Gas pressure regulator full-performance detection system based on secondary self-balancing pressure regulator

Abstract

The invention relates to the technical field of gas transmission and distribution equipment detection, in particular to a gas pressure regulator full-performance detection system based on a secondary self-balancing pressure regulator. Comprising a high-pressure gas source module, an inlet pressure regulation and control module, a tested gas pressure regulator mounting station, a dynamic load simulation module, a multi-parameter sensing array, a central control and data processing unit and other key components. The high-response electric proportional pressure reducing valve is used for accurately regulating and controlling the inlet pressure, and the secondary self-balancing pressure regulator is used for simulating the real dynamic load change of a user side, so that the performance test of the gas pressure regulator under various complex working conditions is realized. The system not only supports a steady state performance test, a dynamic response test and a limit working condition test, but also has a sealing performance test function, can automatically perform intelligent diagnosis and generate a detection report, can be widely applied to gas pressure regulator manufacturing enterprises, third-party detection institutions and urban gas company operation and maintenance centers, and meets various standard requirements at home and abroad.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of gas supply equipment detection, and in particular to a gas pressure regulator full performance detection system based on a secondary self-balancing pressure regulator. BACKGROUND

[0002] As the core safety equipment of the urban gas supply system, the performance of the gas pressure regulator is directly related to the stability of gas supply and the safety of gas use. The current national standard GB / T 38680-2020 and international standards EN 12261 and ANSI Z21.78 all have clear test requirements for the closing pressure, pressure stability accuracy, dynamic response characteristics and sealing performance of the pressure regulator. However, the current detection device widely used in the industry still has significant defects: most systems rely on fixed orifice plates, manual valves or low-response proportional valves to simulate downstream loads, and cannot truly reproduce the non-steady-state conditions such as flow step and pressure fluctuation caused by the start and stop of cooking utensils, the start of boilers and the like in the actual gas use process; dynamic testing is mostly qualitative judgment of "with or without response", and lacks high-precision capture of quantitative indicators such as overshoot, recovery time and oscillation times; the sealing performance test is usually observed by rough pressure retention, and it is difficult to detect small internal leaks (<5 mL / h), and such hidden defects may evolve into major safety hazards in long-term operation. Although some research has tried to introduce electronic loads or servo systems to improve the testing capability, the structure is complex and the cost is high, and it does not form a cooperative feedback mechanism with the measured object, resulting in distorted test excitation and poor repeatability, which is difficult to be applied in manufacturing and operation scenarios. Therefore, we propose a gas pressure regulator full performance detection system based on a secondary self-balancing pressure regulator. SUMMARY

[0003] The main purpose of the present application is to provide a gas pressure regulator full performance detection system based on a secondary self-balancing pressure regulator and a preparation method, which can effectively solve the problems in the background art.

[0004] To achieve the above purpose, the technical scheme adopted by the present application is: A gas pressure regulator full performance detection system based on a secondary self-balancing pressure regulator, comprising: a high-pressure gas source module; an inlet pressure regulation module connected to the high-pressure gas source module for adjusting the pressure applied to the inlet of the measured gas pressure regulator; a measured gas pressure regulator installation station; a dynamic load simulation module, the dynamic load simulation module comprising a secondary self-balancing pressure regulator, the inlet of the secondary self-balancing pressure regulator being connected to the outlet of the measured gas pressure regulator, for simulating the dynamic gas load of a real user end; A multi-parameter sensor array is arranged at the key positions of the inlet, outlet and secondary self-balancing pressure regulator of the gas pressure regulator under test, for synchronously collecting pressure, flow rate, temperature and valve rod displacement signals; A central control and data processing unit is electrically connected with the inlet pressure regulating module, dynamic load simulation module and multi-parameter sensor array, for executing test procedures, collecting data and performing performance evaluation.

[0005] Preferably, the central control and data processing unit is configured with a "double closed-loop + feedforward" compound control strategy, in which: The inner closed loop controls the inlet pressure regulating module to maintain the set inlet pressure; The outer closed loop adjusts the set pressure of the secondary self-balancing pressure regulator according to the difference between the target outlet pressure and the measured outlet pressure; The feedforward channel compensates the output of the inlet pressure regulating module in advance according to the rate of change of the set pressure of the secondary self-balancing pressure regulator, to suppress system disturbance.

[0006] Through the above technical solution: by integrating the "inner loop inlet pressure control + outer loop outlet pressure-flow feedback + feedforward disturbance compensation" compound control architecture in the central control and data processing unit, high-precision regulation of complex test conditions is realized. The inner closed loop uses the inlet pressure sensor signal as feedback to quickly adjust the electric proportional valve to maintain the set inlet pressure; the outer closed loop dynamically adjusts the set value of the secondary self-balancing pressure regulator according to the outlet pressure deviation of the measured pressure regulator; the feedforward channel analyzes the rate of change of the set pressure in real time (dP / dt), and compensates the upstream gas supply in advance, effectively suppressing the system coupling disturbance caused by load mutation, and significantly improving the fidelity and repeatability of the test waveform.

[0007] Preferably, the set pressure of the secondary self-balancing pressure regulator is driven by an electric actuator, which is programmed and controlled by the central control and data processing unit, and can generate step, ramp, sine or random fluctuation pressure set curves to simulate different gas use scenarios.

[0008] Through the above technical solution: the set pressure of the secondary self-balancing pressure regulator is driven by a high-response electric actuator, which receives digital instructions from the central control unit and can generate step, ramp, sine or random fluctuation pressure set curves according to the preset program. Through flexible programming, the system can simulate real user end gas use scenarios (such as stove start-stop, boiler start-up, etc.), so that the measured pressure regulator can be subjected to dynamic performance evaluation under conditions close to actual operating environment, breaking through the limitation of traditional fixed orifice load that cannot reproduce non-steady state conditions.

[0009] ​Preferably, the multi-parameter sensor array includes a high-precision pressure sensor, a Coriolis mass flow meter, a PT100 temperature sensor, and an LVDT displacement sensor. All sensors have a sampling frequency of not less than 1 kHz and achieve data alignment through a timestamp synchronization mechanism.

[0010] The above technical solution involves deploying high-precision pressure sensors (0.1%FS), Coriolis mass flow meters, PT100 temperature sensors, and LVDT valve stem displacement sensors at the inlet, outlet, and key locations of the pressure regulator under test. All sensors have a sampling frequency of at least 1 kHz, and microsecond-level synchronous acquisition is achieved through hardware triggering or timestamp alignment mechanisms. This design ensures accurate and reliable temporal correlation of various physical quantities during dynamic response, providing a high-quality raw data foundation for subsequent feature extraction and fault diagnosis.

[0011] Preferably, it also includes a sealing detection subsystem, which closes the upstream and downstream valves of the gas pressure regulator under test during the static pressure holding phase, and determines whether there is internal or external leakage by monitoring the outlet pressure decay rate and combining it with temperature compensation.

[0012] Through the above technical solution: the system integrates a dedicated sealing test subsystem, which automatically closes the isolation valves upstream and downstream of the pressure regulator under test during the static pressure holding stage, sealing its internal flow channel to form a cavity of known volume; subsequently, it monitors the decay curve of the outlet side pressure over time, and combines it with the measured temperature to perform ideal gas state equation compensation, accurately calculating the leakage rate. This method can detect minute internal leaks as low as 2 mL / h, which is significantly better than the traditional visual pressure holding method and can effectively identify hidden defects such as aging of seals or wear of valve ports.

[0013] Preferably, the central control and data processing unit has a built-in multi-physical quantity fusion diagnostic algorithm. This algorithm extracts feature vectors based on the collected dynamic response data, including overshoot, recovery time, phase lag, and flow-pressure coupling coefficient, and inputs them into a pre-trained classification model to output the health status score and fault type of the tested voltage regulator.

[0014] Through the above technical solution: the central control unit has a built-in intelligent diagnostic module that automatically extracts overshoot based on synchronously acquired high-dimensional time-series data. Recovery time ), number of oscillations, flow-pressure coupling coefficient ( The system constructs a structured feature vector by taking characteristic parameters with clear physical meanings, such as phase lag, and other features. This vector is then fed into a pre-trained classification model to achieve a quantitative assessment of the health status of the tested voltage regulator and outputs a health score of 0–100 and specific fault types (such as diaphragm aging, valve port wear, etc.).

[0015] Preferably, the classification model is a supervised learning model based on support vector machine (SVM) or lightweight neural network, and its training data comes from a test database of historical qualified products and known defective samples.

[0016] The above technical solution employs a supervised learning algorithm such as Support Vector Machine (SVM) or lightweight neural networks (e.g., MobileNet or MLP). Its training data comes from a historical database of over 500 sample sets, covering qualified products and various known defect types (e.g., spring fatigue, seal failure), and has been verified and labeled by experts through disassembly. The model is deployed on an embedded controller in ONNX format, with an inference latency of less than 50 ms, balancing diagnostic accuracy and real-time performance, making it suitable for industrial edge computing environments.

[0017] Preferably, the high-pressure gas source module is equipped with a gas purification and drying device to ensure that the cleanliness of the test medium meets the ISO8573-1 Class 2 standard and to avoid impurities interfering with the performance of the pressure regulator under test.

[0018] The above technical solution integrates a three-stage filtration system, activated carbon adsorption, and freeze-drying unit at the back end of the high-pressure gas source module, ensuring that the cleanliness of the test medium (nitrogen or natural gas) meets the ISO 8573-1 Class 2 standard (particles ≤ 1 mg / m³). 3 (Dew point ≤ -40°C). This design effectively prevents moisture, oil, or particulate impurities from entering the voltage regulator under test, avoiding performance drift or misjudgment caused by contamination, and ensuring the accuracy of test results and the long-term reliability of the equipment.

[0019] Preferably, the system supports a fully automated testing process, including: initial calibration, steady-state performance testing, dynamic response testing, extreme condition testing, and sealing testing, and automatically generates test reports that comply with GB / T 38680 or EN 12261 standards.

[0020] Through the above technical solution, the system supports one-click start of a fully automated testing process, sequentially completing initial purging calibration, steady-state performance testing (multi-flow point), dynamic step response, extreme inlet pressure shock, and high-sensitivity sealing testing. After the test, it automatically calls the diagnostic model to analyze the data and generates a PDF test report conforming to domestic and international standard formats such as GB / T 38680, EN 12261, or ANSI Z21.78, including performance curves, characteristic indicators, health scores, and conclusion recommendations, significantly improving testing efficiency and compliance.

[0021] Preferably, a quick switching interface is provided between the secondary self-balancing pressure regulator and the gas pressure regulator under test, allowing multiple pressure regulators of different types to be connected sequentially for batch testing, thereby improving testing efficiency.

[0022] The above technical solution involves configuring quick-installation flanges or pneumatic quick-change couplings between the dynamic load simulation module and the installation station of the pressure regulator under test. Combined with a modular workstation platform, this allows for the replacement and sealing of different models (DN15–DN300) of pressure regulators within 2 minutes. This design supports continuous batch testing, significantly improving the testing efficiency of production lines or testing centers, and is suitable for large-scale manufacturing quality inspection or third-party certification scenarios.

[0023] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention innovatively uses a secondary self-balancing pressure regulator as a dynamic load simulation unit, achieving for the first time a high-fidelity reproduction of real gas usage disturbance conditions, significantly improving the realism and coverage of the test. Traditional testing systems use static impedance (such as orifice plates) or low-response actuators to simulate user-end loads, failing to reflect the dynamic characteristics of rapid gas usage changes in the pipeline network. The secondary self-balancing pressure regulator itself possesses millisecond-level response speed, high pressure stability, and self-balancing disturbance rejection capabilities. When its set pressure is programmed and adjusted by the central control system, it can accurately generate step, ramp, and even randomly fluctuating pressure-flow curves, realistically simulating typical scenarios such as peak-hour gas usage and intermittent large-flow shocks. This allows the pressure regulator under test to be evaluated under conditions close to actual operating conditions, not only meeting the basic requirements of national standards for dynamic response but also exposing its potential performance shortcomings under complex disturbances, providing a reliable basis for product design optimization and quality grading.

[0024] 2. The composite control architecture proposed in this invention, consisting of "inner loop inlet pressure control + outer loop outlet pressure-flow joint feedback + feedforward disturbance compensation," effectively solves the system coupling interference problem in dynamic testing, achieving high-precision and robust excitation reproduction. During dynamic testing, the active adjustment of the secondary self-balancing pressure regulator will cause a reverse disturbance to the upstream pressure field. Relying solely on conventional feedback control will lead to inlet pressure fluctuations and waveform distortion. This system rapidly stabilizes the inlet pressure through the inner loop, dynamically adjusts the load setting based on the outlet deviation in the outer loop, and analyzes the set pressure change rate in real time via the feedforward channel. This method proactively compensates for upstream gas supply, effectively suppressing system coupling interference caused by load changes. Experiments show that under extreme operating conditions with an outlet pressure step of ±30%, inlet pressure fluctuations can be controlled within ±0.5%, and the standard deviation of the outlet response curve repeatability is less than 0.8%, far superior to traditional methods. This control strategy ensures high repeatability and quantifiability of test excitation, laying a technical foundation for horizontal comparison and vertical tracking of the regulator's dynamic performance.

[0025] 3. The multi-physical quantity fusion intelligent diagnostic algorithm integrated in this invention achieves, for the first time, online, quantitative, and intelligent identification of latent defects in gas pressure regulators, breaking through the limitations of the traditional binary "qualified / unqualified" judgment. Unlike judgment methods that rely solely on a single indicator (such as shut-off pressure), this system simultaneously collects high-sampling-rate pressure, flow, temperature, and valve stem displacement signals, extracting overshoot from them. Recovery time ), flow-pressure coupling coefficient ( ), leakage rate ( ), number of oscillations ( Five characteristic parameters with clear physical meanings, including diaphragm aging, spring fatigue, valve wear, and seal failure, are used to construct a structured feature vector, which is then input into a pre-trained XGBoost model. This model can comprehensively assess various fault modes, such as diaphragm aging, spring fatigue, valve wear, and seal failure, and output a health status score and fault type suggestions. In actual verification, the system successfully identified a batch of products with "normal shut-off pressure but minor internal leakage (2-8 mL / h)," which traditional methods missed due to the lack of high-sensitivity pressure holding tests. The fault diagnosis accuracy reached 91.6%. This capability not only improves the reliability of factory inspection but also provides data support for predictive maintenance of in-service equipment, significantly reducing the risk of safety accidents and operation and maintenance costs. Attached Figure Description

[0026] Figure 1 This is a block diagram of the overall structure of the detection system described in this invention; Figure 2 This is a flowchart of the fully automated testing process. Detailed Implementation

[0027] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0028] I. System Hardware Composition like Figure 1 As shown, a full-performance testing system for a gas pressure regulator based on a secondary self-balancing pressure regulator includes: High-pressure gas source module: The gas source is adjustable from 0.4–10 MPa, provided by a nitrogen or natural gas storage tank, and enters the system after passing through a gas purification and drying device (compliant with ISO 8573-1 Class 2); Inlet pressure control module: It adopts a high-response electric proportional pressure reducing valve, which is controlled by a 4–20 mA signal output from the central control unit, with an adjustment accuracy of ±0.01 MPa; The gas pressure regulator under test is installed at the standard flange position, supporting quick replacement of DN15–DN300 specifications; Dynamic load simulation module: The core is a secondary self-balancing pressure regulator, whose set pressure is adjusted by a built-in electric actuator, with a response time ≤100 ms; Multi-parameter sensor array: The inlet side is equipped with a high-precision pressure sensor P1 (0.1%FS), a Coriolis mass flow meter Q1, a PT100 temperature sensor T1, and an LVDT displacement sensor D1; the outlet side is equipped with P2, Q2, and T2. All sensors have a sampling frequency of 1kHz and time synchronization is achieved through hardware triggering. Central control and data processing unit: based on an industrial PC and a real-time controller (such as NI cRIO), running LabVIEW or custom embedded software; Sealing test isolation valve assembly: located upstream and downstream of the pressure regulator under test, used for static pressure holding test.

[0029] II. Implementation of Control Strategies When the system is running, the central control unit executes the following control logic: Internal closed loop: Using P1 as feedback, the inlet proportional valve is adjusted to stabilize the inlet pressure at the set value (e.g., 0.4 MPa). External closed loop: The difference between P2 and the target outlet pressure (e.g., 2.5 kPa) is used as input, and the set value is output to the electric actuator of the secondary self-balancing pressure regulator through the PID algorithm; Feedforward channel: Real-time monitoring of the set pressure change rate of the secondary self-balancing pressure regulator. Adjusting the opening of the inlet proportional valve in advance can counteract upstream disturbances and improve system robustness.

[0030] For example, in simulating a scenario where a user suddenly turns on a high-flow stove, the system abruptly drops the set pressure of the secondary self-balancing pressure regulator from 2.5 kPa to 2.0 kPa, causing a sudden increase in outlet flow. At this point, the feedforward channel immediately increases the inlet pressure compensation to ensure that the pressure regulator under test completes the dynamic response test under real disturbances.

[0031] III. Typical Test Procedure like Figure 2 As shown, a complete fully automated test includes the following steps: Initialization (0-60s): The operator installs the pressure regulator under test at the workstation and starts the system; the pipeline is automatically purged (30s) and the sensor zero point is calibrated. 1. Steady-state performance test (60-120s): (1) Set the inlet pressure to 0.4 MPa; (2) Adjust the secondary self-balancing pressure regulator so that the outlet flow rate is successively 20%, 50%, 80%, and 100% of the rated flow rate; (3) Record the P2 value at each point and calculate the flow-pressure coupling coefficient. Where ΔQ is the change in outlet flow rate (unit: m³ / s). 3 / h); ΔP is the corresponding change in outlet pressure (unit: kPa); the k value reflects the degree of influence of flow rate change on outlet pressure under steady-state conditions.

[0032] 2. Dynamic response test (120-150s): (1) Under rated operating conditions, The step adjustment is reduced by 20% (e.g., 2.5 → 2.0 kPa); (2) Synchronously acquire the P2(t) curve and calculate the overshoot. With recovery time ; (3) Repeat the step jumps of different amplitudes 5 times (±10%-±50%).

[0033] 3. Extreme operating condition test (150-180s): (1) When the inlet pressure suddenly increases from 0.2 MPa to 0.8 MPa, monitor whether the shut-off pressure exceeds 1.25 times the rated outlet pressure.

[0034] 4. Sealing test (180-240s): (1) Close the isolation valve assembly and pressurize the outlet of the pressure regulator under test to 2.5 kPa; (2) Hold the pressure for 10 minutes and record the P2 decay curve; According to the formula Calculate the leakage rate (V is the known enclosed volume = 0.8L). in, Leakage rate (unit: mL / h) is calculated from the pressure decay rate during the pressure holding stage; V is the effective volume of the closed cavity (unit: L), referring to the total internal volume enclosed by the isolation valve group, including all connected spaces such as the outlet of the pressure regulator under test, connecting pipelines, and sensor interfaces. This value needs to be determined in advance through calibration. The statement "V is a known closed volume = 0.8 L" in the text is not arbitrarily specified. In order to comply with industry testing practices, Appendix B of the national standard GB / T 38680-2020 "Urban Gas Pressure Regulators" stipulates that "the test chamber volume should be recorded" during the sealing test. Moreover, most third-party testing institutions use test fixtures of similar magnitude (0.5–1.2 L). 0.8 L is a reasonable intermediate value, which facilitates horizontal comparison of results. In practical applications, the system supports "volume calibration mode", which involves filling the closed cavity with a known mass of gas (or using standard leak calibration) to deduce the actual V value and store it in the equipment configuration file. Therefore, "0.8 L" is the default reference value, not a fixed and unchangeable parameter; R is the universal gas constant, with units of J / (mol·K) or L·kPa / (mol·K); T2 is the absolute temperature, with units of K.

[0035] 5. Intelligent diagnosis and report generation (240-300s): The above features are combined into a column vector form, and the feature vector is extracted. ; Among them, overshoot (Unit: kPa), representing the maximum excess of the outlet pressure over the target value during the dynamic response process; recovery time. (Unit: s), defined as the time required from the onset of a step disturbance to the exit pressure entering and stabilizing within ±2% of the target band; number of oscillations. (Dimensionless) The number of complete cycles in which the export pressure crosses the target pressure centerline during the dynamic response.

[0036] (2) Input the pre-trained XGBoost model (which has been trained on 500 sets of samples); (3) Output health score (0–100) and fault type; (4) Automatically generate PDF test reports that meet the requirements of GB / T 38680 format.

[0037] IV. Implementation of Intelligent Diagnosis The diagnostic model training process is as follows: Collect historical data: including complete test data from 300 qualified products and 200 known defective samples (including diaphragm aging, valve wear, spring failure, etc.); Labeling: Experts label the fault types based on the disassembly results; Feature engineering: Extract the aforementioned 5-dimensional features and normalize them using Min-Max; Model training: Using the XGBoost algorithm with 5-fold cross-validation, the accuracy was 92.3%. Deployment: The model is embedded in the cRIO controller in ONNX format, with inference latency <50 ms.

[0038] In practical applications, the system successfully identified a batch of products with "normal shut-off pressure but minor internal leakage," which traditional methods missed due to the lack of high-sensitivity pressure holding tests.

[0039] V. Verification of Implementation Results During its trial operation at a national-level gas equipment testing center, this system conducted fully automated performance tests on 120 pressure regulators from 8 different manufacturers, ranging from DN15 to DN100. The results are as follows: Dynamic response test repeatability: Under the same step disturbance condition (outlet pressure jumps from 2.5 kPa to 2.0 kPa), the recovery time obtained from 5 consecutive tests on the same pressure regulator. The standard deviation is 0.73%, indicating that the system excitation reproduction is highly stable; Sealing test sensitivity: Successfully detected a minute internal leak sample with a minimum leakage rate of 2 mL / h (equivalent to a leakage of approximately 1.6 cm per hour under standard conditions). 3 (Natural gas), far exceeding the 10 mL / h threshold required by GB / T 38680; Improved testing efficiency: The average time for a single voltage regulator to complete all four tests (steady-state, dynamic, ultimate, and sealing) is 14.2 minutes, which is 43% more efficient than the traditional manual + semi-automatic method (average 25 minutes). Intelligent diagnostic accuracy: The system outputs health status assessment results and expert analysis conclusions, and the fault diagnosis accuracy rate reaches 91.6%. Among them, the identification rates of two types of latent defects, "diaphragm aging" and "valve port micro-wear", are 89.2% and 93.1% respectively, and the overall false alarm rate is less than 3%.

[0040] The above quantitative data fully demonstrate that the present invention is significantly superior to the prior art in terms of test authenticity, control accuracy, detection sensitivity and diagnostic intelligence, and has outstanding practicality and promotion value.

[0041] Therefore, in summary, this embodiment fully verifies the significant advantages of the present invention in terms of test authenticity, control accuracy, and diagnostic intelligence. It has good prospects for industrial application and can be widely used in gas pressure regulator manufacturers, third-party testing institutions, and urban gas company operation and maintenance centers. It meets the full testing requirements of domestic and international standards such as GB / T 38680, EN 12261, and ANSI Z21.78, and has significant economic and social benefits.

[0042] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A full performance detection system of gas pressure regulator based on secondary self-balancing pressure regulator, characterized in that: It comprises: a high-pressure gas source module; an inlet pressure regulation module connected to the high-pressure gas source module for adjusting the pressure applied to the inlet of the gas pressure regulator under test; a gas pressure regulator installation station; a dynamic load simulation module, which includes a secondary self-balancing pressure regulator, the inlet of which is connected to the outlet of the gas pressure regulator under test, for simulating the dynamic gas load of a real user end; a multi-parameter sensing array arranged at key positions of the inlet, outlet of the gas pressure regulator under test and the secondary self-balancing pressure regulator for synchronously collecting pressure, flow, temperature and valve rod displacement signals; a central control and data processing unit electrically connected to the inlet pressure regulation module, dynamic load simulation module and multi-parameter sensing array for executing test procedures, collecting data and performing performance evaluation; The central control and data processing unit is configured with a "double closed loop + feedforward" compound control strategy, in which: The inner closed loop control inlet pressure regulation module to maintain the set inlet pressure; The outer closed loop adjusts the set pressure of the secondary self-balancing pressure regulator according to the difference between the target outlet pressure and the measured outlet pressure; The feedforward channel compensates the output of the inlet pressure regulation module in advance according to the set pressure change rate of the secondary self-balancing pressure regulator to suppress system disturbance; The set pressure of the secondary self-balancing pressure regulator is driven by an electric actuator controlled by the central control and data processing unit, which can generate step, ramp, sine or random fluctuation pressure set curves to simulate different gas usage scenarios.

2. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator according to claim 1, characterized in that: The multi-parameter sensing array includes high-precision pressure sensors, Coriolis mass flow meters, PT100 temperature sensors and LVDT displacement sensors, all with a sampling frequency not less than 1 kHz, and data alignment is achieved through a timestamp synchronization mechanism.

3. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator of claim 1, wherein: It also includes a leak detection subsystem that closes the upstream and downstream valves of the gas pressure regulator under test during the static pressure maintaining stage, and judges whether there is internal or external leakage by monitoring the outlet pressure decay rate and combining temperature compensation.

4. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator of claim 1, wherein: The central control and data processing unit has a multi-physical quantity fusion diagnosis algorithm, which extracts feature vectors including overshoot, recovery time, phase lag and flow-pressure coupling coefficient based on the collected dynamic response data, and inputs them into a pre-trained classification model to output the health status score and fault type of the measured pressure regulator.

5. The gas pressure regulator full performance test system based on the secondary self-balancing pressure regulator of claim 4, wherein: The classification model is a supervised learning model based on support vector machine or lightweight neural network, and its training data comes from the test database of historical qualified products and known defective samples.

6. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator of claim 1, wherein: The high-pressure gas source module is equipped with a gas purification and drying device to ensure that the test medium cleanliness meets the ISO8573-1 Class 2 standard, avoiding interference of impurities on the performance of the measured pressure regulator.

7. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator of claim 1, wherein: The system supports fully automatic test procedures, including initial calibration, steady-state performance test, dynamic response test, extreme condition test and leak test, and automatically generates a test report in accordance with GB / T 38680 or EN 12261 standards.

8. The gas pressure regulator full performance detection system based on the secondary self-balancing pressure regulator of claim 1, wherein: The secondary self-balancing pressure regulator is provided with a quick switching interface between the secondary self-balancing pressure regulator and the measured gas pressure regulator, and a plurality of different types of pressure regulators are sequentially connected for batch detection, so that the detection efficiency is improved.

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