A pressure testing system for pressure reducing valves

Abstract

This invention relates to the field of pressure reducing valve testing technology and discloses a pressure testing system for pressure reducing valves. The system's environmental parameter monitoring module collects real-time data on temperature, humidity, and vibration intensity of the environment in which the pressure reducing valve is located and transmits this data to the test execution module. Based on the received environmental data, the test execution module initiates a pressure loading process, applying a dynamically changing pressure load sequence through a hydraulic control device, while simultaneously recording the deformation response data of the pressure reducing valve. After receiving the deformation response data, the result analysis module performs multi-dimensional failure mode identification calculations, generating a test report containing leakage risk assessment parameters and structural fatigue coefficients. This report is fed back to the test execution module for real-time adjustment of the pressure load sequence application strategy. Through the coordinated operation of its modules, this system achieves dynamic monitoring and evaluation of the pressure performance of the pressure reducing valve, improving the accuracy and relevance of the test.

Description

Technical Field

[0001] This invention relates to the field of pressure reducing valve testing technology, specifically a pressure reducing valve pressure testing system. Background Technology

[0002] Pressure reducing valves, as key components in fluid control systems, are widely used in numerous industrial fields such as petroleum, chemical, water conservancy, and machinery. Their performance stability directly affects the safe operation of the entire system. Hydrogen energy, as a clean and efficient energy carrier, places even higher demands on the pressure control accuracy and safety of pressure reducing valves in related equipment. In practical applications, pressure reducing valves need to withstand pressure loads of varying intensities for extended periods and operate under complex environmental conditions. Therefore, comprehensive and accurate pressure testing is a crucial prerequisite for ensuring reliable equipment operation.

[0003] While the industry has developed a certain system for pressure testing methods for pressure reducing valves, several limitations remain. Most testing systems, during their design, often neglect the impact of environmental factors on the test results, focusing solely on the application of pressure loads and the recording of basic parameters. For example, regarding temperature, different temperatures can cause changes in the hardness and elasticity of the sealing materials inside the pressure reducing valve, thus affecting its sealing performance and pressure response characteristics. Existing tests often set the temperature to a fixed value, making it difficult to simulate temperature fluctuations in actual operating conditions. Changes in humidity can cause corrosion on the valve body surface or moisture absorption of internal components, affecting structural strength, yet few testing systems include humidity in their monitoring scope. Vibration, a common disturbance in industrial environments, can exacerbate wear and loosening of internal components in pressure reducing valves. Existing tests often fail to consider the interference of vibration intensity on pressure test results, leading to significant deviations between test data and actual operating conditions.

[0004] Existing test execution modules mostly use preset, fixed pressure load sequences, which cannot be adjusted according to the real-time status of the pressure reducing valve. This static loading method is difficult to cover the complex pressure change scenarios that pressure reducing valves may encounter in actual use, and may easily overlook some potential failure risks. For example, if the pressure reducing valve has already shown slight deformation during the test, applying the fixed load sequence as planned may not further excite its structural defects, resulting in insufficient completeness of the test results.

[0005] In failure mode identification, traditional methods are often limited to single-dimensional analysis, such as judging whether there is a leak solely based on pressure changes, or assessing structural fatigue solely based on the degree of deformation, lacking a comprehensive consideration of multi-dimensional parameters. This single-dimensional identification approach cannot fully reflect the actual failure risk of the pressure reducing valve, and may lead to misjudgment or omission of certain complex failure modes. In addition, in existing testing systems, data acquisition, load application, and result analysis are mostly operated independently, lacking an effective closed-loop feedback mechanism, making it difficult to optimize the testing process in real time based on the analysis results, further reducing the relevance and effectiveness of the test. Summary of the Invention

[0006] The purpose of this invention is to provide a pressure testing system for pressure reducing valves to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides a pressure testing system for a pressure reducing valve, the system comprising: an environmental parameter monitoring module, a test execution module, and a result analysis module;

[0008] The environmental parameter monitoring module collects real-time temperature, humidity, and vibration intensity data of the environment where the pressure reducing valve is located, and transmits the temperature, humidity, and vibration intensity data sets to the test execution module.

[0009] The test execution module initiates the pressure loading process based on the received environmental data set, applies a dynamically changing pressure load sequence to the pressure reducing valve through the hydraulic control device, and records the deformation response data of the pressure reducing valve at the same time.

[0010] The result analysis module receives the deformation response data and performs multi-dimensional failure mode identification calculations to generate a test report containing leakage risk assessment parameters and structural fatigue coefficients. The leakage risk assessment parameters and structural fatigue coefficient test report are fed back to the test execution module for real-time adjustment of the pressure load sequence application strategy.

[0011] Preferably, the environmental parameter monitoring module includes a distributed sensor array and a data fusion unit; the distributed sensor array is deployed at the inlet port, outlet port, and valve body surface of the pressure reducing valve to simultaneously capture fluid pulsation frequency data, surface stress distribution data, and environmental noise spectrum data; the data fusion unit uses a spatiotemporal alignment algorithm to timestamp the fluid pulsation frequency data, surface stress distribution data, and environmental noise spectrum data to generate a composite monitoring dataset with environmental labels, which is used as the trigger condition for the pressure loading process input to the test execution module.

[0012] Preferably, the test execution module includes a pressure gradient generation unit and a response capture unit; the pressure gradient generation unit divides the intensity range and duration range of the pressure load sequence according to the temperature data and vibration intensity data in the composite monitoring dataset with environmental labels, and generates a stepped pressure waveform by controlling the hydraulic oil flow through a proportional servo valve; the response capture unit uses a laser displacement sensor array to collect the displacement trajectory data of the pressure reducing valve core, and simultaneously records the hydraulic pipeline pressure oscillation data, integrating them to form a time-aligned deformation response data stream and transmitting it to the result analysis module.

[0013] Preferably, the result analysis module includes a signal reconstruction unit and a failure feature library; the signal reconstruction unit performs wavelet packet decomposition filtering on the deformation response data stream, extracts the high-frequency components and low-frequency drift components of the valve core motion, and reconstructs a pure response signal with environmental noise removed; the failure feature library stores time-domain waveform templates of typical pressure reducing valve failure modes, performs dynamic time warping matching between the pure response signal and the waveform templates, and outputs a set of quantitative indicators including the probability of sealing failure and the elastic deformation threshold.

[0014] Preferably, the system further includes a test preparation module; the test preparation module receives humidity data and noise spectrum data from the composite monitoring dataset with environmental labels, calculates the environmental interference intensity index, and activates the device self-test protocol when the environmental interference intensity index exceeds a preset threshold; the device self-test protocol drives the hydraulic control device to perform zero-point drift calibration and sensor sensitivity verification, generates a device health status code, and embeds initial control commands of the pressure load sequence.

[0015] Preferably, the system includes a data storage center; the data storage center establishes an environmental parameter database, a load application database, and a response feature database; the environmental parameter database stores time slice data of the composite monitoring dataset in real time; the load application database records waveform parameters of pressure load sequences and servo valve control commands; the response feature database stores the pure response signal and a set of quantitative indicators in association, forming a traceable digital twin of the test process.

[0016] Preferably, the result analysis module further includes an anomaly detection unit; the anomaly detection unit performs sliding time window sampling on the deformation response data stream and calculates the statistical characteristic difference between adjacent windows; when the difference exceeds the preset safety boundary, the emergency matching mode of the failure feature library is triggered, and the valve body crack early warning signal and pressure release command are output to the test execution module in real time.

[0017] Preferably, the system includes a feedback control module; the feedback control module receives the seal failure probability and the valve body crack warning signal from the set of quantitative indicators, calculates the pressure safety attenuation coefficient; the pressure safety attenuation coefficient is converted into the flow suppression gradient parameter of the proportional servo valve, dynamically compresses the intensity range of the pressure load sequence, and forms a closed-loop pressure regulation mechanism.

[0018] Preferably, the data storage center is also associated with a test logic engine; the test logic engine calls the historical pure response signals and the current set of quantitative indicators in the response feature database to execute a pressure loading mode iterative algorithm; the pressure loading mode iterative algorithm generates an optimized set of stepped pressure waveform parameters to replace the original pressure load sequence division rules in the test execution module.

[0019] Preferably, the system includes a process management module; the process management module divides the system into an initial preparation stage, a main testing stage, and a termination analysis stage; in the initial preparation stage, it calls the equipment health status code to verify the system integrity; in the main testing stage, it coordinates the data exchange frequency between the pressure gradient generation unit and the feedback control module; and in the termination analysis stage, it integrates the set of quantitative indicators and the digital twin of the testing process to generate a final test report containing a pressure cycle durability graph.

[0020] Compared with the prior art, the beneficial effects of the present invention are:

[0021] The environmental parameter monitoring module overcomes the limitations of traditional testing that neglects environmental factors. Temperature, humidity, and vibration intensity are key environmental variables affecting the performance of pressure reducing valves. In actual operating conditions, fluctuations in these parameters directly alter the valve's sealing performance, structural strength, and pressure response characteristics. This module collects this data in real time and transmits it to the test execution module. This ensures that the subsequent pressure loading process is no longer based on idealized environmental assumptions but closely integrates with the environmental characteristics of actual operating conditions. This makes the testing process more closely resemble the actual working state of the pressure reducing valve, thus avoiding the problem of test results deviating from actual performance due to missing environmental parameters.

[0022] The test execution module initiates the pressure loading process based on the environmental data set and can receive feedback from the results analysis module to adjust the pressure load sequence, demonstrating the advantages of dynamic adaptability. In traditional testing, the pressure load sequence is mostly fixed and preset, unable to be adjusted according to the real-time response of the pressure reducing valve and environmental changes, which may lead to a mismatch between the applied load and actual needs. However, when applying a dynamically changing pressure load sequence, this module references both the initial environmental data and the leakage risk assessment parameters and structural fatigue coefficients generated by the results analysis module, continuously optimizing the magnitude, frequency, and rhythm of the load changes. This dynamic adjustment capability can more accurately stimulate potential defects in the pressure reducing valve under different environmental and load combinations, making the testing process more exploratory and targeted.

[0023] The results analysis module performs multi-dimensional failure mode identification (FMD) calculations, which are more comprehensive than traditional single-dimensional analysis. Pressure reducing valve failure is often the result of multiple factors working together; relying on only one parameter is insufficient to fully determine its leakage risk and structural fatigue state. This module integrates deformation response data and performs FMD identification from multiple dimensions, simultaneously capturing subtle deformation characteristics related to leakage and cumulative damage signals related to structural fatigue. The generated test report includes leakage risk assessment parameters and structural fatigue coefficients, providing richer information for understanding the performance shortcomings of pressure reducing valves.

[0024] The closed-loop feedback mechanism among the three modules further enhances the integrity and coherence of the testing system. The environmental parameter monitoring module provides basic data for the test execution module, the load application and data recording of the test execution module provide analytical material for the results analysis module, and the reports from the results analysis module, in turn, guide the test execution module to optimize its strategies, forming a continuously iterative cycle. This closed-loop design ensures that the testing process is not unidirectional but can continuously self-correct and improve based on real-time data, ensuring that the output of each stage serves the optimization of the next stage. This makes the entire testing process, from data acquisition to result output, more logical and effective, and can more comprehensively reveal the performance of the pressure reducing valve under complex operating conditions. Attached Figure Description

[0025] Figure 1 This is a schematic diagram of the working principle of the pressure testing system for the pressure reducing valve described in this invention.

[0026] Figure 2 This is a schematic diagram of the working principle of the environmental parameter monitoring module;

[0027] Figure 3 A schematic diagram of the module's working principle for testing;

[0028] Figure 4 This is the control flow diagram for the process management module phase. Detailed Implementation

[0029] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] Please see Figure 1 This invention provides a pressure testing system for a pressure reducing valve, the system comprising: an environmental parameter monitoring module, a test execution module, and a result analysis module. Specific implementation details are as follows:

[0031] The environmental parameter monitoring module collects real-time temperature, humidity, and vibration intensity data of the environment where the pressure reducing valve is located. These data are combined into an environmental data set through an internal data transmission link and then transmitted to the test execution module.

[0032] After receiving the environmental data set, the test execution module initiates the preset pressure loading process, applying a dynamically changing pressure load sequence to the pressure reducing valve through the hydraulic control device. During this process, the deformation response data of the pressure reducing valve under pressure is recorded simultaneously.

[0033] After receiving the deformation response data, the results analysis module performs multi-dimensional failure mode identification (FMD) calculations. During these calculations, the structural characteristics of the pressure reducing valve and the pressure load variation patterns are comprehensively considered. Ultimately, a test report is generated, including leakage risk assessment parameters and structural fatigue coefficients. This test report is then fed back to the test execution module, which adjusts the application strategy of the pressure load sequence in real time based on the parameters in the report to achieve more accurate pressure testing.

[0034] Example 1: See Figure 2 The distributed sensor array in the environmental parameter monitoring module adopts a multi-node deployment. A high-frequency pressure sensor and a fluid velocity sensor are installed at the inlet port of the pressure reducing valve to capture real-time pulsation frequency data of the fluid before it enters the valve body. This data reflects changes in the fluid's flow state within the pipeline. The sensor group at the outlet port focuses on monitoring pressure fluctuations after pressure reduction, assisting the inlet port sensors in achieving a complete capture of fluid dynamics. Strain gauges and vibration sensors are installed on the valve body surface according to an equidistant distribution principle. The strain gauges collect surface stress distribution data of the valve body under different pressures, while the vibration sensors record the vibration intensity transmitted to the valve body from the environment and the resulting environmental noise spectrum data. All these sensors employ a synchronous sampling mechanism to ensure that data collected at the same point in time accurately corresponds to the same state of the valve body.

[0035] After receiving various raw data from the distributed sensor array, the data fusion unit initiates a spatiotemporal alignment algorithm. This algorithm first calibrates the timestamps of all data, eliminating time deviations caused by differences in hardware response speeds between different sensors, ensuring complete alignment of fluid pulsation frequency data, surface stress distribution data, and environmental noise spectrum data along the time axis. Subsequently, the algorithm performs spatial correlation analysis, matching monitoring data from the inlet port, outlet port, and valve body surface to determine the inherent relationships between data from different locations. After completing spatiotemporal calibration, the data fusion unit adds environmental tags to the integrated data. These tags include the ambient temperature range, humidity range, and information on the main vibration sources during data acquisition, ultimately forming a composite monitoring dataset with environmental tags. This dataset is transmitted to the test execution module via the internal data bus, serving as a key trigger condition for initiating the pressure loading process.

[0036] Upon receiving the composite monitoring dataset with environmental labels, the pressure gradient generation unit of the test execution module first extracts and analyzes the temperature and vibration intensity data. Based on the temperature range, it determines the basic intensity range of the pressure load sequence. When the temperature is high, the initial pressure intensity range is set to a lower value, gradually expanding as the temperature decreases. The vibration intensity data is used to adjust the duration range of the pressure load; the greater the vibration intensity, the shorter the duration of each individual pressure intensity range is set to reduce the cumulative impact of continuous vibration on the valve body structure. Based on the defined intensity and duration ranges, the pressure gradient generation unit sends a control signal to the proportional servo valve. The proportional servo valve controls the flow rate of hydraulic oil by adjusting the opening of its internal valve port, thereby generating a stepped pressure waveform. Each step of this waveform corresponds to an intensity and duration range, and the rate of pressure change between steps remains constant to ensure a smooth transition during the pressure loading process.

[0037] The response capture unit is equipped with a laser displacement sensor array mounted directly in front of the pressure-reducing valve spool's movement trajectory. Employing a multi-beam synchronous measurement method, it acquires real-time displacement trajectory data of the valve spool under pressure. The sampling frequency is dynamically adjusted according to the pressure change rate; the sampling frequency is increased when the pressure changes rapidly to capture the details of the valve spool's rapid movement. Simultaneously, pressure sensors are installed at the inlet and outlet ends of the hydraulic pipeline to record pressure oscillation data within the pipeline, reflecting pressure fluctuations during transmission. The time synchronization module within the response capture unit ensures that the sampling time of the laser displacement sensor array and the pressure sensors is perfectly synchronized. The acquired valve spool displacement trajectory data and pressure oscillation data are integrated and arranged chronologically to form a time-aligned deformation response data stream. After preliminary data verification, this data stream is sent to the results analysis module via a high-speed data transmission interface, providing foundational data for subsequent failure mode identification.

[0038] Example 2: See Figure 3 Upon receiving the deformation response data stream, the signal reconstruction unit of the results analysis module initiates a wavelet packet decomposition and filtering process. This process first decomposes the data stream into multiple sub-signals of different frequencies, each corresponding to a different frequency component during the valve core's movement. By thresholding these sub-signals, high-frequency interference components containing environmental noise are removed, retaining the effective signals related to the valve core's movement. Based on this, the high-frequency and low-frequency drift components of the valve core's movement are extracted. The high-frequency components mainly reflect the instantaneous motion state of the valve core under rapid pressure changes, while the low-frequency drift components reflect the positional shift trend of the valve core under long-term pressure. These two components are then reconstructed according to the time series of the original signal to reconstruct a clean response signal free from environmental noise interference. During the reconstruction process, the time axis of the signal is finely calibrated to ensure that the signal value at each time point accurately corresponds to the actual motion state of the valve core.

[0039] The failure feature library pre-stores time-domain waveform templates for various typical pressure reducing valve failure modes, covering common failure types such as sealing surface wear, valve core jamming, and spring fatigue. Each waveform template contains the characteristic signal morphology of the failure mode under different pressure conditions, including key features such as signal peak value, valley value, fluctuation frequency, and duration. When a pure response signal is generated, the system performs dynamic time warping matching with the waveform templates in the failure feature library. During the matching process, the pure response signal and the template signal are elastically adjusted according to the signal's duration and waveform change trend to achieve optimal matching in the time dimension. By calculating the matching degree value, the similarity between the current response signal and each failure mode template is determined, and a set of quantitative indicators including the sealing failure probability and elastic deformation threshold is output. The sealing failure probability reflects the likelihood of a decrease in the sealing performance of the pressure reducing valve under the current test conditions, while the elastic deformation threshold represents the maximum deformation that the valve core can withstand without permanent deformation.

[0040] The test preparation module continuously receives humidity and noise spectrum data from a composite monitoring dataset with environmental labels. Humidity data is collected by humidity sensors distributed throughout the test environment, covering humidity conditions at different locations around the pressure reducing valve, forming spatial humidity distribution data. Noise spectrum data comes from acoustic sensors installed near the valve body, recording various noise signals and their frequency distributions in the test environment. The test preparation module integrates and processes this data, calculating an environmental interference intensity index by analyzing the variation amplitude of the humidity data and the energy distribution of the noise spectrum data. This index comprehensively considers the potential impact of humidity on the valve body material performance and the degree of noise interference with sensor signals.

[0041] When the environmental interference intensity index exceeds a preset threshold, the test preparation module automatically activates the equipment self-test protocol. The self-test protocol first sends a calibration command to the hydraulic control unit, initiating the zero-point drift calibration process. The hydraulic control unit closes the inlet and outlet valves, bringing the system to a pressure-free state. At this point, the readings of each pressure sensor are recorded, compared with the standard zero-point value, and the drift is calculated and compensated. Simultaneously, the sensor sensitivity is verified by applying known standard pressure and vibration signals to the test system, checking the accuracy and response speed of the sensor output signals to ensure accurate capture of parameter changes during the test. After calibration and verification, the self-test protocol generates an equipment health status code, which contains the operating status information of each component, including the hydraulic control unit and sensor array. This health status code is embedded in the initial control command of the pressure load sequence and sent to the test execution module along with the control command, serving as crucial reference information for initiating the pressure loading process.

[0042] Example 3: The data storage center in the system adopts a distributed architecture, internally divided into an environmental parameter database, a load application database, and a response characteristic database. These databases interact in real time via a high-speed data bus. After receiving the composite monitoring dataset from the data fusion unit, the environmental parameter database slices the data according to preset time intervals. Each time slice contains complete environmental parameters for that time period, including temperature, humidity, vibration intensity, and fluid pulsation frequency data. These time slice data are indexed and stored in chronological order of acquisition, and associated with corresponding environmental tags, facilitating quick retrieval of environmental parameters for a specific time period based on time dimension or environmental tag.

[0043] The load application database specifically stores various parameters related to pressure loading, including the intensity range and duration range of the pressure load sequence, waveform parameters such as the peak value, valley value, rise rate, and fall rate of the stepped pressure waveform, as well as the control command codes sent to the proportional servo valve. Each control command code corresponds one-to-one with a waveform parameter, recording operational information such as the servo valve's orifice opening and flow rate adjustment at different time points. The load application database employs a dynamic storage strategy, updating data in real time as the test progresses while retaining historical versions to trace adjustments made to the pressure loading strategy.

[0044] The response feature database is responsible for associating and storing pure response signals with a set of quantified indicators. Pure response signals are categorized and stored according to test batch and pressure reducing valve number, with each signal file containing complete time-series data and corresponding sampling frequency information. The set of quantified indicators includes parameters such as seal failure probability, elastic deformation threshold, and is associated with the pure response signals through a unique test number. This associative storage method forms a digital twin of the testing process, which can completely reproduce the data changes throughout the entire testing process, from environmental parameter acquisition to pressure loading and response capture.

[0045] The anomaly detection unit of the results analysis module continuously receives the deformation response data stream and processes the data using a sliding time window sampling method. The length of the sliding time window is dynamically adjusted according to the frequency of change in the pressure load sequence; a shorter time window is used when the pressure changes rapidly, and the time window length is appropriately extended when the pressure is stable. Statistical analysis is performed on the data within each time window to calculate statistical characteristic parameters such as the mean, variance, peak factor, and kurtosis.

[0046] The anomaly detection unit calculates the statistical characteristic difference by comparing the statistical characteristic parameters of two adjacent time windows. The calculation formula is as follows:

[0047]

[0048] in, Indicates the degree of statistical difference. For the previous time window One statistical characteristic parameter, For the next time window One statistical characteristic parameter, This represents the total number of statistical characteristic parameters.

[0049] When the statistical characteristic difference exceeds the preset safety boundary, the anomaly detection unit immediately triggers the emergency matching mode of the failure feature library. In emergency matching mode, the system prioritizes calling the time-domain waveform template related to the valve body crack, shortening the calculation time in the matching process. By quickly comparing the deformation response data within the current time window with the template, if the matching degree reaches the set value, a valve body crack early warning signal is output in real time, and a pressure release command is generated simultaneously. The pressure release command is sent to the test execution module, prompting it to control the hydraulic control device to quickly reduce the system pressure and prevent further crack propagation.

[0050] Example 4: The feedback control module continuously receives a set of quantitative indicators transmitted from the result analysis module, including the probability of seal failure, and also receives a valve body crack warning signal from the anomaly detection unit. The probability of seal failure is presented as a percentage, reflecting the likelihood of a decrease in the sealing performance of the pressure reducing valve under the current pressure load, while the valve body crack warning signal is a binary state value indicating whether a possible crack has been detected. The processing unit inside the feedback control module integrates these two types of information with the inherent parameters of the pressure reducing valve, including the yield strength of the valve body material, the fit clearance between the valve core and the valve seat, and the material properties of the seals. Through internal logic operations, it comprehensively evaluates the impact of the current pressure load on the pressure reducing valve structure, and then determines the pressure safety attenuation coefficient. This coefficient is a value between 0 and 1; the smaller the coefficient, the greater the pressure reduction required.

[0051] After obtaining the pressure safety attenuation coefficient, the feedback control module converts it into the flow suppression gradient parameter of the proportional servo valve. The flow suppression gradient parameter directly determines the flow regulation amplitude of the proportional servo valve per unit time. For example, when the pressure safety attenuation coefficient is small, the flow suppression gradient parameter will decrease accordingly, meaning the servo valve needs to quickly reduce the hydraulic oil flow, thereby rapidly reducing the pressure applied to the pressure reducing valve. When the coefficient is large, the flow suppression gradient parameter remains at a high level, allowing the servo valve to regulate the flow in a relatively smooth manner. The proportional servo valve adjusts its valve opening change rate according to the flow suppression gradient parameter, dynamically compressing the intensity range of the pressure load sequence by controlling the flow of hydraulic oil entering the test system. For example, if the originally set maximum pressure of the pressure load sequence is 10 MPa, after receiving an adjustment command, the maximum pressure may be compressed to 8 MPa, while simultaneously adjusting the pressure values ​​of each step accordingly, forming a closed-loop pressure regulation mechanism, enabling the pressure loading process to adaptively adjust according to the real-time status of the pressure reducing valve.

[0052] The data storage center establishes a connection with the test logic engine through an internal interface, allowing the test logic engine to access all historical clean response signals stored in the response feature database. These historical signals originate from various pressure reducing valve tests completed in the past, covering response data of pressure reducing valves of different models, service lives, and operating conditions under various pressure loads. The test logic engine obtains a set of quantitative indicators generated in real time during the current test process, including parameters such as seal failure probability and elastic deformation threshold, and compares these parameters with the historical clean response signals in multiple dimensions. During the comparison, it focuses on the parts of the historical signals that are similar to the current set of quantitative indicators, analyzes the pressure load sequence parameters corresponding to these similar signals and the final test results, and seeks out patterns.

[0053] Based on the comparative analysis of historical and current data, the test logic engine initiates an iterative algorithm for pressure loading modes. This algorithm first identifies pressure load sequence features from historical tests that more accurately reflect the failure modes of the pressure-reducing valve; for example, certain stepped pressure waveforms show better performance in identifying seal failures. Then, combining the response characteristics of the pressure-reducing valve in the current test, these effective features are adjusted and optimized to generate a new set of stepped pressure waveform parameters. The new parameter set may include adjusted pressure intensity interval division methods, the duration of each interval, and the pressure change rate between steps. The generated optimized parameter set is sent to the test execution module via a data transmission channel, replacing the original pressure load sequence division rules. This makes the subsequent pressure loading process more closely match the actual characteristics of the current pressure-reducing valve, improving the relevance and effectiveness of the test.

[0054] Example 5: See Figure 4 The process management module divides the entire pressure testing process of the pressure reducing valve into the initial preparation stage, the main testing stage, and the termination analysis stage. Each stage proceeds sequentially to form a complete closed loop of the testing process.

[0055] During the initial preparation phase, the process management module obtains the equipment health status code from the test preparation module. The equipment health status code consists of a string of characters and numbers, containing information such as the calibration status of the hydraulic control device, the sensitivity verification results of the sensor array, and the connectivity information of the data transmission link. The process management module parses the equipment health status code, checking for any abnormal indicators. If the status code contains an indicator indicating excessive zero-point drift of the hydraulic control device or a record indicating that the sensor sensitivity has failed verification, the process management module will pause the test process and issue a corresponding prompt. Only when all indicators in the equipment health status code are normal—that is, the hydraulic control device is calibrated successfully, the sensor sensitivity meets the standard, the data transmission link is unobstructed, and the system integrity verification is passed—is the main testing phase allowed.

[0056] During the main testing phase, the process management module coordinates the data exchange frequency between the pressure gradient generation unit and the feedback control module. The pressure gradient generation unit generates relevant parameters for the pressure load sequence based on a composite monitoring dataset with environmental labels and sends these parameters to the feedback control module in real time. The feedback control module calculates the pressure safety attenuation coefficient based on a set of quantitative indicators and early warning signals, converts it into flow suppression gradient parameters, and feeds them back to the pressure gradient generation unit. The process management module adjusts the data exchange interval between the two modules according to the rate of change of the current pressure load. When the pressure load is in a rapidly changing, step-like rising or falling phase, the data exchange interval is shortened, for example, to once every 0.1 seconds, ensuring that pressure adjustment commands are transmitted in a timely manner. When the pressure load is in a stable intensity range, the data exchange interval is extended to once every 1 second to reduce unnecessary data interaction and save system resources. Through this dynamic adjustment, the synergy between pressure loading and feedback regulation is maintained, ensuring the stable progress of the testing process.

[0057] Upon entering the termination analysis phase, the process management module begins integrating the set of quantitative indicators with the digital twin of the testing process. The set of quantitative indicators includes multiple parameters such as the probability of seal failure, elastic deformation threshold, and the number of times the valve body crack warning signal is triggered. These parameters reflect the performance of the pressure reducing valve during the test from different perspectives. The digital twin of the testing process contains detailed information such as environmental parameter change curves throughout the test, the actual applied waveforms of the pressure load sequence, and valve core displacement trajectory data. The process management module summarizes and processes this data, tracing the correspondence between pressure load changes and the pressure reducing valve response in chronological order, and analyzing the failure mode characteristics of the pressure reducing valve under different environmental conditions. Based on this, a final test report is generated, including a pressure cycle durability graph. The graph visually displays the sealing performance change trend and structural fatigue degree of the pressure reducing valve under different pressure cycle numbers, presenting a complete picture of the test results.

[0058] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0059] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A pressure testing system for a pressure reducing valve, characterized in that, It includes an environmental parameter monitoring module, a test execution module, and a result analysis module; The environmental parameter monitoring module collects real-time temperature, humidity, and vibration intensity data of the environment where the pressure reducing valve is located, and transmits the temperature, humidity, and vibration intensity data sets to the test execution module. The test execution module initiates the pressure loading process based on the received environmental data set, applies a dynamically changing pressure load sequence to the pressure reducing valve through the hydraulic control device, and records the deformation response data of the pressure reducing valve at the same time. The result analysis module receives the deformation response data and performs multi-dimensional failure mode identification calculations to generate a test report containing leakage risk assessment parameters and structural fatigue coefficients. The leakage risk assessment parameters and structural fatigue coefficient test report are fed back to the test execution module for real-time adjustment of the pressure load sequence application strategy. The environmental parameter monitoring module includes a distributed sensor array and a data fusion unit; the distributed sensor array is deployed at the inlet port, outlet port and valve body surface of the pressure reducing valve, and simultaneously captures fluid pulsation frequency data, surface stress distribution data and environmental noise spectrum data; The data fusion unit uses a spatiotemporal alignment algorithm to timestamp the fluid pulsation frequency data, surface stress distribution data, and environmental noise spectrum data to generate a composite monitoring dataset with environmental labels. The composite monitoring dataset with environmental labels is used as the trigger condition for the pressure loading process and input to the test execution module. The test execution module includes a pressure gradient generation unit and a response capture unit. The pressure gradient generation unit divides the intensity range and duration range of the pressure load sequence based on the temperature data and vibration intensity data in the composite monitoring dataset with environmental labels, and generates a stepped pressure waveform by controlling the hydraulic oil flow through a proportional servo valve. The response capture unit uses a laser displacement sensor array to collect the displacement trajectory data of the pressure reducing valve core and simultaneously records the hydraulic pipeline pressure oscillation data, integrating them into a time-aligned deformation response data stream and transmitting it to the result analysis module. The result analysis module includes a signal reconstruction unit and a failure feature library. The signal reconstruction unit performs wavelet packet decomposition filtering on the deformation response data stream to extract the high-frequency components and low-frequency drift components of the valve core motion, and reconstructs a pure response signal free of environmental noise. The failure feature library stores time-domain waveform templates of typical pressure reducing valve failure modes. The pure response signal is dynamically time-warped and matched with the waveform templates to output a set of quantitative indicators including the probability of sealing failure and the elastic deformation threshold.

2. The pressure testing system for a pressure reducing valve according to claim 1, characterized in that, The system also includes a test preparation module; the test preparation module receives humidity data and noise spectrum data from the composite monitoring dataset with environmental labels, calculates the environmental interference intensity index, and activates the device self-test protocol when the environmental interference intensity index exceeds a preset threshold; the device self-test protocol drives the hydraulic control device to perform zero-point drift calibration and sensor sensitivity verification, generates a device health status code, and embeds initial control commands of the pressure load sequence.

3. The pressure testing system for a pressure reducing valve according to claim 2, characterized in that, The system includes a data storage center; the data storage center establishes an environmental parameter database, a load application database, and a response characteristic database. The environmental parameter database stores time-slice data of the composite monitoring dataset in real time; the load application database records waveform parameters of the pressure load sequence and servo valve control commands; the response feature database stores the pure response signal and the set of quantitative indicators in association, forming a traceable digital twin of the test process.

4. The pressure testing system for a pressure reducing valve according to claim 3, characterized in that, The result analysis module also includes an anomaly detection unit; the anomaly detection unit performs sliding time window sampling on the deformation response data stream and calculates the statistical characteristic difference between adjacent windows; when the difference exceeds the preset safety boundary, the emergency matching mode of the failure feature library is triggered, and the valve body crack warning signal and pressure release command are output to the test execution module in real time.

5. The pressure testing system for a pressure reducing valve according to claim 4, characterized in that, The system includes a feedback control module; the feedback control module receives the seal failure probability and the valve body crack warning signal from the set of quantitative indicators, and calculates the pressure safety attenuation coefficient; the pressure safety attenuation coefficient is converted into the flow suppression gradient parameter of the proportional servo valve, dynamically compressing the intensity range of the pressure load sequence to form a closed-loop pressure regulation mechanism.

6. The pressure testing system for a pressure reducing valve according to claim 5, characterized in that, The data storage center is also associated with a test logic engine; the test logic engine calls the historical pure response signals and the current set of quantitative indicators in the response feature database to execute the pressure loading mode iterative algorithm; the pressure loading mode iterative algorithm generates an optimized set of stepped pressure waveform parameters to replace the original pressure load sequence division rules in the test execution module.

7. The pressure testing system for a pressure reducing valve according to claim 6, characterized in that, The system includes a process management module; the process management module is divided into an initial preparation phase, a main testing phase, and a termination analysis phase; in the initial preparation phase, the device health status code is called to verify the system integrity. During the main testing phase, coordinate the data exchange frequency between the pressure gradient generation unit and the feedback control module; During the termination analysis phase, the set of quantitative indicators is integrated with the digital twin of the testing process to generate a final test report containing a pressure cycle durability graph.

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