A method and system for collecting transient response data of a pressure reducing valve based on multi-range adaptive switching

Abstract

The application provides a kind of based on multiple range adaptive switching pressure reducing valve transient response data acquisition method and system, it is related to fluid control technical field, the method includes: step 1, obtains the preset test working condition parameter of pressure reducing valve, based on the pressure threshold value and flow interval in preset test working condition parameter, from multiple parallel test channel adaptive matching and switch to target range branch, construct initial fluid conduction loop;The centroid position, moment of inertia, polar moment of inertia and bending center of the fluid passage section of target range branch are executed analytical calculation, obtain section geometric characteristic parameter;Step 2, based on section geometric characteristic parameter and the flow cross section characteristics of initial fluid conduction loop, establish reference pressure field with stable negative pressure gradient on the outlet side of pressure reducing valve, and real-time monitoring steady state convergence state of reference pressure field.The application realizes the standardized collection of pressure reducing valve in positive pressure-negative pressure full working condition, high-low flow range under transient response.

Description

Technical Field

[0001] This invention relates to the field of fluid control technology, and in particular to a method and system for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching. Background Technology

[0002] Existing transient response data acquisition technologies for pressure reducing valves generally only build single-range test channels for conventional positive pressure conditions, and do not have the ability to adaptively switch between multiple ranges. This makes it difficult to meet the transient performance testing requirements of pressure reducing valves across negative pressure to low-pressure and positive pressure ranges in high-end scenarios such as semiconductor manufacturing and aerospace vacuum simulation.

[0003] Taking the acquisition of transient flow rate and step response of a high-precision pressure reducing valve used in a semiconductor manufacturing process as an example, the existing acquisition system can only generate pressure steps using fixed-range pipelines and manual valve control. It is difficult to automatically match the optimal test branch according to the test pressure threshold and flow range, and it is difficult to establish a stable and controllable negative pressure reference pressure field at the outlet side of the pressure reducing valve. At the same time, there are problems such as slow valve step response, poor sampling synchronization, and large measurement error in the low-pressure section. It is impossible to accurately capture the transient displacement of the valve core and the propagation characteristics of the pressure wave, resulting in insufficient cross-range test accuracy, distortion of negative pressure transient data, poor repeatability of step excitation, and inability to effectively obtain complete transient overshoot, settling time and creep characteristic parameters. Summary of the Invention

[0004] This invention provides a method and system for acquiring transient response data of pressure reducing valves based on multi-range adaptive switching, realizing standardized acquisition of transient response of pressure reducing valves under all operating conditions of positive and negative pressure and high and low flow ranges.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: In a first aspect, a method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching is provided, the method comprising: Step 1: Obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, adaptively match and switch from the multi-parallel test channels to the target range branch to construct the initial fluid conduction loop. Perform analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. Step 2: Based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, a reference pressure field with a stable negative pressure gradient is established on the outlet side of the pressure reducing valve, and the steady-state convergence state of the reference pressure field is monitored in real time. Step 3: When the steady-state convergence meets the preset threshold condition, a transient pressure excitation is applied to the surface of the reference pressure field through the flow resistance step change caused by valve switching. The propagation and reflection characteristics of the pressure wave during the excitation process are quantified according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. Step 4: In response to the pressure wave propagation and transient flow rate change in the pipeline caused by the kinematic displacement response, the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve are collected simultaneously to obtain the original dynamic response dataset. Step 5: Based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, perform signal noise reduction processing and transient characteristic parameter calculation to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

[0006] Furthermore, the preset test condition parameters of the pressure reducing valve are obtained. Based on the pressure threshold and flow range in the preset test condition parameters, the valve is adaptively matched and switched from multiple parallel test channels to the target range branch to construct an initial fluid conduction loop, including: The steady-state working pressure range is determined based on the pressure threshold in the preset test conditions parameters. The upper and lower limits of the volumetric flow rate are determined based on the flow range. The pressure threshold and flow range are compared with the rated pressure level and flow capacity of each parallel test channel. The branch with the rated pressure level covering the pressure threshold and the flow capacity covering the flow range is selected as the target range branch. Switch the fluid conduction path to the target range branch, while blocking the other parallel branches. Monitor whether the pressure and flow rate in the switched branch are stable within the preset deviation range. After stabilization, record the channel cross-sectional profile data, wall thickness distribution parameters, and elastic modulus and Poisson's ratio of the pipe material of the target range branch to obtain the initial fluid conduction loop.

[0007] Furthermore, analytical calculations are performed on the centroid position, moment of inertia, polar moment of inertia, and bending center of the fluid channel cross-section of the target range branch to obtain the cross-sectional geometric characteristic parameters, including: Based on the channel cross-sectional profile data of the target range branch, the cross-section is divided into several basic geometric sub-units. The area of ​​each sub-unit and the static moment about the initial reference coordinate system are calculated respectively, and the coordinates of the centroid of the cross-section in the initial reference system are obtained. A centroidal coordinate system is established with the centroid as the origin. The moment of inertia and product of inertia of each sub-unit about the centroidal axis are calculated. The direction of the principal inertia axis and the corresponding principal moment of inertia are solved by coordinate rotation iteration. For each thin-walled segment in the cross section, the assumption of linear distribution of bending shear stress along the wall thickness is adopted. The moment of shear stress about the centroid of each segment is integrated and superimposed to determine the position of the bending center. For the calculation of the polar moment of inertia, according to the opening characteristics of the cross section, the thin film analogy method under free torsion is used to solve the torsional constant of the cross section to obtain the geometric characteristic parameters of the cross section.

[0008] Furthermore, based on the cross-sectional geometric parameters and the flow cross-sectional characteristics of the initial fluid conduction loop, a reference pressure field with a stable negative pressure gradient is established at the outlet side of the pressure reducing valve, and the steady-state convergence state of the reference pressure field is monitored in real time, including: Based on the obtained centroid coordinates, principal moment of inertia, bending center position, and polar moment of inertia of the cross section, combined with the flow cross-sectional area and hydraulic diameter of the initial fluid conduction loop, the friction coefficient and local resistance coefficient of the outlet side pipeline of the pressure reducing valve are calculated. Based on the resistance coefficient, the downstream negative pressure regulating device is driven to gradually reduce the pressure on the outlet side of the pressure reducing valve while keeping the inlet pressure constant. A negative pressure gradient field with gradually decreasing pressure along the flow direction is formed on the outlet side. Multiple pressure sensing points are arranged on the outlet side of the pressure reducing valve to collect the pressure value of each sensing point in real time. The pressure of each point is compared with the theoretical negative pressure distribution curve point by point to calculate the overall deviation of the current pressure field. Based on the overall deviation of the current pressure field, the opening of the negative pressure regulating device is continuously fine-tuned to gradually reduce the overall deviation until the deviation is lower than the preset threshold for three consecutive sampling cycles, at which point the reference pressure field is determined to have entered a steady-state convergence state.

[0009] Furthermore, when the steady-state convergence meets the preset threshold condition, a transient pressure excitation is applied to the surface of the reference pressure field through the flow resistance step change caused by valve switching. The propagation and reflection characteristics of the pressure wave during the excitation process are quantified based on the cross-sectional geometric parameters, causing the pressure reducing valve core to generate a kinematic displacement response under the coupling effect of fluid dynamic pressure difference and inertial force, including: Based on the obtained outlet side pressure distribution data and negative pressure gradient value under steady-state convergence, it is confirmed that the pressure fluctuation amplitude and gradient change rate at each point in the current reference pressure field are lower than the preset threshold condition, and this moment is recorded as the zero-time reference for transient excitation. Based on the zero-time reference, a predetermined timing drive signal is applied to the fast switching valve set upstream of the pressure reducing valve, causing the valve to switch instantaneously from the fully open state to the preset partially closed state. A transient pressure excitation wave with known amplitude and steep rise edge, starting from the zero time, is superimposed on the surface of the stabilized reference pressure field. The peak pressure and rise time of the transient pressure excitation wave are recorded. By combining the peak pressure and rise time of the transient pressure excitation wave with the principal moment of inertia and polar moment of inertia in the cross-sectional geometric parameters and the elastic wave velocity calculation formula of the pipeline, the velocity of the excitation wave propagating in the forward direction of the pipeline, the reflection coefficient at the abrupt change in the cross-section, and the attenuation factor after multiple reflections are quantified, and a set of pressure wave propagation characteristic parameters is obtained. Based on the set of pressure wave propagation characteristic parameters, the arrival time and pressure amplitude of the excitation wave to the front and rear end faces of the pressure reducing valve core are discretized along the pipeline axis to obtain the transient fluid dynamic pressure difference sequence. The transient fluid dynamic pressure difference sequence is used as an external load input and coupled with the inertial force determined by the mass distribution of the valve core and the spring preload to obtain the kinematic displacement response that changes with time.

[0010] Furthermore, in response to the pressure wave propagation and transient flow rate changes within the pipeline caused by the kinematic displacement response, the time-domain pressure sequence and instantaneous flow rate sequence at the inlet and outlet of the pressure reducing valve are simultaneously acquired to obtain the original dynamic response dataset, including: The obtained kinematic displacement response curve is used to extract the starting time when the valve core displacement first leaves the initial equilibrium position, the time when the displacement peak occurs, and the time window when it returns to the vicinity of the equilibrium position, so as to obtain the trigger time reference. Based on the trigger time reference, the inlet pressure sensor and the outlet pressure sensor are activated, and the inlet time domain pressure sequence and the outlet time domain pressure sequence are synchronously acquired from the preset buffer period before the start time to the buffer period after the recovery time at a sampling frequency twice higher than the highest frequency component of the kinematic displacement response. The inlet and outlet flow meters are started in parallel, and the same sampling frequency is used to synchronously collect the inlet instantaneous flow sequence and outlet instantaneous flow sequence within the same time window. The four sequences are aligned according to the time axis to form a multidimensional raw dynamic response dataset indexed by time. The pressure and flow sequences in the multidimensional original dynamic response dataset are compared with the transient fluid dynamic pressure difference sequence point by point to check the deviation. Obvious outliers caused by sensor noise are removed, and the normal values ​​before and after the time of the outlier are filled by linear interpolation to obtain the cleaned original dynamic response dataset.

[0011] Furthermore, based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, signal denoising processing and transient characteristic parameter calculation are performed to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve, including: Obtain the original dynamic response dataset, and simultaneously read the principal moment of inertia and bending center position from the cross-sectional geometric characteristic parameters, as well as the rated pressure level and flow capacity of the target range branch as range adaptation parameters. Based on the sensor accuracy level and range adaptation parameters, the noise floor level of each pressure sequence and flow sequence is determined. An adaptive filter width associated with the polar moment of inertia in the cross-sectional geometric characteristic parameters is used to perform wavelet threshold denoising on the inlet time domain pressure sequence, outlet time domain pressure sequence, inlet instantaneous flow sequence and outlet instantaneous flow sequence in the original dynamic response dataset to obtain the denoised dynamic response sequence. The transient pressure difference change curve is obtained by performing difference calculation on the inlet and outlet pressure sequences after noise reduction, and the transient flow rate change curve is obtained by performing difference calculation on the inlet and outlet flow rate sequences. The two curves are then cross-correlation analysis with the transient fluid dynamic pressure difference sequence to extract time delay, peak ratio and decay rate as primary characteristic parameters of transient response. Based on the primary characteristic parameters, combined with the obtained centroid coordinates of the cross section and principal moments of inertia, the equivalent dynamic stiffness and damping ratio of the pressure reducing valve core during the transient response process are calculated using a coupled analytical method of axial tensile and compressive stress and bending normal stress, thus obtaining the second-order transient characteristic parameters. The second-order transient characteristic parameters and the range adaptation parameters of the target range branch are normalized to obtain standardized data acquisition results.

[0012] Secondly, a transient response data acquisition system for a pressure reducing valve based on multi-range adaptive switching includes: The calculation module is used to obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, it adaptively matches and switches from multiple parallel test channels to the target range branch to construct the initial fluid conduction loop. It performs analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. The monitoring module is used to establish a reference pressure field with a stable negative pressure gradient on the outlet side of the pressure reducing valve based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, and to monitor the steady-state convergence state of the reference pressure field in real time. The switching module is used to apply transient pressure excitation to the surface of the reference pressure field by the flow resistance step change caused by valve switching when the steady-state convergence state meets the preset threshold condition. It also quantifies the propagation and reflection characteristics of the pressure wave during the excitation process according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. The acquisition module is used to respond to the propagation of pressure waves and transient flow of medium in the pipeline caused by kinematic displacement response, and simultaneously acquire the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve to obtain the original dynamic response dataset. The processing module is used to perform signal noise reduction processing and transient characteristic parameter calculation based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

[0013] Thirdly, a computing device, comprising: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the method.

[0014] Fourthly, a computer-readable storage medium storing a program that, when executed by a processor, implements the method.

[0015] The above-described solution of the present invention has at least the following beneficial effects: By employing a multi-channel parallel test system with adaptive matching and switching of target range branches, analyzing the geometric characteristics of the fluid channel cross-section, constructing a stable negative pressure reference pressure field on the outlet side, applying rapid valve step excitation, and using high-frequency synchronous acquisition, signal noise reduction, and transient characteristic calculation techniques, this approach overcomes the technical problems of existing technologies, such as poor single-range adaptability, lack of negative pressure condition testing, inaccurate transient excitation, poor sampling synchronization, large measurement errors in the low-pressure section, distortion of negative pressure transient data, poor repeatability of step excitation, and inability to obtain complete transient characteristic parameters. This enables standardized, high-precision, and highly repeatable acquisition of the transient response of the pressure reducing valve under all positive and negative pressure conditions and high and low flow ranges. It accurately captures the transient displacement and pressure wave propagation characteristics of the valve core, and completely acquires transient overshoot, settling time, and creep characteristic parameters, thereby improving test accuracy. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching, as provided in an embodiment of the present invention.

[0017] Figure 2 This is a schematic diagram of a transient response data acquisition system for a pressure reducing valve based on multi-range adaptive switching, provided by an embodiment of the present invention.

[0018] Figure 3 This is a schematic diagram of the reference negative pressure field distribution on the outlet side of the pressure reducing valve.

[0019] Figure 4 This is a schematic diagram of the deviation convergence during the establishment of the reference negative pressure field.

[0020] Figure 5 This is a diagram showing the comparison of noise reduction effects on the export pressure signal.

[0021] Figure 6 This is a schematic diagram comparing the effects of transient pressure difference feature extraction. Detailed Implementation

[0022] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough understanding of the present disclosure and to fully convey the scope of the disclosure to those skilled in the art.

[0023] like Figure 1 As shown, an embodiment of the present invention proposes a method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching. The method includes the following steps: Step 1: Obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, adaptively match and switch from the multi-parallel test channels to the target range branch to construct the initial fluid conduction loop. Perform analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. Step 2: Based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, a reference pressure field with a stable negative pressure gradient is established on the outlet side of the pressure reducing valve, and the steady-state convergence state of the reference pressure field is monitored in real time. Step 3: When the steady-state convergence meets the preset threshold condition, a transient pressure excitation is applied to the surface of the reference pressure field through the flow resistance step change caused by valve switching. The propagation and reflection characteristics of the pressure wave during the excitation process are quantified according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. Step 4: In response to the pressure wave propagation and transient flow rate change in the pipeline caused by the kinematic displacement response, the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve are collected simultaneously to obtain the original dynamic response dataset. Step 5: Based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, perform signal noise reduction processing and transient characteristic parameter calculation to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

[0024] In this embodiment of the invention, by employing multiple parallel test channels to adaptively switch the target range branch and calculate the cross-sectional geometric characteristic parameters, a stable negative pressure reference pressure field is also constructed on the outlet side of the pressure reducing valve. Precise transient pressure excitation is applied by valve switching, and pressure and flow sequences are simultaneously acquired and noise reduction and feature calculation are performed. Therefore, the problems of poor single-range adaptability, lack of negative pressure test capability, inaccurate transient excitation, insufficient data acquisition synchronization, and inaccurate dynamic feature capture in traditional tests are overcome. This enables standardized acquisition of the transient response of the pressure reducing valve under full operating conditions from positive to negative pressure and under high and low flow ranges, accurately obtaining complete transient characteristic parameters and improving the accuracy of the test.

[0025] In a preferred embodiment of the present invention, step 1 above may include: Step 1.1: Determine the steady-state operating pressure range based on the pressure threshold in the preset test conditions parameters, and determine the upper and lower limits of the volumetric flow rate based on the flow range. Compare the pressure threshold and flow range with the rated pressure level and flow capacity of each parallel test channel item by item. Select the branch whose rated pressure level covers the pressure threshold and whose flow capacity covers the flow range as the target range branch. Specifically, this includes: obtaining the preset test conditions parameters for the high-precision pressure reducing valve used in semiconductor processes; clarifying that the pressure threshold in the preset test conditions parameters is the lower limit of the test pressure -0.095MPa and the upper limit of the test pressure 0.3MPa; and determining the steady-state operating pressure range as -0.095MPa to 0.3MPa based on this pressure threshold. Also clarifying that the flow range in the preset test conditions parameters is the lower limit of the volumetric flow rate 0.005L / min and the upper limit of the volumetric flow rate 50L / min based on this flow range.

[0026] The system has three independent parallel test channels, each with pre-set rated pressure and flow capacity. The first parallel test channel has a rated pressure of -0.1 MPa to 0.6 MPa and a flow capacity of 0.001 L / min to 100 L / min. The second parallel test channel has a rated pressure of -0.1 MPa to 0.2 MPa and a flow capacity of 0.001 L / min to 10 L / min. The third parallel test channel has a rated pressure of 0 MPa to 0.8 MPa and a flow capacity of 1 L / min to 200 L / min.

[0027] The test pressure threshold is compared item by item with the rated pressure level of each parallel test channel, and the test flow range is compared item by item with the flow capacity of each parallel test channel. The comparison process follows a clear mathematical judgment relationship, and the formula format and specifications are as follows: In the mathematical formula for determining pressure coverage capacity: To test the lower limit of pressure, To test the maximum stress level, This is the lower limit of the rated pressure for a single parallel test channel. The rated pressure limit for a single parallel test channel is defined as follows: a single channel must meet both of the above conditions simultaneously to be deemed to meet the pressure coverage requirements.

[0028] In the mathematical formula for determining traffic coverage capability: To test the lower limit of traffic, To test the traffic limit, This represents the lower limit of the current carrying capacity of a single parallel test channel. The upper limit of the flow capacity of a single parallel test channel is that a single channel must meet both of the above conditions to be determined to meet the flow coverage requirements.

[0029] Substitute the preset test parameters into the above judgment relationship to verify each of the three parallel test channels.

[0030] The verification results for the first parallel test channel are as follows: the rated pressure lower limit of -0.1 MPa is less than or equal to the test pressure lower limit of -0.095 MPa, and the rated pressure upper limit of 0.6 MPa is greater than or equal to the test pressure upper limit of 0.3 MPa, thus meeting the pressure coverage requirements. The flow capacity lower limit of 0.001 L / min is less than or equal to the test flow rate lower limit of 0.005 L / min, and the flow capacity upper limit of 100 L / min is greater than or equal to the test flow rate upper limit of 50 L / min, thus meeting the flow coverage requirements.

[0031] The verification result of the second parallel test channel was that the upper limit of the rated pressure (0.2 MPa) was less than the upper limit of the test pressure (0.3 MPa), which did not meet the pressure coverage requirement and was directly eliminated. The verification result of the third parallel test channel was that the lower limit of the rated pressure (0 MPa) was greater than the lower limit of the test pressure (-0.095 MPa), which did not meet the pressure coverage requirement and was directly eliminated. After item-by-item comparison and verification, only the first parallel test channel could simultaneously and completely cover the preset pressure threshold and flow range, and this channel was selected as the target range branch.

[0032] Step 1.2: Switch the fluid conduction path to the target range branch while blocking the other parallel branches. Monitor whether the pressure and flow rate in the branch after switching are stable within the preset deviation range. After stabilization, record the channel cross-sectional profile data, wall thickness distribution parameters, and elastic modulus and Poisson's ratio of the pipe material of the target range branch to obtain the initial fluid conduction circuit. Specifically, this includes: fully opening the pneumatic diaphragm switching valves at the inlet and outlet of the target range branch to completely switch the fluid conduction path to the target range branch, and simultaneously outputting a closing signal to fully close the normally closed isolation valves at the inlet of the second and third parallel test channels, completely blocking the fluid passage of the other two parallel branches, avoiding fluid cross-flow between different branches, and ensuring the stability of fluid parameters in the target range branch.

[0033] The high-precision pressure sensor and thermal mass flow meter within the target range branch are activated to collect real-time fluid pressure and volumetric flow rate data. The preset pressure stability deviation band is ±0.0005 MPa, and the preset flow stability deviation band is ±0.0002 L / min. The sampling frequency of the pressure sensor and mass flow meter is set to 1000 Hz to continuously monitor pressure and flow rate changes within the branch. When the pressure data for eight consecutive sampling cycles remains stable within the preset pressure stability deviation band, and the flow rate data for the same cycle remains stable within the preset flow stability deviation band, the target range branch switching is considered complete, and the internal fluid state has stabilized. After the branch state stabilizes, the channel cross-sectional profile data of the target range branch is collected and recorded. This branch uses a circular, uniform cross-section flow pipe with an inner diameter of 10 mm. The uniform wall thickness distribution parameter of the branch is recorded as 1.5 mm, and the elastic modulus of the branch pipe material is read and recorded. The Poisson's ratio is 0.29. All the above channel parameters, pipe material parameters, and fluid stability parameters are integrated and archived to construct a complete initial fluid conduction loop.

[0034] In this embodiment of the invention, the optimal range branch is matched according to the pressure threshold and flow range of the test conditions, the path is switched and the other branches are blocked, and the stable state of the branch is monitored and the cross-sectional and pipe parameters are recorded to construct the initial loop. Therefore, the problem of the fixed range of the traditional test device being unable to adapt to the changing conditions is overcome. The defect of excessive pressure and flow fluctuations during branch switching is solved, which makes it difficult to stabilize quickly. It also avoids the situation where the subsequent calculation and test are deviated due to the lack or inaccuracy of the basic loop parameters. The test error caused by range mismatch and initial loop instability is eliminated from the source. In this way, the test branch is always highly adapted to the actual test requirements, ensuring the test accuracy under high and low pressure and large and small flow scenarios, allowing the initial fluid conduction loop to quickly reach a stable state, and at the same time obtaining complete and accurate basic loop parameters.

[0035] In a preferred embodiment of the present invention, step 1 above may include: Step 1.3: Based on the channel cross-sectional profile data of the target range branch, the cross-section is divided into several basic geometric sub-units. The area and static moment of each sub-unit about the initial reference coordinate system are calculated to obtain the coordinates of the centroid of the cross-section in the initial reference system. Specifically, this includes: acquiring the recorded channel cross-sectional profile data of the target range branch, which adopts a circular hollow cross-section flow pipe with uniform wall thickness, an inner diameter of 10mm, an outer diameter of 13mm, and a uniform wall thickness of 1.5mm; establishing an initial reference coordinate system, with the origin of the initial reference coordinate system set at the lower left of the outer profile of the cross-section. At the corner endpoint, the X-axis of the initial reference coordinate system extends horizontally to the right along the cross-section, and the Y-axis extends vertically upward along the cross-section. The units of the coordinate system are uniformly set to millimeters. To ensure calculation accuracy and convergence, the complete hollow circular cross-section is divided into 36 basic geometric sub-units along the circumference. Each sub-unit is a sector-shaped ring structure with a central angle of 10 degrees. The radial width of each sub-unit is consistent with the cross-section wall thickness, which is 1.5 mm. The geometric dimensions and shapes of all sub-units are completely identical. The area of ​​each basic geometric sub-unit is calculated separately. The formula for calculating the area of ​​a single sector-shaped ring sub-unit is: ; In the formula: For the first The area of ​​each basic geometric subunit. This is the central angle corresponding to a single sub-unit, with a value of 10°. The radius of the outer contour of the cross section is 6.5 mm. Let be the radius of the inner contour of the cross section, taken as 5mm. Calculations show that the area of ​​a single basic geometric sub-unit is 1.505mm². 2 The total area of ​​the 36 sub-units is consistent with the overall cross-sectional area, which is 54.18 mm². 2 Calculate the static moments of each basic geometric sub-element about the X and Y axes of the initial reference coordinate system. The formula for calculating the static moment is: ; In the formula: For the first The static moments of each basic geometric sub-element about the X-axis of the initial reference coordinate system. For the first The static moments of each basic geometric sub-element about the Y-axis of the initial reference coordinate system. For the first The X-axis coordinates of the centroid of each basic geometric sub-unit in the initial reference coordinate system. For the first The centroids of the 36 basic geometric sub-elements are located in the Y-axis coordinates of the initial reference coordinate system. The static moments of the 36 basic geometric sub-elements are summed to obtain the total static moment of the cross section about the X-axis and Y-axis of the initial reference coordinate system. The formula for calculating the total static moment is as follows: ; Based on the total static moment and total area of ​​the cross section, the coordinates of the centroid of the cross section in the initial reference coordinate system are calculated. The formula for calculating the centroid coordinates is: ; In the formula: Let X be the x-axis coordinate of the centroid of the cross section in the initial reference coordinate system. The Y-axis coordinate of the centroid of the cross section in the initial reference coordinate system. Given the total area of ​​the cross section, the coordinates of the centroid of the cross section in the initial reference coordinate system are calculated to be 6.5 mm on the X-axis and 6.5 mm on the Y-axis, which completely coincides with the geometric center of the cross section. This completes the solution for the centroid coordinates of the cross section.

[0036] Step 1.4: Establish a centroidal coordinate system with the centroid as the origin. Calculate the moment of inertia and product of inertia of each sub-unit about the centroidal axis. Solve for the direction of the principal inertia axis and the corresponding principal moment of inertia through coordinate rotation iteration. For each thin-walled segment in the cross-section, assume a linear distribution of bending shear stress along the wall thickness. Integrate the moments of shear stress about the centroid of each segment, and determine the bending center position after superposition. For the calculation of the polar moment of inertia, based on the opening characteristics of the cross-section, use the thin film analogy method under free torsion to solve for the torsional constant of the cross-section to obtain the geometric characteristic parameters of the cross-section. Specifically, establish a centroidal coordinate system with the obtained cross-section centroid as the origin. The X-axis of the centroidal coordinate system extends horizontally to the right along the cross-section, and the Y-axis extends vertically upward along the cross-section. The unit of the coordinate system is uniformly set to millimeters. Calculate the moment of inertia of each basic geometric sub-unit about the X-axis and Y-axis of the centroidal coordinate system, as well as the product of inertia of the corresponding coordinate axes. The formulas for calculating the moment of inertia and product of inertia are: ; In the formula: For the first The moment of inertia of each basic geometric sub-element about the X-axis of the centroidal coordinate system. For the first The moment of inertia of each basic geometric sub-element about the Y-axis of the centroidal coordinate system. For the first The product of inertia of each basic geometric sub-element with respect to the centroidal coordinate system. For the first The moment of inertia of each basic geometric sub-element about its centroid X-axis. For the first The moment of inertia of each basic geometric sub-element about its centroid Y-axis. For the first The product of inertia of each basic geometric sub-element about its own centroidal coordinate system is used to obtain the total moment of inertia and total product of inertia of the cross section about the X-axis and Y-axis of the centroidal coordinate system. The formulas for calculating the total moment of inertia and total product of inertia are as follows: ; The calculated total moment of inertia of the cross section about the X-axis of the centroidal coordinate system is 910.99 mm. 4 The total moment of inertia about the Y-axis is 910.99 mm. 4 The total inertial product is 0 mm. 4 The principal inertial axis directions and corresponding principal moments of inertia are solved using a coordinate rotation iterative method. The iteration step size for the coordinate rotation angle is set to 0.5 degrees, and the iteration convergence threshold is set to 1×10⁻⁶. -6 mm 4 The formula for calculating the product of inertia after coordinate rotation is: ; In the formula: The product of inertia of the rotated coordinate system. Let the rotation angle be the coordinate axis. When the absolute value of the product of inertia after rotation, obtained through iterative calculation, is less than or equal to the iteration convergence threshold, the coordinate axis corresponding to the current rotation angle is determined to be the principal inertia axis, and the moment of inertia of the corresponding coordinate axis is the principal moment of inertia. Through iterative calculation, any coordinate axis passing through the centroid of this circular hollow cross-section is a principal inertia axis, and the corresponding principal moment of inertia is 910.99 mm. 4 For each thin-walled segment in the cross-section, assuming a linear distribution of bending shear stress along the wall thickness, the location of the bending center of the cross-section is calculated. The circular hollow cross-section is divided into 72 equal thin-walled segments along the circumference, each with an arc length of 0.502 mm and a wall thickness of 1.5 mm. The bending shear stress on each thin-walled segment is calculated using the following formula: ; In the formula: For the bending shear stress on the thin-walled segment, The transverse shear force on the cross section. Let be the static moment of the cross section on one side of the thin-walled segment about the centroid X-axis. Let the wall thickness be 1.5 mm. The moment of shear stress about the centroid of the section is calculated by integration for each thin-walled segment. The moments of all segments are summed, and the bending center of the section is determined based on the moment equilibrium relationship. Calculations show that the bending center of the circular hollow section completely coincides with the centroid, with the coordinates being the origin of the centroid coordinate system. For the calculation of the polar moment of inertia of the section, based on the closed-end characteristic of the circular hollow section, the thin-film analogy method under free torsion is used to solve for the torsional constant of the section. The torsional constant is the polar moment of inertia of the section. The formula for calculating the torsional constant of a closed thin-walled section is: ; In the formula: Let be the torsional constant of the cross section, i.e., the polar moment of inertia. The area enclosed by the centerline of the closed section. Let the arc length of the thin-walled segment be denoted as . Let the cross-sectional wall thickness be 1.5 mm. The calculated area enclosed by the centerline of the cross-section is 103.87 mm². 2 The integral value of the loop obtained by integral calculation is 24.09 mm. -1 The final polar moment of inertia of the cross section is calculated to be 1791.25 mm. 4 By integrating and archiving the centroid coordinates, principal inertial axis directions, principal moments of inertia, bending center positions, and polar moments of inertia obtained from the above solutions, we can obtain complete cross-sectional geometric property parameters.

[0037] In this embodiment of the invention, the target range branch section is divided into basic geometric sub-units to calculate the centroid coordinates. Then, a coordinate system is established based on the centroid to solve the principal moment of inertia. The bending center is determined by combining the thin-wall segmentation assumption, and the polar moment of inertia is calculated using the thin-film analogy method. Therefore, this method overcomes the problem of the rough calculation method of pipeline cross-section geometric and mechanical parameters in traditional testing, solves the problem of missing or large errors in key mechanical parameters, and avoids the situation where the fluid and structure coupling analysis is deviated due to inaccurate cross-section parameters. From the theoretical calculation level, it ensures the accuracy of pipeline characteristic analysis, and thus obtains the core geometric characteristic parameters of the pipeline cross-section completely and accurately.

[0038] In a preferred embodiment of the present invention, step 2 above may include: Step 2.1: Based on the obtained centroid coordinates, principal moments of inertia, bending center position, and polar moments of inertia of the cross-section, combined with the flow cross-sectional area and hydraulic diameter of the initial fluid conduction loop, calculate the friction coefficient and local resistance coefficient of the outlet pipe of the pressure reducing valve. Specifically, the test medium is high-purity nitrogen gas commonly used in semiconductor manufacturing processes, and the medium density under operating conditions is... The value is 1.165 kg / m 3 Dynamic viscosity The value is 1.789 × 10^-5 Pa. The input parameters for the calculation process include the obtained centroid coordinates of the cross section, principal moments of inertia, bending center position, polar moment of inertia, and the flow cross-sectional area of ​​the initial fluid conduction loop. The value is 54.18mm. 2 Hydraulic diameter The value is 10mm, and the pipeline uses 316L stainless steel electropolished tubing with a wall absolute roughness of [value missing]. The value is 0.002 mm, and the rated volumetric flow rate is used for testing. The value is 25 L / min.

[0039] The formula for calculating the average flow velocity of fluid in a pipeline is: ; In the formula: The average flow velocity of the fluid in the pipe. To test the rated volumetric flow rate under operating conditions, Given the cross-sectional area of ​​the pipeline, the calculated average flow velocity of the fluid inside the pipeline is 7.69 m / s.

[0040] The formula for calculating the Reynolds number of fluid flow in a pipeline is: ; In the formula: The Reynolds number is the number of fluid flowing within the pipeline. The density of the measured medium, The hydraulic diameter of the pipeline. The dynamic viscosity of the measured medium was calculated, and the Reynolds number of the flow in the pipeline was 5002, which is in the turbulent smooth pipe region.

[0041] The friction factor is calculated using the Harland equation, an explicit calculation model for the friction factor across the entire flow regime. This model requires no iteration, and the calculation results deviate from the Moody diagram by less than 1.5%, making it suitable for accurate calculation of industrial pipeline resistance. The calculation formula is as follows: ; In the formula: This is the friction factor along the pipeline. The absolute roughness of the pipe wall. The hydraulic diameter of the pipeline. The Reynolds number is the fluid flow rate within the pipeline. The calculation process incorporates the principal moment of inertia parameter of the cross-section. In this embodiment, the principal moments of inertia in the two orthogonal directions of the cross-section are equal, indicating that the pipeline cross-section is isotropic. Therefore, the friction coefficient does not require anisotropic correction for the flow direction. The calculated friction coefficient is 0.0238.

[0042] The local resistance coefficient is calculated for structural components in the pipeline where the flow cross-section changes abruptly or the flow direction changes. In this embodiment, the local components include the connection joint between the pressure reducing valve and the pipeline, two 90-degree bends, and the rectifying section at the front end of the negative pressure regulating device. The local resistance coefficient of the bends is corrected by combining the polar moment of inertia of the cross-section and the position of the bend center. The correction model considers the additional torsional loss caused by the secondary flow in the bend. The larger the polar moment of inertia of the cross-section, the higher the torsional stiffness, and the smaller the additional loss. When the bend center coincides with the centroid, there is no additional resistance loss caused by the additional torsional moment. The formula for correcting the bend resistance coefficient is: ; In the formula: This is the corrected local resistance coefficient for the bend. The basic resistance coefficient for a standard circular pipe bend of the same diameter is taken as 0.4. The polar moment of inertia of a standard circular tube of the same diameter is taken as 1811.78 mm. 4 , The polar moment of inertia of the pipeline cross-section in this embodiment is taken as 1791.25 mm. 4 After correction and calculation, the local resistance coefficient of a single bend is 0.405.

[0043] The total local resistance coefficient of a pipeline is the sum of the resistance coefficients of all local components, and the calculation formula is as follows: ; In the formula: This is the total local resistance coefficient of the pipeline. For the first k The local resistance coefficient of a local component The total number of local components is 4 in this embodiment. After calculation, the resistance coefficient of the inlet joint is 0.2, the resistance coefficient of the outlet rectifier section is 0.15, and the total local resistance coefficient of the pipeline is 1.16.

[0044] Step 2.2: Based on the resistance coefficient, the downstream negative pressure regulating device is driven to gradually reduce the pressure on the outlet side of the pressure reducing valve while maintaining a constant inlet pressure. This creates a negative pressure gradient field with gradually decreasing pressure along the flow direction at the outlet side. Multiple pressure sensing points are arranged on the outlet side of the pressure reducing valve to collect the pressure values ​​of each sensing point in real time. The pressure at each point is compared point by point with the theoretical negative pressure distribution curve to calculate the overall deviation of the current pressure field. Specifically, the inlet end of the pressure reducing valve under test is connected to a high-purity nitrogen gas source, and the inlet pressure is kept constant at 0.101325 MPa through a high-precision pressure stabilizing valve at the front end, with the pressure fluctuation range not exceeding ±0.0002 MPa throughout the process. The downstream negative pressure regulating device uses a Roots dry vacuum pump with an electric proportional regulating valve. The regulating valve has an adjustment accuracy of 0.1%FS and a response time of less than 50ms.

[0045] The theoretical distribution of the negative pressure gradient field within a pipeline is constructed based on Bernoulli's equation for horizontal pipelines. This model combines friction loss and local resistance loss to accurately calculate the theoretical pressure values ​​at various axial locations within the pipeline, thus forming a theoretical negative pressure distribution curve. The calculation formula is as follows: ; In the formula: The axial distance of the pipeline from the inlet The theoretical pressure value at the location, This refers to the pressure at the inlet of the pipeline on the outlet side of the pressure reducing valve. The density of the measured medium, The acceleration due to gravity is taken as 9.81 m / s². 2 , To calculate the axial distance between the calculation point and the pipe inlet, This is the friction factor along the pipeline. The hydraulic diameter of the pipeline. This is the sum of the local component resistance coefficients within the upstream range of the calculation point. This represents the average flow velocity of the fluid within the pipeline.

[0046] Five pressure sensing points are evenly spaced along the axial direction on the pipeline at the outlet side of the pressure reducing valve. The first sensing point is 20mm from the outlet end face of the pressure reducing valve, and the subsequent sensing points are spaced 100mm apart. The axial distances of the five sensing points are 20mm, 120mm, 220mm, 320mm, and 420mm, respectively. Each sensing point is equipped with a high-precision piezoresistive pressure sensor with a measurement range of -0.1MPa to 0.2MPa, an accuracy of 0.05%FS, and a sampling frequency of 1000Hz. The negative pressure regulating device is driven to gradually reduce the pressure at the outlet side of the pressure reducing valve. The pressure regulating step is set to 0.005MPa. After each step adjustment, the pressure is stabilized for 2 seconds, and the real-time pressure values ​​of the five sensing points are collected simultaneously. The adjustment continues until the pressure value of the fifth sensing point at the end of the pipeline reaches -0.09MPa. At this point, a negative pressure gradient field with gradually decreasing pressure along the flow direction is formed in the pipeline.

[0047] The real-time pressure value collected at each sensor point is compared point-by-point with the calculated value of the theoretical negative pressure distribution curve at the same location to calculate the overall deviation of the current pressure field. The overall deviation is calculated using the root mean square error (RMSE), which characterizes the overall degree of deviation between the actual pressure distribution and the theoretical distribution. The smaller the value, the higher the fit between the pressure field and the theoretical model. The calculation formula is: ; In the formula: The overall deviation of the current pressure field. This represents the total number of pressure sensing points, and is set to 5. For the first The average measured pressure collected from each sensor point. For the first The theoretical pressure value corresponding to each sensing point.

[0048] Step 2.3: Based on the overall deviation of the current pressure field, continuously fine-tune the opening of the negative pressure regulating device to gradually reduce the overall deviation until the deviation is lower than the preset threshold for three consecutive sampling periods. This indicates that the reference pressure field has entered a steady-state convergence state. Specifically, based on the calculated overall deviation of the current pressure field, use an incremental PID control algorithm to drive the electric proportional control valve of the negative pressure regulating device. This algorithm only outputs the valve opening increment between the current and previous moments, has no integral accumulation error, and the adjustment process is smooth without overshoot. It is suitable for fine closed-loop control of the negative pressure field. The proportional coefficient of the adjustment algorithm... The value is 1.2, and the integral coefficient is... The value is 0.3, and the differential coefficient is... The value is 0.1, and the minimum increment for opening adjustment is 0.05%.

[0049] After each fine-tuning of the opening, wait 1 second and then re-collect full pressure data from 5 pressure sensor points. Take the average of 1000 samples from each sensor point and calculate the updated overall deviation. Continue fine-tuning to gradually reduce the overall deviation. The preset deviation convergence threshold is 0.5%, and the sampling period is set to 1 second. When the calculated overall deviation is lower than the preset convergence threshold for three consecutive sampling periods, stop the adjustment operation, lock the current opening of the negative pressure regulating device, and determine that the reference pressure field on the outlet side of the pressure reducing valve has entered a steady-state convergence state.

[0050] In this embodiment of the invention, the pipeline resistance coefficient is calculated by combining cross-sectional geometric characteristic parameters and loop flow parameters. Then, based on the resistance coefficient, the downstream negative pressure regulating device is driven to construct a negative pressure gradient field on the outlet side. At the same time, the deviation is compared by collecting pressure at multiple points and the opening of the device is finely adjusted in a closed loop until the continuous sampling period reaches the standard to determine steady-state convergence. Therefore, this method overcomes the problem of inaccurate pipeline resistance calculation in traditional pressure reducing valve testing, solves the defects of difficulty in constructing a stable negative pressure environment on the outlet side and large deviations between the pressure distribution and theoretical values, and avoids the situation of data distortion caused by conducting tests before the negative pressure field reaches a steady state. It also avoids the problem of not being able to provide a stable benchmark for transient response testing. In this way, the pipeline friction and local resistance parameters are accurately obtained, and a uniform, controllable and stable convergent negative pressure benchmark pressure field is formed on the outlet side of the pressure reducing valve, ensuring the consistency of the negative pressure test environment.

[0051] In a preferred embodiment of the present invention, step 3 above may include: Step 3.1: Based on the obtained outlet-side pressure distribution data and negative pressure gradient value under steady-state convergence, confirm that the pressure fluctuation amplitude and gradient change rate at each point in the current reference pressure field are below the preset threshold conditions, and record this moment as the zero-time reference for transient excitation. Specifically, the calculation process input parameters are the pressure distribution data and pipeline axial negative pressure gradient value of the five pressure sensing points on the outlet side under steady-state convergence. The preset pressure fluctuation amplitude threshold is ±0.0003MPa, and the preset pressure gradient change rate threshold is 0.0002MPa / m. Statistically calculate the pressure fluctuation amplitude of each pressure sensing point within 1000 consecutive sampling periods. Based on the pressure difference and axial distance between two adjacent sensing points, calculate the pipeline axial pressure gradient change rate using the following formula: ; In the formula: This represents the rate of change of the pressure gradient between adjacent sensing points. This represents the average pressure value at the (j+1)th downstream sensing point. Let j be the average pressure value at the j-th upstream sensing point. The axial distance between the (j+1)th and jth sensing points is set to 100mm. When the pressure fluctuation amplitude of all sensing points is lower than the preset threshold and the absolute value of the pressure gradient change rate of all adjacent segments is lower than the preset threshold, the reference pressure field is determined to meet the pre-steady-state requirements of transient excitation. The system timestamp at this moment is recorded as the zero-time reference of transient excitation.

[0052] Step 3.2: Based on the zero-time reference, apply a predetermined timing drive signal to the fast-switching valve located upstream of the pressure reducing valve, causing the valve to instantly switch from a fully open state to a preset partially closed state. A transient pressure excitation wave with a known amplitude and steep rise edge, starting from the zero-time reference, is superimposed on the surface of the stabilized reference pressure field. The peak pressure and rise time of the transient pressure excitation wave are recorded. Specifically, the fast-switching valve located upstream of the pressure reducing valve is a high-speed pneumatic ball valve with a valve diameter consistent with the inner diameter of the target range branch pipeline (10mm). The flow resistance coefficient in the fully open state is ≤0.08, and the switching response time from fully open to the preset opening degree is ≤2ms. Starting from the zero-time reference, apply a predetermined timing step drive signal to the electromagnetic drive unit of the fast-switching valve. The drive signal is a 24V DC step voltage with a rise edge ≤100μs and a high-level duration of 500ms, driving the valve to instantly switch from a fully open state to a preset 30% partially closed state.

[0053] During the rapid valve closure process, the kinetic energy of the fluid in the upstream pipeline is rapidly converted into pressure energy, superimposed on the surface of the stabilized reference pressure field to form a transient pressure excitation wave starting from time zero. A high-frequency dynamic pressure sensor is installed at the midpoint of the pipeline between the rapid switching valve and the pressure reducing valve. The sensor has a measurement range of -0.1 MPa to 0.6 MPa, a natural frequency ≥200 kHz, and a sampling frequency of 100 kHz, acquiring the time-domain pressure data of the excitation wave in real time. The peak pressure and rise time of the transient pressure excitation wave are recorded. The rise time is defined as the time interval during which the excitation wave pressure rises from 10% of the steady-state reference value to 90% of the peak pressure. In this embodiment, the peak pressure of the transient pressure excitation wave is 0.15 MPa, and the rise time is 4.2 ms, meeting the excitation requirement of a steep rise edge.

[0054] Step 3.3 involves combining the peak pressure and rise time of the transient pressure excitation wave with the principal moment of inertia and polar moment of inertia from the cross-sectional geometric parameters, as well as the elastic wave velocity calculation formula of the pipeline, to quantify the velocity of the excitation wave propagating in the forward direction along the pipeline, the reflection coefficient at the abrupt change in the cross-section, and the attenuation factor after multiple reflections. This yields a set of pressure wave propagation characteristic parameters, specifically including: the input parameters for the calculation process include the peak pressure and rise time of the transient pressure excitation wave, and the principal moment of inertia of the cross-section obtained in Step 1 (910.99 mm). 4 Polar moment of inertia: 1791.25 mm 4 The pipe has an elastic modulus of 1.95 × 10^11 Pa, a Poisson's ratio of 0.29, and a medium density of 1.165 kg / m³. 3 Dynamic viscosity 1.789×10^-5 Pa s.

[0055] First, the elastic propagation velocity of the fluid pressure wave in the pipeline is calculated using a modified transient wave velocity model for thin-walled pipelines. This model, based on the classical wave velocity formula, introduces correction terms for the principal moment of inertia and polar moment of inertia of the cross section, and considers the influence of the pipeline's bending stiffness and torsional stiffness on the wave propagation characteristics. The modified wave velocity calculation formula is as follows: ; In the formula: The elastic propagation velocity of the pressure wave within the pipeline. The isothermal bulk modulus of the measured medium is taken as 0.101325 MPa under low-pressure conditions with high-purity nitrogen. The density of the measured medium, The hydraulic diameter of the pipeline. The elastic modulus of the pipe is given by [reference]. For the pipe wall thickness, a value of 1.5mm is used. The polar moment of inertia of the pipe cross section, The principal moment of inertia of the pipeline cross section, Based on the calculated Poisson's ratio of the pipe, the elastic propagation velocity of the pressure wave inside the pipe is 342.6 m / s.

[0056] The reflection coefficient of the pressure wave at the point of abrupt change in cross-section is calculated using a reflection coefficient calculation model based on the characteristic impedance matching of the pipeline. This model is a classic model for transient analysis of fluid pipelines and is used to quantify the proportion of reflected energy of the pressure wave at the interface of impedance change. The calculation formula is as follows: ; In the formula: The pressure wave reflection coefficient at the point of abrupt change in cross-section. The characteristic impedance of the upstream pipeline, This is the characteristic impedance of the downstream abrupt cross section.

[0057] The formula for calculating the characteristic impedance of a pipeline is: ; In the formula: The characteristic impedance of the corresponding pipeline section In this embodiment, the location of the abrupt change in cross-sectional area is the interface between the pressure reducing valve core and the pipeline. The calculated pressure wave reflection coefficient at this location is 0.28.

[0058] Next, calculate the attenuation factor after multiple reflections of the pressure wave. The attenuation factor takes into account the friction loss, viscoelastic dissipation of the pipe wall, and energy loss during the reflection process. Combined with the friction coefficient and the correction for the polar moment of inertia of the cross section, the calculation formula is as follows: ; In the formula: The attenuation factor per unit length of the pressure wave. The friction factor along the pipeline is 0.0238μ, which is the dynamic viscosity of the measured medium.

[0059] The formula for calculating the total attenuation factor after n reflections of a pressure wave is: ; In the formula: The total attenuation factor after multiple reflections. This represents the total path length of a pressure wave during a single round trip. The number of reflections of the pressure wave was calculated, and the attenuation factor of the pressure wave for a single round trip was 0.942, while the total attenuation factor after 3 reflections was 0.835.

[0060] The pressure wave propagation velocity, reflection coefficient at abrupt changes in cross section, and attenuation factor obtained from the above calculations are integrated and archived to form a set of pressure wave propagation characteristic parameters.

[0061] Step 3.4: Based on the set of pressure wave propagation characteristic parameters, the arrival time and pressure amplitude of the excitation wave reaching the front and rear ends of the pressure reducing valve core are discretized along the pipeline axis to obtain the transient fluid dynamic pressure difference sequence. Specifically, this includes: using the method of characteristics to discretize the pipeline axis based on the set of pressure wave propagation characteristic parameters. The method of characteristics is a classical numerical solution method for the transient control equations of fluids, transforming the hyperbolic partial differential control equations into ordinary differential equations propagating along characteristic lines, which can solve the propagation process of the transient pressure wave along the pipeline. The axial discretization step size of the pipeline is set to 10 mm, consistent with the hydraulic diameter of the pipeline, and the discretization time step size is set to 10 μs to satisfy the Coulomb stability condition.

[0062] The axial distance between the front end faces of the quick-switching valve and the pressure reducing valve core is 1.2m, discretized into 120 computational nodes; the axial distance between the rear end face of the pressure reducing valve core and the first pressure sensing point on the outlet side is 20mm, discretized into 2 computational nodes. Based on the pressure wave propagation velocity, the pressure amplitude of each node at each discrete time step is recursively calculated, resulting in time-domain pressure sequences for the front and rear ends of the valve core.

[0063] The transient hydrodynamic pressure difference between the front and rear ends of the valve core is the difference between the pressure on the front end and the pressure on the rear end at the same moment, and the calculation formula is: ; In the formula: For the first The transient fluid dynamic pressure difference corresponding to each time step For the first The pressure value at the front end of the valve core at each time step. For the first Pressure value at the rear end face of the valve core at each time step For the first The transient fluid dynamic pressure difference sequence with a time length of 500ms and a time step of 10μs is obtained by recursive calculation of the time corresponding to each discrete time step.

[0064] Step 3.5: The transient fluid dynamic pressure difference sequence is used as the external load input and coupled with the inertial force determined by the mass distribution of the valve core and the spring preload to obtain the kinematic displacement response that changes with time. Specifically, the transient fluid dynamic pressure difference sequence is used as the external load input to establish a single-degree-of-freedom forced vibration coupled dynamic model of the axial motion of the valve core. This model simplifies the axial translation of the valve core into a concentrated mass-spring-damping system, accurately coupling the fluid dynamic pressure load and the inertial force of the valve core structure. It is suitable for solving the transient motion response of the pressure reducing valve core.

[0065] The model input parameters include the mass of the valve core itself. The value is 0.08 kg, and the spring stiffness is... The value is 1200 N / m, and the spring preload is... The value is 30N, and the effective pressure-bearing area of ​​the valve core is... The value is 50.27mm. 2 System viscous damping coefficient Value 5N s / m. The coupled dynamic control equation for the axial motion of the valve core is: ; In the formula: This represents the axial kinematic displacement of the valve core as a function of time. For time variables, The axial acceleration of the valve core. To determine the axial velocity of the valve core, the fourth-order Runge-Kutta method was used to numerically solve the dynamic control equations. The solution time step was consistent with the time step of the transient fluid dynamic pressure difference sequence, set to 10 μs. During the solution process, the fluid dynamic pressure load at each time step was updated synchronously, achieving real-time coupled solution of fluid load and structural motion. The numerical solution yielded the axial kinematic displacement response curve of the valve core, continuously varying with time from 0 to 500 ms, along with the corresponding velocity and acceleration response data.

[0066] In this embodiment of the invention, the steady-state negative pressure field is first confirmed to meet the standard, and the zero-time reference of the transient excitation is locked. Then, a standard pressure excitation wave with a clear amplitude and steep rise edge is generated by rapidly switching valves. The various characteristic parameters of the pressure wave propagation are quantified by combining the cross-sectional geometric characteristics. Then, the transient fluid dynamic pressure difference between the front and rear ends of the valve core is calculated. Finally, the kinematic displacement response of the valve core is obtained by solving the coupled dynamics. Therefore, this method overcomes the problem of the lack of a unified reference for transient excitation in traditional testing, solves the defect that the amplitude and rise edge of the pressure excitation cannot be accurately controlled, and avoids the situation that the propagation law of pressure wave is difficult to quantify and the dynamic response of the valve core cannot be accurately solved. The accuracy is improved in the entire process from excitation generation to response modeling. In this way, a standard transient pressure excitation with high repeatability and clear boundaries is generated, the propagation and attenuation characteristics of the pressure wave in the pipeline are fully quantified, and the true transient fluid dynamic pressure difference and dynamic displacement response of the valve core are accurately obtained.

[0067] In a preferred embodiment of the present invention, step 4 above may include: Step 4.1: Obtain the kinematic displacement response curve. Extract the starting time of the valve core displacement's first departure from the initial equilibrium position, the time of the displacement peak, and the time window for its return to the vicinity of the equilibrium position from the kinematic displacement response curve to obtain the trigger time reference. Specifically, the input parameters for the calculation process are the solved axial kinematic displacement response curve of the valve core, with a curve time coverage range of 0 to 500 ms, a discrete time step of 10 μs, and the initial equilibrium position of the valve core under the steady-state convergence reference pressure field. The value is 0mm.

[0068] The fluctuation range of the valve core's steady-state displacement within 100ms before the zero-time reference is calculated using the following formula: ; In the formula: This represents the fluctuation amplitude of the steady-state displacement of the valve core. This represents the maximum value of the valve core displacement within 100ms before time zero. The minimum value of the valve core displacement within 100ms before time zero is calculated. The steady-state displacement fluctuation amplitude of the valve core is 0.0015mm. The threshold for determining whether the displacement deviates from the initial equilibrium position is set to ±0.002mm. This threshold is greater than the steady-state fluctuation amplitude, which can avoid false triggering caused by steady-state vibration.

[0069] Traverse the full time step data of the displacement response curve, extract the moment when the absolute value of the valve core displacement first exceeds the judgment threshold, and record it as the displacement start moment. In this embodiment The value is 1.2ms.

[0070] By traversing the entire time range of the displacement response curve, the moment corresponding to the maximum absolute value of the displacement is determined and denoted as the moment of displacement peak occurrence. In this embodiment A value of 28.6 ms corresponds to a peak displacement of 0.12 mm. The threshold for determining if the valve core returns to its equilibrium position is set to ±0.005 mm, and the displacement response curves are iterated through. For all subsequent data, the first moment in which the valve core displacement remains within the judgment threshold for 10 consecutive ms is extracted and recorded as the recovery stabilization moment. In this embodiment The value is 220.4ms. , , As the core node, determine the time range for complete coverage of transient response, and form the trigger time benchmark for data acquisition.

[0071] Step 4.2: Based on the trigger time reference, activate the inlet pressure sensor and the outlet pressure sensor, and synchronously acquire the inlet time-domain pressure sequence and the outlet time-domain pressure sequence from the preset buffer period before the start time to the buffer period after the recovery time at a sampling frequency higher than twice the highest frequency component of the kinematic displacement response. Specifically, this includes: performing a fast Fourier transform on the valve core kinematic displacement response curve based on the trigger time reference to obtain the amplitude-frequency characteristic curve of the displacement response signal, and extracting the lowest frequency where the signal amplitude decays to below 0.1% of the peak amplitude as the highest effective frequency component of the displacement response. In this embodiment The sampling frequency is set to 1.2kHz. Data acquisition employs the Nyquist sampling theorem, a fundamental principle of digital signal acquisition. This theorem stipulates that the sampling frequency must be higher than twice the highest effective frequency component of the measured signal to avoid frequency aliasing distortion during sampling and to fully reproduce the time-domain characteristics of the measured signal. Based on this theorem, the sampling frequency... Must meet In this embodiment, the sampling frequency is set. At 20kHz, far exceeding the minimum sampling frequency of 2.4kHz required by the theorem, it can fully capture the high-frequency details of the transient response.

[0072] The preset data acquisition buffer period is 50ms. This buffer period can fully cover the steady-state reference data before the transient excitation is triggered, as well as the decay process data after the response stabilizes, avoiding the truncation of effective signals. The starting point of the data acquisition time window is... The end point of the time window is The complete time window length is 320.4ms.

[0073] Both the inlet and outlet pressure sensors are high-precision piezoresistive dynamic pressure sensors with a measurement range of -0.1MPa to 0.6MPa, a measurement accuracy of 0.05%FS, and a natural frequency ≥200kHz. All sensors share the same hardware synchronization clock system with a clock synchronization accuracy ≤1μs, completely eliminating time deviations in multi-sensor sampling. Using the trigger time reference as the synchronization trigger source, all pressure sensors are synchronously activated at the start of the time window, continuously acquiring data at a sampling frequency of 20kHz to obtain the inlet time-domain pressure sequence. With export time-domain pressure sequence Both sequences had 6408 sampling points, which perfectly matched the time window.

[0074] Step 4.3: Simultaneously start the inlet and outlet flow meters, using the same sampling frequency to synchronously acquire the inlet instantaneous flow rate sequence and outlet instantaneous flow rate sequence within the same time window. Align the four sequences along the time axis to form a multidimensional raw dynamic response dataset indexed by time. Specifically, both the inlet and outlet flow meters are high-frequency thermal response mass flow meters with a measurement range of 0 to 100 L / min, a measurement accuracy of 0.2%FS, and a step response time ≤1 ms. They are connected to the same hardware synchronization clock system as the pressure sensor to ensure complete consistency between sampling triggering and sampling frequency. At the same moment the pressure sensor is activated, the inlet and outlet flow meters are started in parallel, continuously acquiring data within the same time window at a sampling frequency of 20 kHz to obtain the inlet instantaneous flow rate sequence. With the instantaneous flow sequence of the outlet Both sequences had 6408 sampling points, which perfectly matched the pressure sequence.

[0075] Each sampled data point of all acquisition sequences is bound to a unique timestamp output by the synchronous clock system. The timestamp accuracy is 0.1μs. With the zero time reference as the time zero point, all timestamps of the four sequences are uniformly converted into relative time relative to the zero point. Abnormal sampling points with a timetamp deviation of more than 1μs from the theoretical sampling time are removed to ensure that the sampling points of the four sequences correspond one-to-one on the time axis. Using the converted relative time as the unique index, the inlet pressure, outlet pressure, inlet flow rate, and outlet flow rate data corresponding to the same relative time are combined into an independent data unit. All data units are arranged in ascending order of time to form a complete multidimensional original dynamic response dataset.

[0076] Step 4.4 involves performing point-by-point deviation verification on the pressure and flow sequences in the multidimensional original dynamic response dataset and the transient fluid dynamic pressure difference sequence, removing obvious outliers caused by sensor noise, and then linearly interpolating the normal values ​​before and after the outlier to obtain the cleaned original dynamic response dataset. Specifically, the input parameters of the multidimensional original dynamic response dataset include the inlet time-domain pressure sequence, the outlet time-domain pressure sequence, the inlet instantaneous flow sequence, the outlet instantaneous flow sequence, and the synchronously input transient fluid dynamic pressure difference sequence. Point-by-point deviation verification is performed on the pressure sequence. At the same time, the measured inlet and outlet pressure differences are used to calculate the relative deviation between the measured pressure difference and the transient fluid dynamic pressure difference at the same sampling time. A relative deviation threshold of 15% is set for outlier detection. When the relative deviation at a certain sampling time exceeds this threshold, the pressure and flow data at that time are determined to be outliers affected by sensor noise and electromagnetic interference, and are removed. For the missing data points left after removing outliers, linear interpolation is used to fill them. Linear interpolation is a classic method for completing discrete data gaps. Based on the values ​​and time intervals of two adjacent normal data points, the filling value at the missing position is calculated in a linear proportion, which can preserve the temporal continuity of the data to the greatest extent. The formula for calculating the filling value is: ; In the formula: This is the fill value for the missing positions. This represents the value of the nearest normal data point before the missing position. The value is the nearest normal data point after the missing position. This represents the relative time corresponding to the preceding normal data points. This represents the relative time corresponding to subsequent normal data points. After eliminating and filling all outliers, the relative time corresponding to the missing positions is used to perform secondary time axis alignment on the sampling points of the four sequences to ensure that the time indices of all data points are continuous and correspond one-to-one, and finally the cleaned original dynamic response dataset is obtained.

[0077] In this embodiment of the invention, key time nodes are extracted based on the valve core displacement response curve to determine the acquisition trigger benchmark. Inlet and outlet pressure and flow data are collected synchronously at a high-frequency sampling rate. Multiple types of data are aligned along the time axis to form a multidimensional dataset. Then, noise outliers are removed through deviation verification and linear interpolation is performed to fill the gaps. Therefore, this method overcomes the problem of inaccurate trigger timing in traditional acquisition methods, solves the defect of insufficient sampling frequency in capturing transient details, and avoids the situation of data asynchrony between multiple sensors and noise interference causing distortion of the original data. The acquisition process is improved from four aspects: acquisition timing, sampling accuracy, data synchronization, and data quality. This allows for precise locking of the complete transient response time window, complete capture of all subtle changes in the transient process of the pressure reducing valve, and high temporal synchronization of pressure and flow data. This results in a clean and well-organized original dynamic response dataset, effectively improving the integrity and accuracy of the data.

[0078] In a preferred embodiment of the present invention, step 5 above may include: Step 5.1: Obtain the original dynamic response dataset. Simultaneously, read the principal moment of inertia and bending center position from the cross-sectional geometric characteristic parameters, as well as the rated pressure level and flow capacity of the target range branch, as range adaptation parameters. Specifically, the input parameters for the calculation process are the cleaned original dynamic response dataset, which includes the inlet time-domain pressure sequence, outlet time-domain pressure sequence, inlet instantaneous flow rate sequence, and outlet instantaneous flow rate sequence. The sequence sampling frequency is 20kHz, the number of sampling points per sequence is 6408, and the time coverage range is -48.8ms to 271.6ms. Simultaneously, read the obtained cross-sectional geometric characteristic parameters, where the principal moment of inertia of the cross-section is 910.99mm. 4 The bending center of the cross section coincides with the centroid, and the coordinate system is the origin of the centroid coordinate system. The rated pressure level of the target range branch is read as -0.1MPa to 0.6MPa, and the flow capacity is read as 0.001L / min to 100L / min. The above rated pressure level and flow capacity are used as range adaptation parameters to complete the pre-loading and archiving of data and parameters.

[0079] Step 5.2: Based on the sensor accuracy level and range adaptation parameters, determine the noise floor level of each pressure and flow sequence. Using an adaptive filter width associated with the polar moment of inertia in the cross-sectional geometric characteristic parameters, perform wavelet threshold denoising on the inlet time-domain pressure sequence, outlet time-domain pressure sequence, inlet instantaneous flow sequence, and outlet instantaneous flow sequence in the original dynamic response dataset to obtain the denoised dynamic response sequence. Specifically, in this embodiment, the accuracy level of the inlet and outlet pressure sensors is 0.05%FS, the measurement range is -0.1MPa to 0.6MPa, and the full-scale span is 0.7MPa. The accuracy level of the inlet and outlet flow meters is 0.2%FS, the measurement range is 0L / min to 100L / min, and the full-scale span is 100L / min. Based on the sensor accuracy level and range adaptation parameters, determine the noise floor level of each sequence. The noise floor is the maximum inherent noise amplitude of the sensor under rated operating conditions, calculated using the following formula: ; In the formula: The noise floor amplitude of the pressure sequence. This represents the full-scale span of the pressure sensor. For the accuracy class of the pressure sensor, The noise floor amplitude of the flow sequence. The full-scale span of the flow meter. Based on the accuracy class of the flow meter, the calculated noise floor amplitude for the pressure sequence is 0.00035 MPa, and the noise floor amplitude for the flow sequence is 0.2 L / min.

[0080] An adaptive filter width associated with the polar moment of inertia of the cross section is adopted. The correction model for the filter width considers the influence of the torsional stiffness of the cross section on the propagation characteristics of the high-frequency components of the pressure wave. The larger the polar moment of inertia, the higher the torsional stiffness of the cross section, the smaller the attenuation amplitude of the effective high-frequency components of the pressure wave, and the wider the required filter width. Conversely, the filter width is narrowed to avoid excessive filtering of the effective signal. The formula for calculating the adaptive filter width is: ; In the formula: For adaptive filtering window width, The basic filter window width is set to the standard diameter circular tube, with 5 sampling points. The polar moment of inertia of the pipeline cross-section in this embodiment is taken as 1791.25 mm. 4 , The polar moment of inertia of a standard circular tube of the same diameter is taken as 1811.78 mm. 4 The calculated adaptive filtering window width is 4.94 sampling points, which is rounded down to 5 sampling points.

[0081] Wavelet thresholding denoising was performed on the four sequences in the original dynamic response dataset. The db4 wavelet basis function was used for denoising. This wavelet basis function has compact support and orthogonality, making it suitable for denoising transient non-stationary signals. It can effectively filter out Gaussian white noise while preserving the transient change characteristics of the signal. The wavelet decomposition level was set to 5 levels. A soft thresholding function was used to threshold the high-frequency coefficients of each decomposition level. The soft thresholding function can avoid the signal oscillation distortion caused by the hard thresholding function. The threshold calculation is based on the sequence noise basis and the adaptive filter width. After processing, the wavelet coefficients were reconstructed to obtain the denoised dynamic response sequence.

[0082] Step 5.3: Perform difference calculation on the denoised inlet and outlet pressure sequences to obtain the transient pressure difference change curve. At the same time, perform difference calculation on the inlet and outlet flow sequences to obtain the transient flow rate change curve. Perform cross-correlation analysis on the two curves and the transient fluid dynamic pressure difference sequence to extract the time delay, peak ratio, and decay rate as primary characteristic parameters of the transient response. Specifically, this includes: performing point-by-point difference calculation on the denoised inlet pressure sequence and the outlet pressure sequence to obtain the transient pressure difference change curve. The denoised transient pressure difference at each sampling time is equal to the denoised inlet pressure value minus the denoised outlet pressure value at that sampling time.

[0083] The transient flow rate change curve is obtained by performing point-by-point difference calculation between the noise-reduced inlet flow rate sequence and the outlet flow rate sequence. The noise-reduced transient flow rate difference at each sampling time is equal to the noise-reduced inlet flow rate value minus the noise-reduced outlet flow rate value at that sampling time.

[0084] Cross-correlation analysis is performed between the transient pressure difference change curve and the obtained transient hydrodynamic pressure difference sequence. Cross-correlation analysis is a classic analysis model in the field of digital signal processing, used to quantify the linear correlation between two time-domain sequences and simultaneously solve for the time offset between the two sequences. The formula for calculating the cross-correlation function is as follows: ; Let be the cross-correlation function value of the two sequences. This represents the time offset between the two sequences. This represents the total number of sampling points in the sequence. Time offset The subsequent transient hydrodynamic pressure difference sequence.

[0085] Based on the cross-correlation analysis results and the time-domain characteristics of the two change curves, primary characteristic parameters of the transient response are extracted. The time delay is the time offset corresponding to the peak value of the cross-correlation function; in this embodiment, it is taken as 1.1 milliseconds. The peak-to-peak ratio is the ratio of the peak value of the transient pressure difference change curve to the peak value of the transient hydrodynamic pressure difference sequence; in this embodiment, it is taken as 0.972. The decay rate is the time constant required for the transient pressure difference to decay from the peak value to 10% of the peak value; in this embodiment, it is taken as 32.4 milliseconds. These three parameters are integrated and archived to form the primary characteristic parameters of the transient response.

[0086] Step 5.4: Based on the primary characteristic parameters, combined with the obtained centroid coordinates and principal moments of inertia of the cross section, a coupled analytical method of axial tensile and compressive stress and bending normal stress is used to calculate the equivalent dynamic stiffness and damping ratio of the pressure reducing valve core during the transient response process, thus obtaining the second-order transient characteristic parameters. Specifically, based on the primary characteristic parameters, combined with the obtained centroid coordinates and principal moments of inertia of the cross section, a coupled analytical method of axial tensile and compressive stress and bending normal stress is used to calculate the equivalent dynamic stiffness and damping ratio of the pressure reducing valve core during the transient response process. This coupled analytical method simultaneously considers the axial tensile and compressive stress of the fluid generated by the axial movement of the valve core, as well as the bending normal stress of the pipeline generated by the transient pressure impact. The coupling effect of the pipeline bending stiffness on the dynamic characteristics of the valve core is quantified by the principal moments of inertia of the cross section. The larger the principal moments of inertia of the cross section, the higher the pipeline bending stiffness, the stronger the constraint on the axial movement of the valve core, and the larger the equivalent dynamic stiffness, which can accurately restore the true dynamic characteristics of the valve core under transient conditions. The standard transfer model of the second-order system for the axial motion of the valve core is adopted. This model is a classic model in structural dynamics for describing single-degree-of-freedom forced vibration, and it can accurately characterize the dynamic response characteristics of the axial motion of the valve core. The model includes two core parameters of the valve core system: natural angular frequency and equivalent damping ratio. The equivalent dynamic stiffness is calculated by combining the principal moment of inertia correction of the cross section as follows: ; in, The equivalent dynamic stiffness of the valve core system. For the valve core return spring stiffness, The elastic modulus of the pipe is given by [reference]. Principal Moment of Inertia of Pipe Section The axial distance from the valve seat to the first fixed support point of the pipeline is used to calculate the equivalent damping ratio based on the attenuation rate and peak ratio in the primary characteristic parameters, combined with the attenuation characteristics of the transient response of the second-order system. The calculation method for the equivalent damping ratio is as follows: ; in, The equivalent damping ratio of the valve core system. The ratio of the attenuation of adjacent peak values ​​of transient pressure difference. Pi is the mathematical constant of a circle.

[0087] Step 5.5 involves normalizing the second-order transient characteristic parameters and the range adaptation parameters of the target range branch to obtain standardized data acquisition results. Specifically, this includes normalizing the second-order transient characteristic parameters and the range adaptation parameters of the target range branch, mapping characteristic parameters of different ranges and dimensions to a unified numerical range of 0 to 1. This eliminates the incomparability of parameters caused by range differences and meets the requirements for lateral comparison of cross-range test results. The normalized equivalent dynamic stiffness is calculated as follows: ; in, The original equivalent dynamic stiffness, The normalized equivalent dynamic stiffness, The minimum equivalent dynamic stiffness adapted to the target range branch. The maximum equivalent dynamic stiffness adapted to the target range branch.

[0088] The normalized equivalent damping ratio is calculated as follows: ; in, This is the original equivalent damping ratio. The normalized equivalent damping ratio, This represents the maximum damping ratio boundary of the pressure reducing valve's dynamic characteristics. To obtain the normalized equivalent damping ratio, the normalized second-order transient characteristic parameters are integrated and archived with the primary characteristic parameters and the denoised dynamic response sequence to obtain complete standardized data acquisition results.

[0089] In this embodiment of the invention, a noise floor is determined by combining the cross-sectional geometric characteristics and range adaptation parameters of the original dynamic response dataset. Adaptive wavelet thresholding with correlated polar moments of inertia is used to denoise the data. Primary transient features are extracted through difference calculations and cross-correlation analysis. Second-order features are then obtained by coupling analytical valve core dynamic stiffness and damping ratio, and normalized. This approach overcomes the problems of poor adaptability and incomplete noise suppression in traditional data denoising methods, solves the defects of one-sided transient feature extraction and large dynamic mechanical parameter calculation errors, and avoids the situation where test results lack a unified standard and cannot be compared across scenarios. The entire process from data processing and feature calculation to result standardization optimizes the analysis logic, thereby accurately filtering out test noise and retaining the true transient signal. It fully extracts multi-dimensional feature parameters of the pressure reducing valve's transient response, accurately calculates core mechanical indicators such as valve core dynamic stiffness and damping ratio, and finally outputs normalized standardized acquisition results, improving data processing accuracy and feature calculation reliability, and ensuring that test results have a unified standard.

[0090] like Figure 2 As shown, embodiments of the present invention also provide a transient response data acquisition system for a pressure reducing valve based on multi-range adaptive switching, comprising: The calculation module is used to obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, it adaptively matches and switches from multiple parallel test channels to the target range branch to construct the initial fluid conduction loop. It performs analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. The monitoring module is used to establish a reference pressure field with a stable negative pressure gradient on the outlet side of the pressure reducing valve based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, and to monitor the steady-state convergence state of the reference pressure field in real time. The switching module is used to apply transient pressure excitation to the surface of the reference pressure field by the flow resistance step change caused by valve switching when the steady-state convergence state meets the preset threshold condition. It also quantifies the propagation and reflection characteristics of the pressure wave during the excitation process according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. The acquisition module is used to respond to the propagation of pressure waves and transient flow of medium in the pipeline caused by kinematic displacement response, and simultaneously acquire the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve to obtain the original dynamic response dataset. The processing module is used to perform signal noise reduction processing and transient characteristic parameter calculation based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

[0091] It should be noted that this system is a system corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0092] Embodiments of the present invention also provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0093] Embodiments of the present invention also provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method described above. All implementations in the above method embodiments are applicable to this embodiment and can achieve the same technical effects.

[0094] Experimental example: Test object and preset working conditions Pressure reducing valve under test: High-precision pressure reducing valve for semiconductor manufacturing processes.

[0095] Test medium: high-purity nitrogen.

[0096] Preset test parameters: Pressure threshold: lower limit -0.095MPa, upper limit +0.3MPa.

[0097] Flow rate range: 0.005L / min~50L / min.

[0098] Rated test flow rate: 25L / min.

[0099] Step 1, Multi-range adaptive switching, loop construction, and cross-sectional characteristic analysis: The testing system has three built-in parallel testing branches with the following range specifications: Branch 1, rated pressure -0.1~0.6MPa, flow capacity 0.001~100L / min; Branch 2, rated pressure -0.1~0.2MPa, flow capacity 0.001~10L / min; Branch 3, rated pressure 0~0.8MPa, flow capacity 1~200L / min.

[0100] The preset operating parameters were automatically compared with the flow range of each branch. Calculations showed that only branch 1 could simultaneously cover the pressure threshold and flow range. The pneumatic valve was then controlled to switch the fluid path to branch 1, while the other branches were closed. Once the pressure and flow rate in branch 1 stabilized within the deviation range, the branch parameters were recorded: circular pipe, inner diameter 10mm, wall thickness 1.5mm, material 316L stainless steel. This established the initial fluid conduction loop. The geometric and mechanical properties of the pipe cross-section of branch 1 were analyzed. The circular annular cross-section was divided into 36 sector sub-elements for calculation, yielding the following cross-sectional geometric property parameters: Centroid coordinates coincide with geometric center, principal moment of inertia I x =I y =910.99mm 4 The coincidence of the bending center and the centroid, and the polar moment of inertia I t =1791.25mm 4 .

[0101] Step 2, Establishment and monitoring of the stable negative pressure gradient reference pressure field: Based on the cross-sectional parameters and loop information obtained in step 1, the friction coefficient and local resistance coefficient of the pipeline are calculated. While maintaining a constant inlet pressure of 0.101325 MPa at the pressure reducing valve inlet, the downstream Roots vacuum pump and proportional valve are started to gradually reduce the outlet pressure. Five high-precision pressure sensors are evenly spaced on the pipeline downstream of the pressure reducing valve outlet. The pressure at these five points is collected in real time and compared with the theoretical negative pressure distribution curve calculated based on Bernoulli's equation and the resistance coefficient. The opening of the proportional valve is fine-tuned using an incremental PID algorithm to continuously approximate the theoretical pressure distribution curve.

[0102] Figure 3 The results show that after multiple iterations of adjustment, the measured pressure values ​​of the five sensors are in high agreement with the theoretical negative pressure distribution curve, forming a gradient field in which the pressure decreases steadily along the flow direction. Figure 4 The diagram shows the process by which the overall deviation of the pressure field decreases over time and eventually converges during the entire adjustment process. When the deviation is lower than the preset threshold for three consecutive sampling periods, the reference pressure field is determined to have entered a steady-state convergence state, at which point the pressure fluctuation amplitude at each point is < ±0.0003 MPa.

[0103] Step 3, Solving for the transient pressure excitation and valve core motion response: After confirming the stability of the reference pressure field, the system locks this state as the zero-time reference for transient excitation. At zero time, a drive signal is sent to the high-speed pneumatic ball valve upstream of the pressure reducing valve, causing it to instantaneously switch from a fully open state to a 30% opening. This operation excites a transient pressure excitation wave with an amplitude of 0.15 MPa and a rise time of 4.2 ms in the stable flow field. Based on the parameters of this excitation wave, the pipe material properties, and the polar moment of inertia of the cross section obtained in step 1, the propagation characteristics of the pressure wave are quantified: wave velocity 342.6 m / s, reflection coefficient at the valve core 0.28. The pressure wave transmitted to the front and rear ends of the valve core is obtained by discretization calculation using the method of characteristics. Then, the transient fluid dynamic pressure difference sequence acting on the valve core is obtained. Using this dynamic pressure difference sequence as input, combined with parameters such as valve core mass and spring stiffness, the kinematic displacement response curve of the valve core is obtained through numerical solution using a coupled dynamic model. The curve shows that the valve core begins to move about 1.2 ms after excitation and reaches a maximum displacement of 0.12 mm at 28.6 ms.

[0104] Step 4, High-frequency synchronous data acquisition based on response triggering: Based on the obtained valve core displacement response curve, the system determined the data acquisition time window: from 50ms before the displacement start to 50ms after the recovery and stabilization, with a total duration of approximately 320.4ms. Within this time window, the system synchronously triggered the inlet and outlet pressure sensors and thermal mass flow meters at a sampling frequency of 20kHz. All sensors shared the same synchronization clock, ensuring data time consistency. Ultimately, four sets of perfectly time-aligned sequences were acquired, forming the original dynamic response dataset. This dataset was compared with the calculated theoretical transient fluid dynamic pressure difference sequence. Obvious outliers caused by noise were removed through deviation verification, and the dataset was filled with adjacent data through linear interpolation, resulting in the cleaned original dynamic response dataset.

[0105] Figure 5 The comparison between the export pressure sequence before and after noise reduction is shown, demonstrating that high-frequency random noise is effectively filtered out while key transient fluctuation features are well preserved. Figure 6 The superposition of the extracted transient pressure difference curve and the calculated theoretical transient hydrodynamic pressure difference sequence is shown. The two curves are highly consistent in shape, and their differences are used to calculate parameters such as peak ratio and time delay.

[0106] Step 5, Signal processing and transient characteristic parameter calculation and standardization: Based on the sensor accuracy and range, the noise floor of the pressure sequence was calculated to be 0.00035 MPa. An adaptive wavelet threshold denoising method associated with the cross-sectional polar moment of inertia was used to process the four original sequences separately, resulting in clean dynamic response sequences. By calculating the transient pressure difference and transient flow difference, cross-correlation analysis was performed between the transient pressure difference curve and the theoretical dynamic pressure difference sequence, extracting primary characteristic parameters as time delay 1.1 ms, peak value ratio 0.972, and decay rate 32.4 ms. Combining the primary characteristics, cross-sectional centroid coordinates, and principal moments of inertia, the equivalent dynamic stiffness and equivalent damping ratio of the valve core system were calculated using a coupled analytical method of axial tension / compression and bending stress. The second-order characteristic parameters and the range adaptation parameters of the target branch were normalized to obtain standardized data acquisition results.

[0107] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching, characterized in that, The method includes: Step 1: Obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, adaptively match and switch from the multi-parallel test channels to the target range branch to construct the initial fluid conduction loop. Perform analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. Step 2: Based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, a reference pressure field with a stable negative pressure gradient is established on the outlet side of the pressure reducing valve, and the steady-state convergence state of the reference pressure field is monitored in real time. Step 3: When the steady-state convergence meets the preset threshold condition, a transient pressure excitation is applied to the surface of the reference pressure field through the flow resistance step change caused by valve switching. The propagation and reflection characteristics of the pressure wave during the excitation process are quantified according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. Step 4: In response to the pressure wave propagation and transient flow rate change in the pipeline caused by the kinematic displacement response, the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve are collected simultaneously to obtain the original dynamic response dataset. Step 5: Based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, perform signal noise reduction processing and transient characteristic parameter calculation to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

2. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 1, characterized in that, Step 1: Obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, adaptively match and switch to the target range branch from multiple parallel test channels to construct the initial fluid conduction loop, including: The steady-state working pressure range is determined based on the pressure threshold in the preset test conditions parameters. The upper and lower limits of the volumetric flow rate are determined based on the flow range. The pressure threshold and flow range are compared with the rated pressure level and flow capacity of each parallel test channel. The branch with the rated pressure level covering the pressure threshold and the flow capacity covering the flow range is selected as the target range branch. Switch the fluid conduction path to the target range branch, while blocking the other parallel branches. Monitor whether the pressure and flow rate in the switched branch are stable within the preset deviation range. After stabilization, record the channel cross-sectional profile data, wall thickness distribution parameters, and elastic modulus and Poisson's ratio of the pipe material of the target range branch to obtain the initial fluid conduction loop.

3. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 2, characterized in that, Analytical calculations are performed on the centroid position, moment of inertia, polar moment of inertia, and bending center of the fluid channel cross-section of the target range branch to obtain the cross-sectional geometric parameters, including: Based on the channel cross-sectional profile data of the target range branch, the cross-section is divided into several basic geometric sub-units. The area of ​​each sub-unit and the static moment about the initial reference coordinate system are calculated respectively, and the coordinates of the centroid of the cross-section in the initial reference system are obtained. A centroidal coordinate system is established with the centroid as the origin. The moment of inertia and product of inertia of each sub-unit about the centroidal axis are calculated. The direction of the principal inertia axis and the corresponding principal moment of inertia are solved by coordinate rotation iteration. For each thin-walled segment in the cross section, the assumption of linear distribution of bending shear stress along the wall thickness is adopted. The moment of shear stress about the centroid of each segment is integrated and superimposed to determine the position of the bending center. For the calculation of the polar moment of inertia, according to the opening characteristics of the cross section, the thin film analogy method under free torsion is used to solve the torsional constant of the cross section to obtain the geometric characteristic parameters of the cross section.

4. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 3, characterized in that, Step 2: Based on the cross-sectional geometric parameters and the flow cross-sectional characteristics of the initial fluid conduction loop, a reference pressure field with a stable negative pressure gradient is established at the outlet side of the pressure reducing valve, and the steady-state convergence state of the reference pressure field is monitored in real time, including: Based on the obtained centroid coordinates, principal moment of inertia, bending center position, and polar moment of inertia of the cross section, combined with the flow cross-sectional area and hydraulic diameter of the initial fluid conduction loop, the friction coefficient and local resistance coefficient of the outlet side pipeline of the pressure reducing valve are calculated. Based on the resistance coefficient, the downstream negative pressure regulating device is driven to gradually reduce the pressure on the outlet side of the pressure reducing valve while keeping the inlet pressure constant. A negative pressure gradient field with gradually decreasing pressure along the flow direction is formed on the outlet side. Multiple pressure sensing points are arranged on the outlet side of the pressure reducing valve to collect the pressure value of each sensing point in real time. The pressure of each point is compared with the theoretical negative pressure distribution curve point by point to calculate the overall deviation of the current pressure field. Based on the overall deviation of the current pressure field, the opening of the negative pressure regulating device is continuously fine-tuned to gradually reduce the overall deviation until the deviation is lower than the preset threshold for three consecutive sampling cycles, at which point the reference pressure field is determined to have entered a steady-state convergence state.

5. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 4, characterized in that, Step 3 includes: Based on the obtained outlet side pressure distribution data and negative pressure gradient value under steady-state convergence, it is confirmed that the pressure fluctuation amplitude and gradient change rate at each point in the current reference pressure field are lower than the preset threshold condition, and this moment is recorded as the zero-time reference for transient excitation. Based on the zero-time reference, a predetermined timing drive signal is applied to the fast switching valve set upstream of the pressure reducing valve, causing the valve to switch instantaneously from the fully open state to the preset partially closed state. A transient pressure excitation wave with known amplitude and steep rise edge, starting from the zero time, is superimposed on the surface of the stabilized reference pressure field. The peak pressure and rise time of the transient pressure excitation wave are recorded. By combining the peak pressure and rise time of the transient pressure excitation wave with the principal moment of inertia and polar moment of inertia in the cross-sectional geometric parameters and the elastic wave velocity calculation formula of the pipeline, the velocity of the excitation wave propagating in the forward direction of the pipeline, the reflection coefficient at the abrupt change in the cross-section, and the attenuation factor after multiple reflections are quantified, and a set of pressure wave propagation characteristic parameters is obtained. Based on the set of pressure wave propagation characteristic parameters, the arrival time and pressure amplitude of the excitation wave to the front and rear end faces of the pressure reducing valve core are discretized along the pipeline axis to obtain the transient fluid dynamic pressure difference sequence. The transient fluid dynamic pressure difference sequence is used as an external load input and coupled with the inertial force determined by the mass distribution of the valve core and the spring preload to obtain the kinematic displacement response that changes with time.

6. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 5, characterized in that, Step 4: In response to the pressure wave propagation and transient flow rate changes in the pipeline caused by the kinematic displacement response, the time-domain pressure sequence and instantaneous flow rate sequence at the inlet and outlet of the pressure reducing valve are simultaneously acquired to obtain the original dynamic response dataset, including: The obtained kinematic displacement response curve is used to extract the starting time when the valve core displacement first leaves the initial equilibrium position, the time when the displacement peak occurs, and the time window when it returns to the vicinity of the equilibrium position, so as to obtain the trigger time reference. Based on the trigger time reference, the inlet pressure sensor and the outlet pressure sensor are activated, and the inlet time domain pressure sequence and the outlet time domain pressure sequence are synchronously acquired from the preset buffer period before the start time to the buffer period after the recovery time at a sampling frequency twice higher than the highest frequency component of the kinematic displacement response. The inlet and outlet flow meters are started in parallel, and the same sampling frequency is used to synchronously collect the inlet instantaneous flow sequence and outlet instantaneous flow sequence within the same time window. The four sequences are aligned according to the time axis to form a multidimensional raw dynamic response dataset indexed by time. The pressure and flow sequences in the multidimensional original dynamic response dataset are compared with the transient fluid dynamic pressure difference sequence point by point to check the deviation. Obvious outliers caused by sensor noise are removed, and the normal values ​​before and after the time of the outlier are filled by linear interpolation to obtain the cleaned original dynamic response dataset.

7. The method for acquiring transient response data of a pressure reducing valve based on multi-range adaptive switching according to claim 6, characterized in that, Step 5 includes: Obtain the original dynamic response dataset, and simultaneously read the principal moment of inertia and bending center position from the cross-sectional geometric characteristic parameters, as well as the rated pressure level and flow capacity of the target range branch as range adaptation parameters. Based on the sensor accuracy level and range adaptation parameters, the noise floor level of each pressure sequence and flow sequence is determined. An adaptive filter width associated with the polar moment of inertia in the cross-sectional geometric characteristic parameters is used to perform wavelet threshold denoising on the inlet time domain pressure sequence, outlet time domain pressure sequence, inlet instantaneous flow sequence and outlet instantaneous flow sequence in the original dynamic response dataset to obtain the denoised dynamic response sequence. The transient pressure difference change curve is obtained by performing difference calculation on the inlet and outlet pressure sequences after noise reduction, and the transient flow rate change curve is obtained by performing difference calculation on the inlet and outlet flow rate sequences. The two curves are then cross-correlation analysis with the transient fluid dynamic pressure difference sequence to extract time delay, peak ratio and decay rate as primary characteristic parameters of transient response. Based on the primary characteristic parameters, combined with the obtained centroid coordinates of the cross section and principal moments of inertia, the equivalent dynamic stiffness and damping ratio of the pressure reducing valve core during the transient response process are calculated using a coupled analytical method of axial tensile and compressive stress and bending normal stress, thus obtaining the second-order transient characteristic parameters. The second-order transient characteristic parameters and the range adaptation parameters of the target range branch are normalized to obtain standardized data acquisition results.

8. A transient response data acquisition system for a pressure reducing valve based on multi-range adaptive switching, the system implementing the method as described in any one of claims 1 to 7, characterized in that, include: The calculation module is used to obtain the preset test condition parameters of the pressure reducing valve. Based on the pressure threshold and flow range in the preset test condition parameters, it adaptively matches and switches from multiple parallel test channels to the target range branch to construct the initial fluid conduction loop. It performs analytical calculations on the centroid position, moment of inertia, polar moment of inertia and bending center of the fluid channel cross section of the target range branch to obtain the cross section geometric characteristic parameters. The monitoring module is used to establish a reference pressure field with a stable negative pressure gradient on the outlet side of the pressure reducing valve based on the cross-sectional geometric characteristics and the flow cross-sectional characteristics of the initial fluid conduction loop, and to monitor the steady-state convergence state of the reference pressure field in real time. The switching module is used to apply transient pressure excitation to the surface of the reference pressure field by the flow resistance step change caused by valve switching when the steady-state convergence state meets the preset threshold condition. It also quantifies the propagation and reflection characteristics of the pressure wave during the excitation process according to the cross-sectional geometric characteristic parameters, so that the valve core of the pressure reducing valve generates a kinematic displacement response under the coupling action of fluid dynamic pressure difference and inertial force. The acquisition module is used to respond to the propagation of pressure waves and transient flow of medium in the pipeline caused by kinematic displacement response, and simultaneously acquire the time-domain pressure sequence and instantaneous flow sequence at the inlet and outlet of the pressure reducing valve to obtain the original dynamic response dataset. The processing module is used to perform signal noise reduction processing and transient characteristic parameter calculation based on the original dynamic response dataset, cross-sectional geometric characteristic parameters, and range adaptation parameters of the target range branch, to obtain standardized data acquisition results of the transient response characteristics of the pressure reducing valve.

9. A computing device, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program that, when executed by a processor, implements the method as described in any one of claims 1 to 7.

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