A smart gas self-closing valve with real-time operation status monitoring

Abstract

This invention relates to the field of gas safety control technology, specifically disclosing an intelligent gas self-closing valve for real-time operational status monitoring. The intelligent gas self-closing valve includes a status monitoring system. The system comprises: acquiring the gas pressure waveform of the gas channel during the gas supply recovery phase; performing parameter gradient analysis on the rising segment of the gas pressure waveform to establish an impact characteristic matrix; constructing a diaphragm-airflow coupled dynamic model to determine if the diaphragm has a risk of water hammer impact; if so, extracting the minimum effective impact force of the diaphragm and outputting a real-time damping opening command; controlling multi-stage flow channels based on the damping opening command, and performing fluid kinetic energy vortex dissipation analysis on the flow channels to determine if a deformation analysis signal is triggered; if triggered, performing material deformation analysis on the diaphragm to obtain the theoretical deviation of the diaphragm, locating the weak points in the dissipation flow of the flow channels, and establishing a dynamic correction model for the weak points to adjust the distribution of the flow channel's flow area.

Description

Technical Field

[0001] This invention relates to the field of gas safety control technology, specifically to an intelligent gas self-closing valve with real-time operating status monitoring. Background Technology

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

[0003] In practical use, during the gas supply restoration phase after a gas outage for maintenance or equipment restart, the pipeline pressure rises rapidly from the outage state. When gas fills the pipeline at high speed, it easily creates a water hammer effect. This generates transient high-pressure impacts that directly act on the diaphragm of the self-closing valve. Since the diaphragm has a defined yield strength limit, the instantaneous force of the water hammer impact often exceeds the safe range, leading to diaphragm deformation, cracking, or fatigue damage. This, in turn, causes the self-closing valve to fail, creating a potential gas leak hazard.

[0004] Therefore, the present invention provides an intelligent gas self-closing valve for real-time operation status monitoring. Summary of the Invention

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

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] A smart gas self-closing valve with real-time operating status monitoring, the smart gas self-closing valve includes a status monitoring system, the status monitoring system including the following modules:

[0008] Transient capture module: acquires the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising segment of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs the impact characteristic matrix.

[0009] Impact prediction module: Constructs a diaphragm-airflow coupled dynamics model by combining coupled dynamics theory with impact feature matrix, obtains impact judgment characteristics, and determines whether the diaphragm is at risk of water hammer impact;

[0010] 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, and the opening is controlled based on the effective impact force and water hammer impact characteristics, and the real-time damping opening command is output.

[0011] Turbulent dissipation module: Controls multi-stage flow channels based on damping opening commands, performs fluid kinetic energy vortex dissipation analysis on the flow channels to obtain energy decay rate, performs diaphragm deformation deviation analysis based on energy decay rate, and determines whether to trigger deformation analysis signal.

[0012] As a further technical solution of the present invention, the method for performing the parameter gradient parsing is as follows:

[0013] Collect the gas pressure of the gas channel at N sampling points during the gas supply recovery phase and output the original gas pressure waveform;

[0014] The original gas pressure waveform is preprocessed and purified to obtain the purified gas waveform.

[0015] Obtain the midpoint of the rising segment of the gas purification waveform, and divide the rising segment into two parts using the midpoint as the origin to obtain multiple rising sub-segments.

[0016] Feature extraction is performed on each rising segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak value, and waveform jump coefficient of each rising segment as water hammer impact characteristics.

[0017] As a further technical solution of the present invention: the method for determining whether the diaphragm has a risk of water hammer impact is as follows:

[0018] Obtain the impact determination characteristics output by the diaphragm-airflow coupling dynamics model;

[0019] A three-level impact criterion is constructed based on the impact judgment characteristics. If the impact judgment characteristics meet the high-risk impact criterion, the diaphragm is determined to be at risk of water hammer impact.

[0020] As a further technical solution of the present invention, the method for obtaining the impact determination features is as follows:

[0021] A transient dynamics sub-model of airflow is constructed, and the intrinsic parameters of the gas and diaphragm are obtained. Combined with the water hammer impact characteristics, the transient dynamics sub-model of airflow is input to obtain the instantaneous impact force.

[0022] An energy transfer coupling interface is constructed, and the transient dynamics sub-model of airflow and the mechanical response sub-model of diaphragm are processed in conjunction through the energy transfer coupling interface to obtain the instantaneous deformation stress in the central region of the diaphragm.

[0023] The instantaneous deformation stress in the central region of the diaphragm, as well as the overpressure time ratio and waveform jump coefficient, output from the diaphragm-airflow coupling dynamic model are integrated and used as impact judgment features.

[0024] As a further technical solution of the present invention, the method for performing the opening control process is as follows:

[0025] Minimize the effective impact force actually borne by the diaphragm in the diaphragm-airflow coupling dynamics model;

[0026] The opening optimization target and constraints of the gas self-closing valve are determined based on the effective impact force and water hammer impact characteristics.

[0027] Based on the pressure rise rate in the impact feature matrix, an opening control strategy is constructed to obtain the valve opening.

[0028] The verification is based on the valve opening degree combined with the constraint conditions. If the valve opening degree meets the constraint conditions, the damping opening degree command is output.

[0029] As a further technical solution of the present invention: the method for determining whether a deformation analysis signal is triggered is as follows:

[0030] The eddy intensity coefficient is obtained, and the vortex dissipation coefficient of different flow stages is obtained by constructing an energy dissipation equation.

[0031] The total dissipation coefficient is calculated based on the vortex dissipation coefficient and energy dissipation time of different flow channels.

[0032] Obtain the initial energy coefficient of the water hammer, calculate the percentage difference between the initial energy coefficient and the vortex dissipation coefficient, and obtain the energy decay rate.

[0033] Comparative analysis based on energy decay rate is used to determine whether a deformation analysis signal is triggered.

[0034] As a further technical solution of the present invention: the method for obtaining the eddy current intensity coefficient is as follows:

[0035] The dynamic allocation ratio of the flow area of ​​the multi-stage flow channel is determined based on the damping opening command, and the flow state of the multi-stage flow channel is controlled based on the dynamic allocation ratio.

[0036] After obtaining the flow state of the multi-stage flow channels, the pressure pulsation of each flow channel is collected and the standard deviation of the pressure pulsation is calculated.

[0037] Obtain the water hammer calibration coefficient, and multiply the standard deviation of the pressure pulsation in each flow channel with the water hammer calibration coefficient to obtain the eddy current intensity coefficient.

[0038] As a further technical solution of the present invention:

[0039] Dynamic correction module: If triggered, it performs material deformation analysis on the diaphragm to obtain the theoretical deviation of the diaphragm, obtains the eddy current intensity of different flow channels, and performs deviation-eddy current intensity correlation analysis on the diaphragm in combination with the theoretical deviation of the diaphragm to locate the weak link of dissipation flow in the flow channel. It then establishes a dynamic correction model for the weak link of dissipation flow to adjust the distribution of the flow channel area.

[0040] As a further technical solution of the present invention: the method for locating the weak link of the dissipative flow in the flow channel is as follows:

[0041] The eddy current intensity and diaphragm theoretical deviation of different flow channels were obtained and correlation analysis was performed to obtain the correlation degree between deviation and eddy current intensity for each flow channel.

[0042] Screening was performed based on the correlation between deviation and eddy current intensity in different flow channels to identify the weak points in the dissipation of multi-stage flow channels.

[0043] As a further technical solution of the present invention, the method for obtaining the theoretical deviation of the membrane is as follows:

[0044] If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the vortex dissipation coefficient is calculated to obtain the residual energy value.

[0045] Based on Hooke's law in mechanics of materials, a deviation analysis of diaphragm deformation and residual energy is conducted to obtain the theoretical deviation of the diaphragm.

[0046] The beneficial effects of this invention are:

[0047] (1) Based on the coupled dynamics theory, a diaphragm-airflow coupled dynamics model is constructed. The instantaneous impact force is calculated by the transient dynamics equation of 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 beneficial to simulate the interaction between the diaphragm and the airflow under water hammer impact. At the same time, combined with the diaphragm stress output by the model and the overpressure time ratio and waveform jump coefficient in the impact characteristic matrix, a three-level impact criterion including high risk, medium risk and low risk is constructed. This is beneficial to determine whether the diaphragm is at risk of water hammer impact, to provide early warning of diaphragm overload risk, and to protect the diaphragm from impact damage.

[0048] (2) The optimization goal is to minimize the effective impact force of the diaphragm and the impact characteristics deviate from the high-risk criterion. At the same time, the triple constraint conditions of opening change rate, target opening and the force state of the diaphragm are set to achieve the safety of opening control. The dynamic opening control method is conducive to alleviating the force of water hammer impact on the diaphragm and reducing the new airflow disturbance caused by sudden opening changes, thus ensuring the stability of the gas channel operation.

[0049] (3) The vortex dissipation coefficient of each flow channel is calculated by the energy dissipation equation. The sum is multiplied by the energy dissipation time to obtain the total value of the dissipation coefficient. The energy decay rate is obtained by comparing the initial energy coefficient of the water hammer. The dissipation effect of the water hammer energy can be monitored in real time. When the energy decay rate is lower than the threshold, the deformation analysis signal is triggered. The insufficient dissipation can be detected in time, and the water hammer energy that is not completely decayed can be reduced to act on the diaphragm and cause deformation. 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 self-closing valve's resistance to water hammer impact.

[0050] (4) The residual energy is obtained by calculating the difference between the initial energy of water hammer and the energy dissipated by vortex. The theoretical deviation of the diaphragm is obtained by combining Hooke's law in mechanics of materials. Then, 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. The feedback is sent to the multi-level flow channel control link to adjust the flow area distribution. The targeted correction method can make up for the dissipation shortcomings of the flow channel, balance the dissipation capacity of each level of the flow channel, 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 in dissipation capacity, and extend the service life of the self-closing valve. Attached Figure Description

[0051] The invention will now be further described with reference to the accompanying drawings.

[0052] Figure 1 This is a block diagram of an intelligent gas self-closing valve for real-time operation status monitoring according to the present invention;

[0053] Figure 2 This is a flowchart of the diaphragm-airflow coupling dynamics model constructed according to the present invention;

[0054] Figure 3 This is a flowchart of whether the deformation analysis signal is present in this invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] 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:

[0057] Transient capture module: acquires the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising segment of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs the impact characteristic matrix.

[0058] The method for obtaining the gas pressure waveform of the gas supply channel during the gas supply recovery phase is as follows:

[0059] Preferably, the gas pressure in 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.

[0060] It should be noted that the miniature piezoresistive pressure sensor normally monitors at a low sampling rate. When it detects that the pipeline pressure has risen from the gas outage state (≤0.01 bar) to the start-up threshold (≥0.05 bar), it determines that it has entered the gas supply recovery stage and immediately switches to 10kHz high-frequency sampling (lasting 500ms, covering the water hammer transient process) to record pressure-time waveform data in real time; where N=5000.

[0061] The original gas pressure waveform is pre-processed and purified in two stages to obtain the purified gas waveform.

[0062] The two-stage preprocessing method is as follows:

[0063] The first stage uses a sliding window method to perform median filtering on the original gas pressure waveform to reduce spike noise generated by pipeline vibration.

[0064] The sliding window has a size of 16 sampling points;

[0065] Based on the gas pressure waveform after the first stage of processing, a fitting baseline is constructed by collecting steady-state data for a time period of T in the second stage. The original gas pressure waveform is then corrected by a linear trend line on the fitting baseline to reduce the slow baseline drift caused by temperature drift, thus obtaining the gas purification waveform.

[0066] Preferably, T=200ms;

[0067] The method for obtaining the water hammer impact characteristics by performing parameter gradient analysis on the rising segment of the gas pressure waveform is as follows:

[0068] Obtain the midpoint of the rising segment of the gas purification waveform, and divide the rising segment into two parts using the midpoint as the origin to obtain multiple rising sub-segments.

[0069] It should be explained that the rising segment of the gas purification waveform is the range from when the gas pressure in the gas channel rises above the pressure start-up threshold to the first peak value.

[0070] Feature extraction is performed on each rising segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak value and waveform jump coefficient of each rising segment as water hammer impact characteristics.

[0071] Preferably, the method for extracting the pressure rise rate, overpressure time ratio, waveform curvature peak value, and waveform jump coefficient is as follows:

[0072] Pressure rise rate: The average slope of the line connecting the start and end points of the rising segment is used as the pressure rise rate.

[0073] Overpressure time ratio: Obtain the time length during which the pressure is higher than the preset steady-state pressure value by z times to obtain the overpressure duration, and obtain the total time length of the rising segment; then, calculate the ratio between the overpressure duration and the total time length of the rising segment to obtain the overpressure time ratio;

[0074] Preferably, z=1.5;

[0075] Waveform curvature peak: Calculate the waveform curvature of multiple sampling points within the rising segment and filter the waveform curvature peak of each rising segment;

[0076] Waveform jump coefficient: The sum of squares of the deviations between the pressure of each rising segment and the fitted baseline in the two-stage preprocessing is calculated as the waveform jump coefficient.

[0077] Obtain the water hammer impact characteristics of all rising segments and construct an impact feature matrix containing the water hammer impact characteristics;

[0078] Impact prediction module: Constructs a diaphragm-airflow coupled dynamics model by combining coupled dynamics theory with impact feature matrix, obtains impact judgment characteristics, and determines whether the diaphragm is at risk of water hammer impact;

[0079] like Figure 2 As shown, the method for constructing the diaphragm-airflow coupled dynamic model is as follows:

[0080] S201. Construct a transient dynamics sub-model of airflow through the transient dynamics equation of airflow, obtain the intrinsic parameters of the gas and diaphragm, and input the water hammer impact characteristics into the transient dynamics sub-model of airflow to obtain the instantaneous impact force;

[0081] The intrinsic parameters of the gas and the diaphragm include: gas density. The effective force-bearing area A of the diaphragm;

[0082] The transient dynamics sub-model of the airflow is constructed by multiplying the diaphragm shape influence coefficient with the gas density, the instantaneous gas flow rate at time t, and the change in airflow velocity before and after the impact at time t, thus obtaining the instantaneous impact force at time t of the rising segment. ;

[0083] Among them, the diaphragm shape influence coefficient is related to the diaphragm curvature radius and thickness. For example, it is 1.0 for flat-bottomed diaphragms and 1.6 for curved diaphragms.

[0084] It should be noted that the instantaneous flow rate of the gas at time t is obtained in real time by means of a turbine flow meter, and the difference between the flow velocity at time t measured by the real-time flow velocity sensor and the steady-state flow velocity before the impact is used to obtain the change in airflow rate before and after the impact at time t.

[0085] 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.

[0086] Obtain the fixed coefficient, effective radius r of the diaphragm, and Poisson's ratio of the diaphragm material for stress calculation of the circular diaphragm. Multiply the instantaneous impact force at time t of the rising segment with the Poisson's ratio correction term, the square of the effective radius r of the diaphragm, and the fixed coefficient to obtain the stress distribution coefficient.

[0087] The membrane thickness is obtained, and the cube of the membrane thickness is multiplied by pi to obtain the membrane range coefficient.

[0088] By comparing the stress distribution coefficient and the diaphragm range coefficient, a sub-model of the diaphragm's mechanical response is constructed, yielding the instantaneous deformation stress at time t at an effective radius r of the diaphragm.

[0089] 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.

[0090] Preferably, the fixed coefficient is 0.75;

[0091] S203. Construct an energy transfer coupling interface to link the airflow transient dynamics sub-model and the diaphragm mechanical response sub-model through the energy transfer coupling interface to obtain the instantaneous deformation stress in the central region of the diaphragm.

[0092] Preferably, the method for constructing the energy transfer coupling interface is as follows:

[0093] Based on the peak waveform curvature of each rising field in the impact characteristic matrix, dynamic energy transfer coefficients corresponding to different peak waveform curvature are defined. ;

[0094] It should be noted that the energy transfer coefficient reflects the influence of the degree of airflow turbulence on the energy transfer efficiency. When the peak value of the waveform curvature is higher than 0.8, it is determined that the airflow turbulence is severe, and the energy transfer coefficient η is taken as 0.3-0.5 (turbulent dissipation leads to a decrease in energy transfer efficiency).

[0095] When the peak value of the waveform curvature is below 0.8, the airflow is considered stable, and the energy transfer coefficient is [value missing]. Take a value of 0.6-0.8;

[0096] The effective impact force actually borne by the diaphragm is obtained by multiplying the energy transfer coefficient by the instantaneous impact force at time t.

[0097] It should be noted that during the coupling process, the segment division of the impact feature matrix needs to be matched in real time: for the two rising segments bounded by the midpoint of the rising segment, segment 1 (the first half of the rising 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 focus is on calculating the instantaneous deformation stress in the central region of the diaphragm (the effective radius of the diaphragm is less than or equal to the radius of the diaphragm) to realize the construction of the energy transfer coupling interface;

[0098] The diaphragm radius is an inherent parameter of the diaphragm, which is obtained from the parameter manual of the self-closing valve.

[0099] Sub-segment 2 (the latter half of the rising phase, corresponding to the impact decay phase, duration of the impact decay phase) When applying an effective impact force, the focus should be on calculating the diaphragm edge area. The stress distribution ensures that the coupled model adapts to the dynamic evolution characteristics of water hammer impact;

[0100] The instantaneous deformation stress in the central region of the diaphragm, obtained from the output of the diaphragm-airflow coupling dynamic model, and the overpressure time ratio and waveform jump coefficient in the impact characteristic matrix are integrated as impact judgment features.

[0101] It is understandable that the function of integrating impact determination features is:

[0102] Function 1: The integrated instantaneous deformation stress, overpressure time ratio, and waveform jump coefficient provide a core basis for constructing a three-level impact criterion and determining the risk of diaphragm water hammer impact, reducing the limitations of single-parameter judgment;

[0103] Function 2: Provides key parameters for the damping control module to determine the opening optimization target and set constraints such as the opening change rate, so as to match the opening adjustment with the actual impact risk;

[0104] The method for determining whether a diaphragm is at risk of water hammer impact is as follows:

[0105] A three-level impact criterion is constructed based on the impact judgment characteristics. If the impact judgment characteristics meet the high-risk impact criterion, the diaphragm is determined to be at risk of water hammer impact.

[0106] Preferably, the method for constructing the three-level impact criterion is as follows:

[0107] High-risk impact criterion (risk of water hammer impact exists): Meeting any of the following conditions:

[0108] The instantaneous deformation stress in the central region of the diaphragm is greater than or equal to 1.2σs;

[0109] The overpressure-time ratio is greater than or equal to 0.8 and the instantaneous deformation stress is greater than or equal to σs;

[0110] The waveform jump coefficient is greater than or equal to 5000 Pa²・s (corresponding to severe pressure fluctuations) and the instantaneous deformation stress is greater than or equal to 1.1σs;

[0111] Medium risk: The instantaneous deformation stress is between 0.8σs and 1.2σs, and the overpressure time ratio is between 0.3 and 0.8.

[0112] Low risk: instantaneous deformation stress is less than 0.8σs, and waveform jump coefficient is less than 2000Pa²・s;

[0113] Wherein, σs is the preset yield strength, which is obtained by consulting the technical manual.

[0114] 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, which further includes the following modules:

[0115] 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, and the opening is controlled based on the effective impact force and water hammer impact characteristics, and the real-time damping opening command is output.

[0116] The method for controlling the opening based on effective impact force and water hammer impact characteristics is as follows:

[0117] Minimize the effective impact force actually borne by the diaphragm in the diaphragm-airflow coupling dynamics model;

[0118] S301. Determine the opening optimization target and constraints of the gas self-closing valve based on the effective impact force and water hammer impact characteristics.

[0119] Among them, the opening optimization objectives are 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 criteria.

[0120] Preferably, the constraints include:

[0121] Constraint 1: The rate of change of opening degree is less than or equal to the preset maximum rate of change of opening degree. 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;

[0122] When the overpressure time ratio is <0.8, the maximum rate of change of opening is 5% / ms, to prevent sudden changes in opening from causing a sudden change in airflow velocity and triggering a new pressure shock;

[0123] Constraint 2: The target opening is greater than or equal to 40% (derived from 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 reduce the compatibility with the 3-stage flow channel structure of the turbulence dissipation module).

[0124] Constraint 3: The opening adjustment must be adapted to the current stress state of the diaphragm. If the effective impact force of the impact loading stage (t1 = 20-150 ms) of segment 1 (impact loading stage) is greater than or equal to Q times the maximum allowable force of the diaphragm, the initial opening adjustment rate should be reduced first.

[0125] The preferred value is Q=1.2;

[0126] Preferably, the maximum allowable force on the diaphragm is set by those skilled in the art based on experience;

[0127] If the effective impact force of segment 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 increased.

[0128] S302. Based on the pressure rise rate in the impact feature matrix, construct an opening control strategy to obtain the valve opening.

[0129] Preferably, if the pressure rise rate is higher than or equal to 0.5 bar / ms (severe impact scenario), an exponential gradual adjustment logic is adopted: combining the current actual valve opening, the target safe opening determined by the effective impact force, and the adjustment coefficient used to regulate the rhythm of opening change (such as the adjustment coefficient being 0.1-0.3, with the value decreasing as the impact becomes more severe), the valve opening gradually transitions from the current value to the target safe opening, thereby obtaining a suitable valve opening (avoiding instability caused by sudden changes in opening);

[0130] If the pressure rise rate is less than 0.5 bar / ms (relatively stable impact scenario), a piecewise linear adjustment logic is adopted: first, a piecewise 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 rate; when the time exceeds this node, the valve opening is directly adjusted to the target safe opening.

[0131] S303. Verify based on valve opening degree and constraint conditions. If the valve opening degree meets the constraint conditions, output the damping opening degree command.

[0132] Preferably, the valve opening is output based on the opening control strategy, and the constraint conditions are verified one by one to determine whether the valve opening meets each constraint condition.

[0133] If the valve opening meets the constraint conditions, a damping opening command is output to control the valve opening.

[0134] It is understandable that the purpose of the output damping opening command is:

[0135] Objective 1: By dynamically adjusting the valve opening, minimize the effective impact force actually borne by the diaphragm, reduce damage such as deformation and cracking of the diaphragm caused by water hammer impact exceeding the safe stress range, and directly protect the structural integrity of the diaphragm.

[0136] Objective 2: To provide control basis for the turbulence dissipation module, and to regulate the flow state of the multi-stage flow channel by outputting real-time opening commands, laying the foundation for subsequent flow channel fluid kinetic energy vortex dissipation analysis, and helping to reduce water hammer impact energy.

[0137] Turbulent dissipation module: Controls multi-stage flow channels based on damping opening commands, performs fluid kinetic energy vortex dissipation analysis on the flow channels to obtain energy decay rate, performs diaphragm deformation deviation analysis based on energy decay rate, and determines whether to trigger deformation analysis signal;

[0138] The dynamic allocation ratio of the flow area of ​​the multi-stage flow channel is determined based on the damping opening command, and the flow state of the multi-stage flow channel is controlled based on the dynamic allocation ratio.

[0139] After obtaining the flow state of the control multi-stage flow channel, pressure pulsation of each flow channel is collected by setting N1 sampling points and the standard deviation of pressure pulsation is calculated.

[0140] Obtain the water hammer calibration coefficient, and multiply the standard deviation of the pressure pulsation in each flow channel with the water hammer calibration coefficient to obtain the eddy current intensity coefficient.

[0141] It should be noted that the water hammer calibration coefficient is calibrated by those skilled in the art through experiments on DN15 / DN20 pipes;

[0142] Based on the eddy intensity coefficient, eddy dissipation analysis is performed to obtain the eddy dissipation coefficient of each flow channel.

[0143] The method for performing vortex dissipation analysis is as follows:

[0144] Obtain the dissipation ratio coefficient and the average airflow velocity. Multiply the cube of the average airflow velocity, the dynamic flow area of ​​each flow channel, the dissipation ratio coefficient, and the square of the vortex intensity coefficient of each flow channel to obtain the vortex dissipation coefficient of each stage.

[0145] Preferably, the dissipation ratio is 0.5 times the gas density;

[0146] The energy dissipation time is obtained, the vortex dissipation power of all stages is summed, and the summation result is multiplied by the energy dissipation time to obtain the total dissipation coefficient.

[0147] Obtain the pipe cross-sectional area, maximum airflow velocity, and overpressure duration. Multiply the dissipation ratio coefficient by the pipe cross-sectional area, the cube of the maximum airflow velocity, and the overpressure duration to obtain the initial energy coefficient of water hammer.

[0148] The energy decay rate is obtained by calculating the percentage difference between the initial energy coefficient and the vortex dissipation coefficient.

[0149] like Figure 3 As shown, the energy decay rate is compared with a preset energy decay threshold (e.g., the energy decay threshold is set to 0.8, i.e., 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.

[0150] If the energy decay rate is higher than the preset energy decay threshold, the energy decay rate will continue to change.

[0151] It is understandable that the function of determining the trigger deformation analysis signal is:

[0152] Function 1: To promptly identify situations where water hammer energy dissipation is insufficient, providing a trigger signal for subsequent diaphragm material deformation analysis, reducing the risk of diaphragm overload deformation or damage caused by incompletely decayed water hammer energy, and providing early warning of diaphragm safety risks.

[0153] Function 2: Provides a basis for the dynamic correction module to start. By triggering the signal, the module is guided to locate the weak link in the flow channel dissipation, and then the flow channel area distribution is adjusted to optimize the water hammer energy dissipation capacity of the multi-stage flow channel.

[0154] Dynamic correction module: If triggered, material deformation analysis is performed on the diaphragm to obtain the theoretical deviation of the diaphragm, the eddy current intensity of different flow channels is obtained, and the deviation-eddy current intensity correlation analysis is performed on the diaphragm in combination with the theoretical deviation of the diaphragm to locate the weak link of dissipation flow in the flow channel. A dynamic correction model is established for the weak link of dissipation flow to adjust the distribution of the flow channel area.

[0155] The method for performing material deformation analysis on the diaphragm is as follows:

[0156] If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the vortex dissipation coefficient is calculated to obtain the residual energy value.

[0157] Based on Hooke's law in mechanics of materials, a deviation analysis of diaphragm deformation and residual energy is conducted to obtain the theoretical deviation of the diaphragm.

[0158] Those skilled in the art will understand that the remaining energy (initial water hammer energy minus the sum of the vortex dissipation coefficients of each flow channel) is calculated. Then, based on Hooke's law in mechanics of materials (stress is proportional to strain, i.e., stress is the elastic modulus of the diaphragm multiplied by strain), and combined with the diaphragm's geometric parameters (effective radius, thickness) and material parameters (such as Poisson's ratio), the remaining energy is converted into the stress borne by the diaphragm. Then, the strain is derived through the correlation between stress and strain. Finally, based on the geometric laws of thin plate deformation (corresponding strain to the diaphragm's deformation and theoretical deviation), a quantitative relationship between the remaining energy and the diaphragm's theoretical deviation is established, and the diaphragm's theoretical deviation is calculated.

[0159] The method for obtaining the eddy current intensity of different flow channels and performing deviation-eddy current intensity correlation analysis on the diaphragm in conjunction with the theoretical deviation of the diaphragm is as follows:

[0160] Based on the theoretical deviation of the diaphragm, the dissipation weakness of the core flow channel is located, and a dynamic correction model of theoretical deviation - flow channel ratio is established for the weak dissipation link.

[0161] Among them, the method of locating the dissipation weakness of the core flow channel based on diaphragm theory deviation is as follows:

[0162] Correlation analysis was conducted based on the eddy current intensity and diaphragm theoretical deviation of different flow channels to obtain the correlation degree between deviation and eddy current intensity for each flow channel.

[0163] The correlation analysis is performed by obtaining the vortex intensity and the corresponding dynamic flow area of ​​each flow channel.

[0164] The single-stage diffusion coefficient is obtained by multiplying the vortex intensity of each flow channel by the corresponding dynamic flow area.

[0165] Obtain the preset safety value of the theoretical deviation of the diaphragm, and then compare the theoretical deviation of the diaphragm with the safety value of the theoretical deviation of the diaphragm to obtain the safety factor;

[0166] Calculate the sum of the single-stage diffusion coefficients of all flow channels, multiply the single-stage diffusion coefficients 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-vortex intensity correlation of each flow channel.

[0167] Screening was performed based on the correlation between deviation and eddy current intensity of different flow channels to identify the weak points of dissipation in multi-stage flow channels.

[0168] It is understandable that the way to determine the weak point of dissipation in a multi-stage flow channel is as follows: if the correlation between the deviation and vortex intensity of the 3rd stage flow channel is higher than 0.5 (the correlation is the highest for the 3rd stage flow channel): it indicates that the vortex intensity of the 3rd stage flow channel (the core dissipation link) is insufficient, which is the main cause of the deviation. In this case, the vortex dissipation capacity of the 3rd stage flow channel needs to be matched with the deviation. That is, the weak point of dissipation is the 3rd stage flow channel.

[0169] If the sum of the deviation and vortex intensity correlation of the first and second stage flow channels is higher than 0.6, it indicates that the pretreatment of the first and second stage flow channels is insufficient, resulting in excessive energy transfer to the third stage, which indirectly causes the deviation. In this case, the vortex dissipation capacity of the first and second stage flow channels needs to be matched with the deviation. The weak dissipation link is the first and second stage flow channels.

[0170] The method for establishing a dynamic correction model of theoretical deviation - flow channel ratio for weak dissipation links is as follows:

[0171] If the weak point of 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.

[0172] Preferably, the flow channel correction factor for the third-level flow channel is 0.8;

[0173] If the weakest dissipation link is the first or second stage flow channel, when calculating the correction amount for the first stage flow channel, multiply the safety factor (the ratio of the theoretical deviation of the diaphragm to the safe value of the theoretical deviation of the diaphragm) by the turbulence coefficient of the first stage flow channel, and then multiply the resulting product by (-0.08). The final result is the correction amount for the first stage flow channel.

[0174] When calculating the correction amount for the second-stage flow channel, multiply the safety factor (the ratio of the theoretical deviation of the diaphragm to the safe value of the theoretical deviation of the diaphragm) by the turbulence coefficient of the second-stage flow channel, and then multiply the resulting product by 0.08. The final result is the correction amount for the second-stage flow channel.

[0175] The turbulence coefficient of the flow channel is set by those skilled in the art; the coefficient of 0.08 is an empirical adaptation value obtained through extensive experiments and simulations, which 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 theoretical deviation of the diaphragm to the safety value) and the turbulence coefficient of the flow channel, without causing system instability due to excessive correction. The correction amount of the first-stage flow channel is negative and the correction amount of the second-stage flow channel is positive, so that the correction amounts of the first-stage and second-stage flow channels form a complementary control logic - so that the flow characteristics (such as flow capacity) of the first-stage flow channel are adapted in reverse 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 channels and dynamically correcting weak points in dissipation.

[0176] It should be noted that the process of obtaining the correction amount based on the 3rd stage flow channel and the process of obtaining the correction amount of the 1st and 2nd stage flow channels realizes the establishment of a dynamic correction model of theoretical deviation - flow channel ratio.

[0177] The correction amount obtained from the dynamic correction model is fed back to the multi-stage flow channel control link to correct the dynamic allocation ratio of the flow area of ​​the flow channel.

[0178] Those skilled in the art will understand that the correction is performed as follows: The dynamic correction model first calculates the correction amount of the flow area of ​​each flow channel based on the deviation of the core flow channel vortex intensity coefficient from the optimal range, combined with real-time data such as diaphragm deformation and water hammer energy dissipation; then, these correction amounts are fed back to the actuators (such as electric regulating valves) of the multi-stage flow channels in the form of control commands. The actuators adjust their opening according to the correction amount, increasing the flow area ratio of the flow channels with insufficient dissipation to enhance vortex dissipation, and decreasing 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 correction is performed until the dynamic allocation ratio of the flow area of ​​the multi-stage flow channels is adapted to the current operating conditions, ensuring that the vortex dissipation capacity of the core flow channel is stable within the preset optimal range.

[0179] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the present invention should still fall within the scope of the present invention.

Claims

1. A smart gas self-closing valve with real-time operating status monitoring, characterized in that: The intelligent gas self-closing valve includes a status monitoring system, which comprises the following modules: Transient capture module: acquires the gas pressure waveform of the gas channel during the gas supply recovery phase, performs parameter gradient analysis on the rising segment of the gas pressure waveform, obtains the water hammer impact characteristics, and constructs the impact characteristic matrix. The method for performing the parameter gradient parsing is as follows: Collect the gas pressure of the gas channel at N sampling points during the gas supply recovery phase and output the original gas pressure waveform; The original gas pressure waveform is preprocessed and purified to obtain the purified gas waveform. Obtain the midpoint of the rising segment of the gas purification waveform, and divide the rising segment into two parts using the midpoint as the origin to obtain multiple rising sub-segments. Feature extraction is performed on each rising segment to obtain the pressure rise rate, overpressure time ratio, waveform curvature peak value and waveform jump coefficient of each rising segment as water hammer impact characteristics. Impact prediction module: Constructs a diaphragm-airflow coupled dynamics model by combining coupled dynamics theory with impact feature matrix, obtains impact judgment characteristics, and determines whether the diaphragm is at risk of water hammer impact; The method for determining whether the diaphragm poses a risk of water hammer impact is as follows: Obtain the impact determination characteristics output by the diaphragm-airflow coupling dynamics 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, the diaphragm is determined to be at risk of water hammer impact. The method for obtaining impact determination features is as follows: A transient dynamics sub-model of airflow is constructed, and the intrinsic parameters of the gas and diaphragm are obtained. Combined with the water hammer impact characteristics, the transient dynamics sub-model of airflow is input to obtain the instantaneous impact force. An energy transfer coupling interface is constructed, and the transient dynamics sub-model of airflow and the mechanical response sub-model of diaphragm are processed in conjunction through the energy transfer coupling interface to obtain the instantaneous deformation stress in the central region of the diaphragm. The instantaneous deformation stress in the central region of the diaphragm, as well as the overpressure time ratio and waveform jump coefficient, output from the diaphragm-airflow coupling dynamic model are integrated and used as impact judgment features. 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, and the opening is controlled based on the effective impact force and water hammer impact characteristics, and the real-time damping opening command is output. The opening degree control process is performed as follows: Minimize the effective impact force actually borne by the diaphragm in the diaphragm-airflow coupling dynamics model; The opening optimization target and constraints of the gas self-closing valve are determined based on the effective impact force and water hammer impact characteristics. Based on the pressure rise rate in the impact feature matrix, an opening control strategy is constructed to obtain the valve opening. The verification is based on the valve opening degree combined with the constraint conditions. If the valve opening degree meets the constraint conditions, the damping opening degree command is output. Turbulent dissipation module: Controls multi-stage flow channels based on damping opening commands, performs fluid kinetic energy vortex dissipation analysis on the flow channels to obtain energy decay rate, performs diaphragm deformation deviation analysis based on energy decay rate, and determines whether to trigger deformation analysis signal.

2. The intelligent gas self-closing valve for real-time operation status monitoring according to claim 1, characterized in that: The method for determining whether a deformation analysis signal has been triggered is as follows: The eddy intensity coefficient is obtained, and the vortex dissipation coefficient of different flow stages is obtained by constructing an energy dissipation equation. The total dissipation coefficient is calculated based on the vortex dissipation coefficient and energy dissipation time of different flow channels. Obtain the initial energy coefficient of the water hammer, calculate the percentage difference between the initial energy coefficient and the vortex dissipation coefficient, and obtain the energy decay rate. Comparative analysis based on energy decay rate is used to determine whether a deformation analysis signal is triggered.

3. The intelligent gas self-closing valve for real-time operation status monitoring according to claim 2, characterized in that: The method for obtaining the eddy current intensity coefficient is as follows: The dynamic allocation ratio of the flow area of ​​the multi-stage flow channel is determined based on the damping opening command, and the flow state of the multi-stage flow channel is controlled based on the dynamic allocation ratio. After obtaining the flow state of the multi-stage flow channels, 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, and multiply the standard deviation of the pressure pulsation in each flow channel with the water hammer calibration coefficient to obtain the eddy current intensity coefficient.

4. The intelligent gas self-closing valve for real-time operation status monitoring according to claim 3, characterized in that: It also includes the following modules: Dynamic correction module: If triggered, it performs material deformation analysis on the diaphragm to obtain the theoretical deviation of the diaphragm, obtains the eddy current intensity of different flow channels, and performs deviation-eddy current intensity correlation analysis on the diaphragm in combination with the theoretical deviation of the diaphragm to locate the dissipation weakness of the flow channel. It then establishes a dynamic correction model for the dissipation weakness to adjust the distribution of the flow channel area.

5. The intelligent gas self-closing valve for real-time operation status monitoring according to claim 4, characterized in that: The method for locating the weak point of dissipation in the flow channel is as follows: The eddy current intensity and diaphragm theoretical deviation of different flow channels were obtained and correlation analysis was performed to obtain the correlation degree between deviation and eddy current intensity for each flow channel. Screening was performed based on the correlation between deviation and eddy current intensity in different flow channels to identify the weak points in the dissipation of multi-stage flow channels.

6. The intelligent gas self-closing valve for real-time operation status monitoring according to claim 5, characterized in that: The method for obtaining the theoretical deviation of the membrane is as follows: If the deformation analysis signal is triggered, the difference between the initial energy coefficient and the vortex dissipation coefficient is calculated to obtain the residual energy value. Based on Hooke's law in mechanics of materials, a deviation analysis of diaphragm deformation and residual energy is conducted to obtain the theoretical deviation of the diaphragm.

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