: Dynamic correction module: If triggered, the diaphragm material deformation analysis is performed to obtain the diaphragm theoretical deviation, obtain the eddy current intensity of different flow channels, and perform deviation-eddy current intensity correlation analysis on the diaphragm in combination with the diaphragm theoretical deviation to locate the weak link of dissipative flow in the flow channel. A dynamic correction model is established for the weak link to adjust the distribution of flow channel flow area.

9. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 1 is characterized in that: The way to locate the weak link of dissipative flow in the flow channel is: The eddy current intensity and diaphragm theoretical deviation of different flow channels are obtained and correlation analysis is performed to obtain the deviation-eddy current intensity correlation of each flow channel; Screening is performed based on the deviation-vortex intensity correlation of different levels of flow channels to determine the weak links in dissipation of multi-stage flow channels.

10. The intelligent gas self-closing valve with real-time operation status monitoring according to claim 9, characterized in that: The method to obtain the theoretical deviation of the diaphragm is: If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the eddy dissipation coefficient is calculated to obtain the residual energy value; The deviation between diaphragm deformation and residual energy is analyzed based on Hooke's law of material mechanics to obtain the theoretical deviation of the diaphragm.

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