A method and system for detecting leakage of a positive pressure helium detection valve

Abstract

The application provides a positive pressure helium detection valve internal leakage detection method and system, relates to the valve sealing performance detection technical field, and the method comprises the following steps: applying a test gas with a rated working pressure to a valve to be tested, monitoring the internal pressure change of the valve in real time under the rated working pressure, and performing positive pressure internal leakage pre-detection; if the pressure remains stable, a pre-detection passing judgment result is obtained, and if the pressure fluctuation exceeds a set threshold value, the test is terminated and an alarm signal is sent out; based on the pre-detection passing judgment result, the temperature condition of the valve to be tested is controlled during the continuous application of the test gas, the positive pressure internal leakage test is repeatedly performed under different temperatures, the basic leakage rate at each temperature point is recorded, and an initial dynamic sealing performance curve is obtained. The application can realize accurate correction and multi-dimensional data fusion of valve leakage detection data, and improve the accuracy of internal leakage detection of the valve under temperature alternating conditions.

Description

Technical Field

[0001] This invention relates to the field of valve sealing performance testing technology, and in particular to a method and system for detecting internal leakage in positive pressure helium-sealed valves. Background Technology

[0002] In the field of industrial valve sealing performance testing, positive pressure helium testing technology has become the mainstream technical means for detecting internal leaks in valves due to the tracer properties of helium. It is widely used in fields such as energy and aerospace where valve sealing reliability requirements are stringent.

[0003] Existing positive-pressure helium detection methods for valve internal leakage, when simulating valve temperature conditions, rely solely on pressure monitoring and helium mass spectrometry to obtain leakage rate data. This approach generally suffers from the following technical shortcomings: it fails to consider the impact of temperature-induced geometric deformation of the valve's sealing interface on the leakage rate detection results. Because the obtained leakage rate data is uncorrected raw data, it's difficult to distinguish whether the leakage rate change is caused by actual valve sealing performance failure or by geometric deformation due to thermal expansion and contraction of the sealing interface. This leads to a discrepancy between the leakage rate detection results and the valve's actual sealing state, making it difficult to accurately quantify even minor internal leaks. Furthermore, the sealing performance curve generated based on the raw leakage rate data cannot accurately reflect the actual sealing behavior of the valve under alternating temperature conditions. Using this curve to predict the long-term leakage trend of the valve is prone to misjudgment, potentially creating hidden safety hazards.

[0004] Meanwhile, existing detection methods also have the problem of not effectively integrating the basic leakage rate data of positive pressure internal leakage pre-detection with the leakage rate data of helium mass spectrometry leak detection. The detection data is only output in a single dimension, making it difficult to form a temperature-leakage rate correlation analysis curve, and it is also difficult to effectively characterize the evolution of valve sealing performance under temperature changes from a dynamic perspective, thus reducing the reference value of the detection data for valve operation and maintenance decisions. Summary of the Invention

[0005] This invention provides a method and system for detecting internal leakage in positive pressure helium-sealed valves. It can achieve accurate correction of valve leakage rate detection data and multi-dimensional data fusion, improve the accuracy of internal leakage detection of valves under temperature alternation conditions, and provide a basis for valve sealing performance evaluation and long-term leakage trend prediction.

[0006] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows:

[0007] Firstly, a method for detecting internal leakage in a positive pressure helium detection valve, the method comprising:

[0008] Test gas at the rated working pressure is applied to the valve under test. The pressure change inside the valve is monitored in real time under the rated working pressure to perform positive pressure internal leakage pre-inspection. If the pressure remains stable, the result of passing the pre-inspection is obtained. If the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued.

[0009] Based on the results of the pre-inspection, the temperature conditions of the valve under test are controlled during the continuous application of test gas. The positive pressure internal leakage test is repeated at different temperatures, and the basic leakage rate at each temperature point is recorded to obtain the initial dynamic sealing performance curve of leakage rate as a function of temperature.

[0010] During the testing at various temperature points, multiple characteristic spatial markers are simultaneously deployed at the sealing interface on the outer surface of the valve. The three-dimensional spatial coordinates of each characteristic spatial marker are collected in real time to fit a spatial closed surface. The surface deformation rate of the spatial closed surface relative to the initial state is calculated to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

[0011] At each temperature point, the outer surface of the valve is scanned using helium mass spectrometry to capture tracer gas molecules that are leaking out. Helium mass spectrometry leak detection is then performed to obtain the original leak rate detection data at the corresponding temperature point.

[0012] Using the geometric fidelity coefficient at the same temperature point as a correction factor, the original leakage rate detection data at the corresponding temperature point is compensated and corrected according to the compensation correction function that is positively correlated with the geometric fidelity coefficient, and the corrected leakage rate detection result is obtained. The corrected leakage rate detection result at each temperature point is fused with the initial dynamic sealing performance curve, that is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original basic leakage rate value at the corresponding temperature point in the initial dynamic sealing performance curve, and smooth interpolation is performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, thus completing the output of the test results.

[0013] Furthermore, test gas at the rated working pressure is applied to the valve under test, and after the pressure stabilizes, the internal pressure change of the valve is monitored in real time at the rated working pressure to perform a positive pressure internal leakage pre-test. If the pressure remains stable, the pre-test is passed; if the pressure fluctuation exceeds a set threshold, the test is terminated and an alarm signal is issued, including:

[0014] Test gas is introduced into the valve under test until the internal pressure of the valve reaches the rated working pressure. After the rated working pressure is reached, the gas introduction is stopped to obtain the initial stable pressure value.

[0015] Based on the initial stable pressure value, the internal pressure data of the valve is continuously collected, and the pressure fluctuation amplitude between the current pressure value and the initial stable pressure value is calculated in real time with a preset sampling period.

[0016] The pressure fluctuation amplitude is compared with a set threshold. If the pressure fluctuation amplitude is always lower than the set threshold during the preset monitoring period, the pressure is determined to be stable, and the pre-test is passed. If the pressure fluctuation amplitude exceeds the set threshold during the preset monitoring period, the pressure fluctuation is determined to be outside the allowable range, the test is terminated immediately, and an alarm signal is output.

[0017] Furthermore, based on the pre-inspection results, during the continuous application of test gas, the temperature conditions of the valve under test are controlled, and the positive pressure internal leakage test is repeatedly performed at different temperatures. The baseline leakage rate at each temperature point is recorded, and the initial dynamic sealing performance curve of leakage rate as a function of temperature is obtained, including:

[0018] After obtaining the result of passing the pre-inspection, maintain the internal test gas pressure of the valve at the rated working pressure and set the temperature control sequence; wherein, the temperature control sequence includes multiple target temperature points that increase or decrease according to preset step size;

[0019] The ambient temperature of the valve is adjusted to each target temperature point in turn. After thermal equilibrium is reached at each target temperature point, the pressure decay data of the valve's internal pressure over time is continuously collected.

[0020] Based on the pressure decay data collected at each target temperature point, the basic leakage rate corresponding to this temperature point is calculated, and the correspondence between each target temperature point and the basic leakage rate is obtained.

[0021] Using the target temperature point as the x-axis and the basic leakage rate as the y-axis, the basic leakage rate at each target temperature point is curve-fitted to form the initial dynamic sealing performance curve of leakage rate as a function of temperature.

[0022] Furthermore, multiple characteristic spatial markers are simultaneously deployed at the sealing interface on the outer surface of the valve. The three-dimensional spatial coordinates of each characteristic spatial marker are collected in real time to fit a spatial closed surface. The surface deformation rate of the spatial closed surface relative to the initial state is calculated to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature, including:

[0023] The temperature control sequence that has been set for the valve under test is retrieved from the control terminal. Before performing the positive pressure internal leakage test at each target temperature point, the initial three-dimensional spatial coordinates of multiple characteristic spatial markers at the sealing interface on the outer surface of the valve are collected. The characteristic spatial markers are located in the contact ring area between the valve seat sealing surface and the valve disc, as well as the circumferential area at the junction of the valve stem and the stuffing box.

[0024] During the positive pressure internal leakage test at each target temperature point, once the target temperature point reaches thermal equilibrium, the real-time three-dimensional spatial coordinates of the same set of characteristic spatial markers at the current temperature are simultaneously collected.

[0025] The real-time three-dimensional spatial coordinates collected at the current temperature are spatially matched with the initial three-dimensional spatial coordinates to fit the initial spatial closed surface and the current spatial closed surface respectively.

[0026] Calculate the surface deformation rate of the current spatial closed surface relative to the initial spatial closed surface, and use the surface deformation rate as the geometric fidelity coefficient of the sealing interface at the current target temperature point to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

[0027] Furthermore, at each temperature point, helium mass spectrometry was used to scan the outer surface of the valve to capture tracer gas molecules escaping from the leak, obtaining the raw leak rate detection data at the corresponding temperature point, including:

[0028] Obtain the geometric fidelity coefficient of the sealing interface at each target temperature. For each target temperature, after performing a positive pressure internal leak test at this temperature and reaching thermal equilibrium, start the helium mass spectrometry leak detection process.

[0029] The device moves along a preset scanning path on the outer surface of the valve to continuously scan the outer surface of the valve in order to capture the concentration signal of tracer gas molecules escaping from the leak point in real time.

[0030] The captured tracer gas molecule concentration signal is converted into a leak rate value to obtain the raw leak rate detection data at the current temperature point;

[0031] The original leak rate detection data at the current temperature point is associated with the geometric fidelity coefficient at this temperature point and stored to form a correspondence between each target temperature point and the original leak rate detection data.

[0032] Furthermore, using the geometric fidelity coefficient at the same temperature point as a correction factor, the original leakage rate detection data at the corresponding temperature point is compensated and corrected according to the compensation correction function positively correlated with the geometric fidelity coefficient, resulting in a corrected leakage rate detection result. The corrected leakage rate detection results at each temperature point are then fused with the initial dynamic sealing performance curve. That is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original baseline leakage rate value at the corresponding temperature point in the initial dynamic sealing performance curve. Smooth interpolation is then performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, completing the output of the test results, including:

[0033] The correspondence between each target temperature point and the original leak rate detection data is obtained, and the initial dynamic sealing performance curve is obtained at the same time.

[0034] For each target temperature point, the original leak rate detection data and the corresponding geometric fidelity coefficient at this temperature point are extracted. The geometric fidelity coefficient is used as a correction factor, and the original leak rate detection data is compensated and corrected according to the compensation correction function that is positively correlated with the geometric fidelity coefficient to obtain the corrected leak rate detection result at the temperature point.

[0035] The corrected leakage rate detection results at each target temperature point are fused with the initial dynamic sealing performance curve under the same temperature coordinate. That is, the corrected leakage rate detection results are used as the true leakage rate at that temperature point, replacing the original basic leakage rate value of the corresponding temperature point in the initial dynamic sealing performance curve. Smooth interpolation is performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve.

[0036] The temperature-corrected leak rate correlation curve is output as the test result.

[0037] Secondly, a detection system for internal leakage of a positive pressure helium detection valve includes:

[0038] The positive pressure internal leakage pre-inspection module is used to apply test gas at the rated working pressure to the valve under test. It monitors the pressure change inside the valve in real time under the rated working pressure and performs positive pressure internal leakage pre-inspection. If the pressure remains stable, the result of passing the pre-inspection is obtained. If the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued.

[0039] The dynamic operating condition simulation module is used to control the temperature conditions of the valve under test during the continuous application of test gas based on the judgment results of passing the pre-inspection. It repeatedly performs positive pressure internal leakage test at different temperatures, records the basic leakage rate at each temperature point, and obtains the initial dynamic sealing performance curve of leakage rate as a function of temperature.

[0040] The sealing interface deformation detection module is used to simultaneously deploy multiple characteristic spatial markers at the sealing interface on the outer surface of the valve, collect the three-dimensional spatial coordinates of each characteristic spatial marker in real time, fit them into a spatial closed surface, calculate the surface deformation rate of the spatial closed surface relative to the initial state, and obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

[0041] The helium mass spectrometry leak detection module is used to perform helium mass spectrometry leak detection at various temperature points, scan the outer surface of the valve, capture the tracer gas molecules that escape from the leak, and obtain the raw leak rate detection data at the corresponding temperature point.

[0042] The data processing and fusion module is used to compensate and correct the original leakage rate detection data at the corresponding temperature point using the geometric fidelity coefficient at the same temperature point as a correction factor, to obtain the corrected leakage rate detection result. The corrected leakage rate detection result at each temperature point is then fused with the initial dynamic sealing performance curve. That is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original basic leakage rate value at the corresponding temperature point in the initial dynamic sealing performance curve. Smoothing interpolation is then performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, thus completing the output of the test results.

[0043] Thirdly, a computing device includes:

[0044] One or more processors;

[0045] 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.

[0046] Fourthly, a computer-readable storage medium storing a program that, when executed by a processor, implements the method.

[0047] The above-described solution of the present invention has at least the following beneficial effects:

[0048] By introducing a dynamic detection and correction mechanism for the geometric fidelity coefficient of the sealing interface, and by multi-dimensionally fusing the corrected leakage rate data with the initial dynamic sealing performance curve, the following beneficial effects were achieved: Because the three-dimensional spatial coordinates of characteristic spatial markers at the sealing interface on the outer surface of the valve are simultaneously acquired during temperature testing, and a closed spatial surface is fitted to calculate the surface deformation rate and obtain the geometric fidelity coefficient, the technical deficiency of existing technologies—the inability to distinguish whether leakage rate changes are caused by sealing performance failure or by geometric deformation due to thermal expansion and contraction—is overcome. This achieves accurate compensation and correction of the original helium mass spectrometry leakage rate data, effectively improving the quantitative assessment accuracy of minute internal leaks. Furthermore, by fusing the corrected leakage rate detection results with the initial dynamic sealing performance curve under the same temperature coordinates, the technical problem of existing methods only outputting single-dimensional data and difficulty in forming temperature-leakage correlation analysis is overcome. This generates a temperature-corrected leakage rate correlation curve that truly reflects the evolution of the valve's sealing performance under alternating temperature conditions, providing a reliable data foundation for accurate prediction of long-term valve leakage trends and maintenance decisions. Attached Figure Description

[0049] Figure 1 This is a schematic flowchart of a method for detecting internal leakage in a positive pressure helium detection valve, provided by an embodiment of the present invention.

[0050] Figure 2 This is a schematic diagram of a positive pressure helium detection valve internal leakage detection system provided by an embodiment of the present invention. Detailed Implementation

[0051] 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 so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0052] like Figure 1 As shown, an embodiment of the present invention proposes a method for detecting internal leakage in a positive pressure helium detection valve, the method comprising the following steps:

[0053] Step 1: Apply test gas at the rated working pressure to the valve under test, and monitor the pressure change inside the valve in real time under the rated working pressure to perform positive pressure internal leakage pre-inspection; if the pressure remains stable, the result of passing the pre-inspection is obtained; if the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued.

[0054] Step 2: Based on the judgment result of passing the pre-inspection, during the continuous application of test gas, control the temperature conditions of the valve under test, repeat the positive pressure internal leakage test at different temperatures, record the basic leakage rate at each temperature point, and obtain the initial dynamic sealing performance curve of leakage rate changing with temperature.

[0055] Step 3: During the test at each temperature point, multiple characteristic spatial markers are simultaneously set up at the sealing interface on the outer surface of the valve. The three-dimensional spatial coordinates of each characteristic spatial marker are collected in real time to fit a spatial closed surface. The surface deformation rate of the spatial closed surface relative to the initial state is calculated to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

[0056] Step 4: At each temperature point, the outer surface of the valve is scanned using helium mass spectrometry to capture the tracer gas molecules that are leaking out. Helium mass spectrometry leak detection is then performed to obtain the original leak rate detection data at the corresponding temperature point.

[0057] Step 5: Using the geometric fidelity coefficient at the same temperature point as a correction factor, the original leakage rate detection data at the corresponding temperature point is compensated and corrected according to the compensation correction function that is positively correlated with the geometric fidelity coefficient, and the corrected leakage rate detection result is obtained. The corrected leakage rate detection results at each temperature point are fused with the initial dynamic sealing performance curve, that is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original basic leakage rate value of the corresponding temperature point in the initial dynamic sealing performance curve, and smooth interpolation is performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, and the test results are output.

[0058] In this embodiment of the invention, by simultaneously acquiring the three-dimensional spatial coordinates of the sealing interface under multiple temperature conditions to calculate the surface deformation rate and generate the geometric fidelity coefficient, dynamic compensation and correction of the original helium mass spectrometry leak rate data is achieved. This effectively eliminates the interference of the geometric deformation of the sealing interface caused by temperature changes on the leak rate detection results, and effectively improves the quantitative assessment accuracy of minor internal leaks of the valve under alternating temperature conditions. At the same time, by fusing the corrected leak rate detection results with the initial dynamic sealing performance curve, a temperature-corrected leak rate correlation curve is constructed, realizing the multi-dimensional integration of positive pressure internal leak pre-detection data and helium mass spectrometry leak detection data. This reasonably presents the dynamic law of valve sealing performance evolution with temperature, providing reliable data support for accurate prediction of valve leakage trends and operation and maintenance decisions during long-term operation.

[0059] In a preferred embodiment of the present invention, step 1 above may include:

[0060] Step 1.1: Inflate the valve under test with test gas until the internal pressure reaches the rated working pressure, and stop inflating after reaching the rated working pressure to obtain an initial stable pressure value. Specifically, this includes: inflating the valve under test with test gas, wherein the test gas is helium or a mixture of helium and nitrogen, with helium used as a tracer medium for subsequent leak detection; during the inflation process, monitor the internal pressure of the valve in real time and compare the monitored pressure value with the preset rated working pressure; wherein the preset rated working pressure is determined according to the actual operating conditions of the valve under test, specifically the maximum working pressure value that the valve can withstand under normal operating conditions; when the internal pressure of the valve is detected to rise to the rated working pressure, immediately control the proportional regulating valve to close, cut off the gas supply, and stop the inflation action; After inflation stops, a pressure stabilization waiting phase begins. The preset stabilization waiting time is pre-set based on the valve volume and the properties of the test gas to eliminate pressure fluctuations caused by gas molecule movement and temperature changes after inflation. During the preset stabilization waiting time, the internal pressure changes of the valve are continuously monitored. Once the pressure fluctuation amplitude is continuously lower than the set pressure change rate threshold and the duration reaches the preset stabilization waiting time, it is determined that the internal pressure of the valve has stabilized. The pressure value collected at this time is recorded as the initial stable pressure value. This initial stable pressure value serves as the benchmark reference value for judging pressure fluctuations. It should be noted that the pressure in this step refers to the pressure inside the valve reaching the rated working pressure and the pressure fluctuation stabilizing within the allowable range. Subsequent pressure monitoring is performed under this stable pressure condition.

[0061] Step 1.2: Based on the initial stable pressure value, continuously collect internal pressure data of the valve, and simultaneously calculate the pressure fluctuation amplitude between the current pressure value and the initial stable pressure value in real time at a preset sampling period. Specifically, this includes: after recording the initial stable pressure value, starting a pressure monitoring timer and setting a sampling period. The sampling period is determined comprehensively based on the volume of the valve under test, the diffusion rate of the test gas, and the order of magnitude of the expected leakage rate, specifically a fixed time interval used to control the frequency of pressure acquisition; at the end of each sampling period, triggering a pressure acquisition action through a pressure sensor to obtain the real-time pressure value at the current moment; at the end of each sampling period, comparing the acquired real-time pressure value with the initial stable pressure value, and calculating the absolute difference between the two. The calculation process for the absolute difference is as follows: first, read the real-time pressure value and the initial stable pressure value, then calculate the difference between the real-time pressure value and the initial stable pressure value, then take the absolute value of this difference as the pressure fluctuation amplitude, and finally associate the calculated pressure fluctuation amplitude with the timestamp corresponding to the sampling period to form a set of monitoring data containing time information and fluctuation amplitude.

[0062] Step 1.3: Compare the pressure fluctuation amplitude with a set threshold. If the pressure fluctuation amplitude is consistently lower than the set threshold within the preset monitoring period, the pressure is determined to be stable, and the pre-test is passed. If the pressure fluctuation amplitude exceeds the set threshold within the preset monitoring period, the pressure fluctuation is determined to be outside the allowable range, and the test is immediately terminated, with an alarm signal output. Specifically, this includes: calculating the pressure fluctuation amplitude in each sampling cycle and comparing it with a preset allowable fluctuation threshold. The preset allowable fluctuation threshold is pre-calibrated based on the sealing accuracy level and allowable leakage rate requirements of the valve under test. Specifically, it is the maximum allowable pressure attenuation of the valve under rated working pressure. This preset allowable fluctuation threshold is obtained by converting the allowable leakage rate into a pressure change, and is used to distinguish whether the valve is in a stable sealing state or has significant leakage. If the pressure fluctuation amplitude of the current sampling cycle is lower than the allowable fluctuation threshold, it is determined that there is no abnormal leakage in the current sampling cycle, and the monitoring of the next sampling cycle continues.

[0063] If the pressure fluctuation amplitude of the current sampling period exceeds the allowable fluctuation threshold, the valve is determined to have a leak exceeding the allowable range. The monitoring process is immediately interrupted and the test is terminated, and an alarm signal is output. The alarm signal includes pressure over-limit information, the sampling period number corresponding to the time of over-limit, and the current pressure fluctuation amplitude, which is used to prompt the operator to check the valve installation status or whether there are obvious defects on the sealing surface. At the same time, a continuous monitoring period is set. The continuous monitoring period is determined comprehensively based on the valve volume, the properties of the test gas, and the temperature stabilization time required for subsequent dynamic testing. Specifically, it is the complete time interval from the start of pressure stabilization monitoring after the gas filling stops to the end of the pre-inspection. If the pressure fluctuation amplitude calculated for all sampling periods is lower than the allowable fluctuation threshold during the continuous monitoring period, the valve internal pressure is determined to remain stable throughout the monitoring process, and a pre-inspection pass result is generated. This result serves as the starting condition for triggering the subsequent dynamic testing process.

[0064] In a preferred embodiment of the present invention, step 2 above may include:

[0065] Step 2.1: After obtaining the pre-inspection result, maintain the internal test gas pressure of the valve at the rated working pressure and set the temperature control sequence. The temperature control sequence includes multiple target temperature points that increase or decrease according to preset step sizes. Specifically, after obtaining the positive pressure internal leakage pre-inspection result, immediately initiate the constant pressure holding control process for the valve's internal pressure. A pressure closed-loop control circuit is formed through a proportional regulating valve and a pressure sensor connected to the gas path of the valve under test. The pressure sensor collects the valve's internal pressure data in real time at a sampling frequency of 10Hz and feeds it back to the control terminal. When the detected pressure value is lower than the rated working pressure, the control terminal controls the proportional regulating valve to open slightly, supplementing the valve with test gas. When the pressure value recovers to the rated working pressure, the proportional regulating valve immediately closes. Throughout the process, the pressure fluctuation of the test gas inside the valve is controlled within the range set during the pre-inspection stage. Within the allowable fluctuation threshold, ensure that the pressure environment of subsequent temperature condition simulation tests is completely consistent with the rated working pressure of the valve in actual industrial operation, and that the pressure state remains stable. Determine the actual working temperature range of the valve under test based on its actual application field, and then set a temperature control sequence within this temperature range in combination with the accuracy requirements of valve sealing performance testing. The temperature control sequence includes multiple target temperature points that increase or decrease according to a preset step size. The preset step size is determined comprehensively based on the thermal expansion and contraction characteristics of the valve sealing surface material and the sensitivity of the sealing performance to temperature. The temperature difference between two adjacent target temperature points is kept equal, and the values ​​of all target temperature points strictly fall within the safe working temperature range designed for the valve. At the same time, it covers the low temperature, normal temperature, and high temperature key operating conditions in the actual operation of the valve, ensuring that the temperature conditions simulated by the temperature control sequence closely match the actual operating state of the valve, with no operating conditions omitted.

[0066] Step 2.2: Sequentially adjust the ambient temperature of the valve to each target temperature point. After thermal equilibrium is reached at each target temperature point, continuously collect pressure decay data of the valve's internal pressure over time. Specifically, this includes: initiating a gradient temperature control process based on a pre-set temperature control sequence, adjusting the ambient temperature of the valve under test at a temperature rise / fall rate of 5℃ / min. Uniform gradient temperature control avoids additional thermal stress on the valve sealing interface and valve body structure caused by sudden temperature changes, preventing deformation of the sealing interface caused by non-operating factors, and ensuring consistency between the test results and actual operating conditions. For each target temperature point in the temperature control sequence, after the ambient temperature is adjusted to the target temperature value, maintain a stable temperature output and enter a thermal equilibrium waiting phase. During the waiting phase, synchronously collect temperature data at multiple points on the valve sealing interface and valve body sidewall. The sampling frequency is 5Hz. When the deviation between the sampled temperature and the target temperature value of all points does not exceed ±1℃ within 5 consecutive minutes, and the temperature data fluctuation of each point does not exceed ±0.5℃, the target temperature point is determined to have reached thermal equilibrium. At this time, the valve body and the surrounding environment have completed complete heat exchange. When the valve is in thermal equilibrium at the target temperature, the closed-loop constant pressure control of the test gas pressure inside the valve is continuously maintained. At the same time, the internal pressure of the valve is continuously sampled at a fixed sampling period of 2Hz, and the continuous value of pressure change over time is recorded. Each sampled pressure value is associated with the corresponding sampling timestamp to form complete pressure decay data at the target temperature. This data is continuous time-series monitoring data containing time independent variables and pressure dependent variables, ensuring that there is no missing or interrupted data throughout the process.

[0067] Step 2.3: Based on the pressure decay data collected at each target temperature point, calculate the basic leakage rate corresponding to that temperature point, and obtain the correspondence between each target temperature point and the basic leakage rate. Specifically, this includes: for the pressure decay data collected at each target temperature point, using 3... σ Outlier removal criteria: Calculate the average value of the pressure decay data. and standard deviation It will exceed Pressure values ​​within a certain range are identified as abnormal fluctuations and discarded to ensure the accuracy of the data source for calculating the basic leakage rate and to eliminate pressure data deviations caused by minor external interference. Then, combined with the internal cavity volume of the valve under test, the basic leakage rate corresponding to the target temperature point is calculated. The formula for calculating the basic leakage rate is:

[0068]

[0069] In the formula, The base leakage rate at the target temperature point, in units of ; The volume of the internal cavity of the valve under test is expressed in cubic meters. This value is a fixed value and is an inherent structural parameter of the valve under test. The pressure change inside the valve within a preset monitoring period, measured in Pascals (Pa), is the initial pressure value after removing outliers from the pressure decay data. With end pressure value The absolute difference is obtained, that is ; T This is the thermodynamic temperature of the target temperature point, in Kelvin (K), obtained by adding 273.15 to the Celsius temperature value t of the target temperature point. T =t+273.15; The preset monitoring time, in seconds (s), represents the effective acquisition time span after removing outliers from the pressure decay data, set to 300s to 1800s based on the valve volume. Following the aforementioned formulas and parameter definitions, the baseline leakage rate is calculated for each target temperature point in the temperature control sequence. The Celsius temperature value of each target temperature point is then correlated with the corresponding calculated baseline leakage rate value, forming a structured table showing the correspondence between target temperature points and baseline leakage rates. This table includes the target temperature (°C), thermodynamic temperature (K), pressure change (Pa), and baseline leakage rate (...). Key columns such as ) are recorded with data accurate to 6 decimal places.

[0070] Step 2.4: Using the target temperature point as the abscissa and the basic leakage rate as the ordinate, perform curve fitting on the basic leakage rate at each target temperature point to form an initial dynamic sealing performance curve showing the leakage rate changing with temperature. Specifically, this includes: constructing a two-dimensional rectangular coordinate system, using the target temperature point in the temperature control sequence as the abscissa, with the scale unit being degrees Celsius (°C). The range of values ​​on the abscissa covers the minimum to maximum target temperature value of the temperature control sequence, and the scale interval is consistent with the preset step size of the temperature control sequence; and using the basic leakage rate corresponding to each target temperature point as the ordinate, with the scale unit being Pa. m 3 / s, the range of values ​​for the vertical axis is reasonably set according to the calculated range of the basic leakage rate, ensuring that all data points can be clearly presented in the coordinate system without scale congestion or data overflow; the corresponding data of each target temperature point and the basic leakage rate are used as scatter points and accurately marked in the constructed two-dimensional coordinate system. The horizontal and vertical axes of each scatter point correspond to a unique target temperature value and a basic leakage rate value, respectively. At the same time, each scatter point is numbered and matched one by one with the data items in the corresponding relationship table to ensure the accuracy of data traceability.

[0071] After completing the scatter point labeling, the least squares method is used to perform curve fitting on all labeled scatter points. During the fitting process, based on the actual distribution trend of the scatter points, a quadratic polynomial function model is selected as the basic model for fitting. The specific expression of the quadratic polynomial function model is as follows:

[0072] ;

[0073] in, The dependent variable is the baseline leakage rate at the corresponding temperature point, expressed in Pa. m 3 / s; is the independent variable, representing the Celsius temperature value of the target temperature point, with the unit being degrees Celsius (°C). For the constant term of the polynomial, it represents the theoretical fitted value of the basic leakage rate at a temperature of 0℃; The coefficients of the first-order term of the polynomial represent the rate at which the basic leakage rate changes linearly with temperature; The coefficients of the quadratic term in the polynomial represent the curvature of the basic leakage rate as a function of temperature, reflecting the nonlinear characteristics of the leakage rate with temperature variation; the above coefficients All values ​​were determined through iterative calculation using the least squares method. During the fitting process, minimizing the sum of squared residuals was the optimization objective. The specific formula for calculating the sum of squared residuals is as follows:

[0074] ;

[0075] In the formula The sum of squared residuals represents the overall deviation between the actual values ​​and the fitted values ​​of all scattered points; n This represents the total number of scatter points, i.e., the number of target temperature points in the temperature control sequence; i The index of the scatter plot is 1 to 1. n ; For the first i The actual base leakage rate value of each scatter point, that is, the base leakage rate calculated by step 2.3; For the first i The fitted baseline leakage rate values ​​for each scatter point are calculated using a polynomial function model, i.e. ,in For the first i The target temperature values ​​for each scattered point.

[0076] Temperature values ​​of all scatter points Compared with the actual baseline leakage rate value Substituting into the above formula, the sum of squared residuals is obtained through iterative solution. The coefficient that takes the minimum value The optimal fitting function is obtained to ensure that the deviation between the fitted curve and each scatter point is minimized, and the actual test data is matched to the greatest extent. The smooth curve obtained by the final fitting is determined as the initial dynamic sealing performance curve of the leakage rate of the valve under test as a function of temperature. This curve can intuitively and continuously reflect the overall trend of the valve's basic leakage rate with temperature under rated working pressure. Moreover, any point on the curve corresponds to a unique temperature value and basic leakage rate value. The reference value of the basic leakage rate corresponding to any intermediate temperature point in the temperature control sequence can be obtained by interpolation of this curve, providing complete basic data support for the fusion of test data.

[0077] In a preferred embodiment of the present invention, step 3 above may include:

[0078] Step 3.1: Retrieve the temperature control sequence pre-set for the valve under test from the control terminal. Before performing the positive pressure internal leakage test at each target temperature point, collect the initial three-dimensional spatial coordinates of multiple characteristic spatial markers at the sealing interface of the valve's outer surface. These characteristic spatial markers are located in the contact ring area between the valve seat sealing surface and the valve disc, and in the circumferential area at the junction of the valve stem and the stuffing box. Specifically, this includes: first, retrieving the temperature control sequence pre-set for the valve under test from the control terminal, accurately obtaining the number, specific values, and gradient adjustment sequence of all target temperature points to be tested within the sequence, and determining the test priority of each temperature point to prepare the preliminary process planning and data for the subsequent synchronous acquisition of the three-dimensional coordinates of the temperature points; before formally performing the positive pressure internal leakage test at each target temperature point, completing the standardized and regulated layout of the characteristic spatial markers at the sealing interface of the valve's outer surface; among them, the markers are preferably selected from highly reflective, high-temperature resistant, and non-displaceable hard markers that fit the sealing interface. The markers are small in size and do not protrude from the sealing interface surface to avoid interfering with the valve's sealing status and subsequent leak detection operations.

[0079] The contact ring area between the valve seat sealing surface and the valve disc is the core static sealing area of ​​the valve and the main area where internal leakage occurs. Thermal expansion and contraction caused by temperature changes directly lead to changes in the fit clearance of this ring area, and its geometric changes directly reflect the physical state of the valve's core sealing performance. The circumferential area at the junction of the valve stem and stuffing box is the key area for dynamic sealing. The fit clearance between the valve stem and stuffing box is easily deformed by temperature, making it a secondary high-risk area for internal leakage. Monitoring the geometric deformation of this area can completely cover the main leakage risk points at the valve sealing interface. Therefore, these two areas are the core layout areas for characteristic spatial markers. During layout, the contact ring area between the valve seat sealing surface and the valve disc is arranged at equal angles around the circumference. Marking points are laid out with the center of the ring as the center and the spacing of the marking points determined according to the circumference of the ring. The arc length of adjacent marking points is consistent. When the diameter of the ring is less than 100mm, no less than 12 marking points are laid out, and when the diameter of the ring is greater than or equal to 100mm, no less than 24 marking points are laid out. The circumferential area at the junction of the valve stem and the stuffing box is laid out with a combination of radial equal spacing and circumferential equal angle. Basic marking points are laid out at equal angles along the circumferential direction. At the same time, an additional set of marking points is added along the radial direction of the valve stem at the junction of the upper and lower end faces of the stuffing box. Each set of circumferential marking points has no less than 8 points. This ensures that the distribution density of the marking points can completely and accurately represent the overall geometric shape of the two sealing areas without missing any key deformation features.

[0080] After deployment, initial coordinates of all deployed characteristic spatial markers are acquired. During acquisition, the acquisition reference plane is kept strictly parallel to the valve sealing reference plane, the acquisition distance and angle are fixed, and the acquisition accuracy is controlled at the micrometer level. The spatial position of each marker is scanned and identified point by point, and the initial three-dimensional spatial coordinates of each marker are recorded point by point, uniformly denoted as... ,in j This is a unique index for the characteristic spatial markers, with a value ranging from 1 to a positive integer representing the total number of markers. The first j The initial three-dimensional spatial coordinates of each marker point are determined by their X, Y, and Z axial components. All initial coordinate data are then classified and stored in the system database after being associated with the marker point number and its corresponding deployment area. This data serves as the baseline raw data for subsequent calculations of the deformation of the sealing interface.

[0081] Step 3.2: During the positive pressure internal leakage test at each target temperature point, once the target temperature point reaches thermal equilibrium, the real-time three-dimensional spatial coordinates of the same set of characteristic spatial markers at the current temperature are simultaneously acquired. Specifically, this includes: executing the positive pressure internal leakage test procedure sequentially for each target temperature point according to the preset order of the temperature control sequence; during the test of a single target temperature point, first completing the gradient temperature control, temperature stabilization, and thermal equilibrium determination operations for that temperature point, maintaining the rated working pressure of the test gas inside the valve throughout the process; once it is determined through multi-point temperature monitoring data that the target temperature point has reached thermal equilibrium, the test continues... Under the premise of maintaining thermal equilibrium and stable pressure, the real-time three-dimensional spatial coordinate acquisition process of characteristic spatial markers is simultaneously initiated. During the acquisition process, the acquisition position, angle, and acquisition accuracy must be strictly kept consistent with the state when acquiring the initial three-dimensional spatial coordinates in step 3.1 to eliminate coordinate system deviations caused by changes in acquisition conditions and avoid introducing deformation errors caused by non-temperature factors. Using the same high-precision method as the initial acquisition, the coordinates of the same group of characteristic spatial markers set up in step 3.1 are acquired point by point at the current temperature, and the real-time three-dimensional spatial coordinates of each marker point at the current temperature are recorded point by point and uniformly denoted as... ,in i This is a unique serial number for the target temperature point, with a value ranging from 1 to the total number of target temperature points. j The serial numbers of the characteristic spatial markers correspond one-to-one with the serial numbers in step 3.1, with no mismatches. The first i At the target temperature point, the first j The axial components of the X, Y, and Z axes of the real-time three-dimensional spatial coordinates of each marker point are stored in the system database after all real-time coordinate data are associated with the target temperature point number and the marker point number, forming an associated data group with the corresponding initial coordinates.

[0082] Step 3.3 involves spatially matching the real-time 3D spatial coordinates acquired at the current temperature with the initial 3D spatial coordinates to fit the initial and current spatial closed surfaces, respectively. Specifically, this includes retrieving the initial 3D spatial coordinates of all stored characteristic spatial markers, categorized by marker point number. This is used as the reference coordinate set for spatial matching, and the coordinates are set according to the same marker point number and the first... i Retrieve the real-time three-dimensional spatial coordinates of the same set of markers for each target temperature point number. As a set of coordinates to be matched, both sets of coordinates retain the associated information such as the layout area and sequence number of the marked point, ensuring the one-to-one correspondence of the point cloud data and avoiding the problem of mismatched points; taking the fixed geometric features of the valve sealing interface (such as the center of the valve seat sealing surface and the valve stem axis) as the absolute spatial reference benchmark, the iterative nearest point coordinate registration algorithm is used to accurately match the two sets of coordinates in space.

[0083] The specific matching process is as follows: First, a coarse matching operation is performed. By extracting common geometric feature points from the two sets of coordinates, such as the center of the valve seat sealing surface and the center of the valve stem axis, the spatial correspondence between the two sets of coordinates is quickly established. The spatial position of the coordinate set to be matched is calibrated to eliminate obvious spatial translation and rotation deviations caused by slight equipment offsets and fine-tuning of the viewing angle during the acquisition process. This ensures that the spatial overlap of the two sets of coordinates reaches the set coarse matching threshold. Then, a fine matching operation is performed based on the coarse matching results. The spatial Euclidean distance between each marker point in the coordinate set to be matched and the corresponding marker point in the reference coordinate set is calculated point by point. By continuously iterating and adjusting the spatial attitude parameters of the coordinate set to be matched, the spatial Euclidean distance of each marker point is gradually reduced until the average Euclidean distance of all marker points converges to within the micron-level preset fine matching threshold of 1 to 5 microns. This preset fine matching threshold is pre-set according to the acquisition accuracy of the three-dimensional coordinates and the accuracy requirements of the sealing interface deformation detection. The iteration is stopped and the fine matching operation is completed. Finally, it is ensured that the initial three-dimensional spatial coordinates and the real-time three-dimensional spatial coordinates are in the same standard spatial coordinate system to eliminate various small spatial deviations generated during the acquisition process and ensure the complete comparability of the two sets of coordinate data in terms of spatial position and geometric dimension.

[0084] After spatial matching is completed and coordinates are unified, a triangulation surface fitting algorithm is used to fit closed surfaces to the two sets of coordinates. The fitting process and core algorithm parameters (including neighborhood search radius, triangular patch partitioning threshold, and interpolation step size) for the initial and real-time coordinates are kept completely consistent to ensure the comparability of the fitting results of the two closed surfaces at the algorithm level. Specifically, the fitting process is as follows: first, the initial 3D spatial coordinates of all marked points are used as the base point cloud; then, spatial neighborhood relations are retrieved from the base point cloud according to the set neighborhood search radius to determine the adjacent points of each marked point; finally, the adjacent points are determined according to the principles of non-collinearity and no overlap. The basic point cloud is meshed according to the principles of overlapping and full coverage. Three adjacent non-collinear marker points are used as a triangular facet unit. All marker points are connected sequentially to form a continuous, complete, and non-overlapping spatial triangular facet network, covering the entire area of ​​the valve sealing interface. The edges and junctions of the triangular facet network are smoothed. Linear interpolation is used to fill the tiny gaps between the triangular facets according to a preset interpolation step size, so that all triangular facets are seamlessly spliced ​​to form a complete, continuous, and smooth spatial closed surface. This initial spatial closed surface can completely and accurately represent the initial geometry of the sealing interface, and is uniformly denoted as […]. The geometry of the curved surface closely matches the actual geometric features of the initial state of the sealed interface, with no significant deviation.

[0085] For the iThe fitting process of real-time 3D spatial coordinates at a target temperature point is completely consistent with the initial coordinate fitting process and operating standards: The real-time 3D spatial coordinates of all marked points at that temperature are used as the point cloud to be fitted. Spatial neighborhood relations are retrieved using the same neighborhood search radius as the initial coordinate fitting. Meshization is completed using the same partitioning principle. Similarly, a spatial triangular patch network covering the same sealing interface area is constructed, with three adjacent non-collinear marked points as a triangular patch unit. After smoothing with the same parameters and linear interpolation for gap filling, all triangular patches are seamlessly spliced ​​to form a complete, continuous, and smooth spatial closed surface, which is the current spatial closed surface representing the actual geometric shape of the sealing interface at that temperature, and is uniformly denoted as... Throughout the fitting process, the fitting deviation was monitored in real time, and the division accuracy and interpolation error of the triangular patches were strictly controlled. This ensured that the spatial deviation between the fitted closed surface and the actual coordinates of each marked point was always kept within the range of coordinate acquisition accuracy, guaranteeing that the closed surface could accurately reflect the actual geometric shape of the sealing interface. The initial spatial closed surface... With the current closed surface in space All data are stored in a spatial region data format, containing complete information such as the three-dimensional geometric coordinates of all points on the surface and the topological relationships of the patches, providing reliable and comprehensive geometric basis data for the accurate calculation of the region deformation rate.

[0086] Step 3.4: Calculate the surface deformation rate of the current spatial closed surface relative to the initial spatial closed surface. Use the surface deformation rate as the geometric fidelity coefficient of the sealing interface at the current target temperature point to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature. Specifically, this includes: retrieving the fitted initial spatial closed surface. With the i Current spatial closed surface at each target temperature point The corresponding spatial region data, based on the three-dimensional geometric information of the two surfaces formed by splicing triangular facets, calculates their total surface area. The total surface area of ​​the initial spatial closed surface is denoted as... , No. i The total surface area of ​​the current closed surface in space at each target temperature point is denoted as . All units are in square meters; because the surface is constructed by a triangulation fitting algorithm, the surface area is calculated using the triangular facet accumulation method that matches this algorithm, and the total surface area of ​​the initial spatial closed surface is... The calculation formula is:

[0087] ;

[0088] In the formula, m The total number of spatial triangular facets after the initial spatial closed surface is subdivided is a fixed positive integer; kThe unique index of the triangular facet on the initial spatial closed surface, with a value ranging from 1 to 1. m Positive integers; For the first closed surface in the initial space k The two spatial edge vectors of a triangular facet are determined by the initial three-dimensional spatial coordinates of the facet's three vertices. Calculated; for and The cross product of the lengths represents the area of ​​the parallelogram spanned by the two side vectors, in square meters. The accumulation symbol represents the sum from the 1st to the 2nd. m The areas of the triangular facets are summed sequentially; the... i The total surface area of ​​the current closed surface in space at each target temperature point The calculation formula is:

[0089] ;

[0090] in, m This represents the total number of spatial triangular faces after the current spatial closed surface is subdivided, which is exactly the same as the number of triangular faces of the initial spatial closed surface. k It is a unique index of the triangular facet on the current spatial closed surface, which is matched one by one with the index of the triangular facet on the initial spatial closed surface; , For the current closed surface in space, the first k The two spatial edge vectors of a triangular facet are derived from the real-time three-dimensional spatial coordinates of the facet's three vertices. Calculated; for and The cross product of the modulus is in square meters; the meanings of the remaining characters are the same as... The calculation formulas are exactly the same.

[0091] The above formulas are used to accurately calculate the total surface area of ​​the two surfaces, ensuring the compatibility of the calculation process with the surface fitting algorithm and guaranteeing the accuracy of the calculation results. Based on the calculated surface areas, the deformation rate of the current spatial closed surface relative to the initial spatial closed surface is calculated. The formula for calculating the deformation rate is as follows: ,in For the first i The surface deformation rate of the sealed interface at a target temperature point, dimensionless, expressed as a percentage. The absolute difference in surface area between the current closed surface and the initial closed surface in space, expressed in square meters; the value of the first surface area calculated using the formula... i Surface deformation rate at a target temperature point It is directly used as the geometric fidelity coefficient of the sealing interface at the target temperature point, and is uniformly denoted as... ,Right now The geometric fidelity coefficient is associated with and stored in relation to the corresponding target temperature point number and the sealing area to which it belongs. Following the above process, the surface deformation rate calculation and geometric fidelity coefficient assignment are completed sequentially for all target temperature points in the temperature control sequence, resulting in the geometric fidelity coefficient corresponding to each target temperature point. This forms a set of geometric fidelity coefficients for the sealing interface of the characteristic spatial marker area at each temperature. This set, together with the temperature control sequence and the basic leakage rate data, forms multi-dimensional correlation data, providing accurate correction factors for leakage rate data correction.

[0092] It should be noted that all operations in step 3 are based on the temperature control sequence and the thermal equilibrium state at the target temperature point in step 2. This involves synchronous monitoring of the geometric morphology of the sealing interface at the same target temperature point. i The serial number of the target temperature point needs to be consistent with that in step 2 to achieve a precise correlation between the temperature point, the basic leakage rate, and the geometric fidelity coefficient, providing a matching correction factor for leakage rate data correction; two locations i The value range and numbering rules are completely unified, and all are based on the target temperature point of the temperature control sequence. There are no other numbering dimensions, so there is no confusion or ambiguity.

[0093] In a preferred embodiment of the present invention, step 4 above may include:

[0094] Step 4.1: Obtain the geometrical fidelity coefficient of the sealing interface at each target temperature point. For each target temperature point, after performing a positive pressure internal leak test at that temperature point and reaching thermal equilibrium, initiate the helium mass spectrometry leak detection process. Specifically, this includes: first, retrieving the geometrical fidelity coefficient of the sealing interface corresponding to each target temperature point within the temperature control sequence obtained in Step 3.4; then, according to the numbering order of the target temperature points, matching and binding each geometrical fidelity coefficient with the corresponding target temperature point number, target temperature value, and information about the area to which the sealing interface belongs, item by item, forming a complete temperature-coefficient correspondence with the target temperature point number as the unique index, the temperature value as the associated field, and the geometrical fidelity coefficient as the core field. This correspondence allows direct querying of the corresponding temperature value and geometrical fidelity coefficient using the temperature point number. The geometric fidelity coefficient can also be used to reverse locate the corresponding number and geometric fidelity coefficient through temperature values, ensuring that subsequent leak detection data and deformation coefficients can be accurately matched. For each target temperature point in the temperature control sequence, after completing gradient temperature control, thermal balance judgment, positive pressure internal leakage test, and three-dimensional coordinate acquisition and surface fitting of the sealing interface at that temperature point, the pressure of the test gas inside the valve is kept at a stable rated working pressure, and the ambient temperature of the valve is kept at the thermal balance state at the target temperature point. Without changing the overall working condition of the valve and the test environment, the preparatory and formal testing process of helium mass spectrometry leak detection is started simultaneously, so that helium mass spectrometry leak detection and previous tests are completed under the same temperature, pressure, and thermal balance conditions, ensuring that the test data have a unified working condition benchmark and comparable conditions.

[0095] Step 4.2: Move along the preset scanning path on the outer surface of the valve to continuously scan the outer surface of the valve in order to capture the concentration signal of tracer gas molecules escaping from the leak point in real time. Specifically, the preset scanning path is a standardized detection path pre-planned according to the structural characteristics and sealing leakage risk distribution of the valve under test. The path is based on the principles of full coverage, no omissions, and no repetition. It can sequentially traverse all key areas of the valve that are prone to leakage, ensuring that each potential leak point can be effectively detected. The direction, point distribution, and movement sequence of the scanning path correspond one-to-one with the outer dimensions and sealing structure of the valve, and have uniqueness and stability.

[0096] The helium mass spectrometry leak detection device is a high-precision detection equipment used to detect minute leaks. It mainly consists of an induction probe, a signal acquisition module, a signal processing module, and a tracer gas identification module. The induction probe is responsible for collecting gas signals at close range and converting gas concentration information into electrical signals. The signal acquisition module receives and transmits the electrical signals output by the induction probe in real time, ensuring that the signal is attenuated and has no delay. The tracer gas identification module performs helium feature matching and identification on the incoming signal to eliminate interference from other gases. The signal processing module amplifies, filters, and normalizes the identified valid signals to output a stable and usable concentration signal. The four modules work together in sequence to complete the acquisition, identification, and signal output of the tracer gas. The tracer gas molecules are helium molecules used in this test. Helium has the characteristics of small molecular diameter, stable chemical properties, non-corrosiveness, extremely low content in air, and easy accurate identification. In the positive pressure internal leak test of valves, helium molecules are filled into the valve. Once there is a defect or gap in the valve sealing interface, helium molecules will escape from the inside through the leak point, becoming a marker gas characterizing the leak state.

[0097] Following the preset scanning path, a full-coverage scan is sequentially completed along the outer surface of the valve at a constant and stable moving speed. The scanning path passes through all critical areas where gas leaks may occur, including the outer area of ​​the valve seat sealing surface, the circumferential area at the junction of the valve stem and stuffing box, the valve body cavity mating surface, and the flange surface connecting the valve body and the pipeline. During the scanning process, the distance between the leak detection probe and the outer surface of the valve is kept constant and within the optimal detection distance range to avoid distortion of the tracer gas signal acquisition caused by probe shaking, sudden distance changes, or uneven speed. During the continuous moving scan, the inductive probe of the helium mass spectrometer leak detection device captures tracer gas molecules escaping from the inside of the valve through the leak point in real time. After being processed by the various modules inside the device, the concentration signal of the tracer gas molecules, which changes synchronously with the scanning position, is output in real time to ensure that the concentration signal corresponding to each leak location can be recorded completely, continuously, and stably.

[0098] Step 4.3 converts the captured tracer gas molecule concentration signal into a leak rate value to obtain the raw leak rate detection data at the current temperature. Specifically, this includes: transmitting the simulated tracer gas molecule concentration signal, acquired and output in real-time by the helium mass spectrometer during continuous scanning, to the data processing terminal. Upon receiving the signal, the data processing terminal performs hardware-level and software-level filtering, amplification, and noise reduction on the concentration signal, effectively filtering out background gas interference, electromagnetic interference, invalid signals and abnormal abrupt changes caused by brief probe shaking or scanning speed fluctuations, thus maintaining a smooth signal. Continuous and reliable; after completing signal preprocessing, the data processing terminal calls the calibration curve and concentration-leakage correspondence obtained by the helium mass spectrometer leak detection device through step-by-step calibration with standard leak holes before leaving the factory. The calibration curve and correspondence are obtained by step-by-step calibration using standard leak holes with known leakage rates under standard conditions. By inputting helium tracer gas of different concentrations and recording the electrical signals output by the device, a stable one-to-one mapping relationship between helium concentration values ​​and leakage rate values ​​is established. This correspondence is stored in the device in the form of a curve, which can ensure the accuracy and consistency of the conversion of concentration signals to leakage rate values.

[0099] The data processing terminal uses the effective concentration signal at each sampling moment during the scanning process as input, reads the coordinate point corresponding to the concentration signal on the calibration curve, and performs numerical conversion point by point and moment by moment through coordinate positioning and interpolation calculation according to the linear or quasi-linear change law of the curve. It converts the discretely distributed concentration values ​​into uniquely corresponding leakage rate values ​​one by one, ensuring that each concentration signal can accurately and unambiguously match the corresponding leakage rate value, and that the entire conversion process does not produce numerical distortion or deviation. After completing the signal conversion of all points, the data processing terminal centrally integrates and sorts all leakage rate values ​​obtained at the current target temperature point and under the same thermal equilibrium state according to the sampling time sequence, and then makes a reasonable judgment on the leakage rate values, further eliminating extreme outliers that deviate significantly from the overall data distribution range, and retaining effective data that can truly reflect the leakage state of the valve under the operating condition. Finally, it forms complete, continuous, reliable, and original leakage rate detection data that can truly reflect the overall leakage level of the valve at the temperature point.

[0100] Step 4.4: Associate and store the raw leak rate detection data at the current temperature point with the geometric fidelity coefficient at this temperature point to form a correspondence between each target temperature point and the raw leak rate detection data. Specifically, this includes: binding the raw leak rate detection data obtained through signal processing and numerical conversion at the current target temperature point one-to-one with the geometric fidelity coefficient of the sealing interface calculated at the same target temperature point in Step 3.4. The binding process uses the target temperature point number as the unique index key, and also associates the specific temperature value, thermal balance state identifier, and sealing interface area information of the target temperature point. The data is classified and stored in ascending order of the target temperature point number to ensure that each set of raw leak rate detection data can only be matched with the corresponding geometric fidelity coefficient at the same temperature point and under the same operating condition, and there will be no data confusion across temperature points or regions.

[0101] A one-to-one correspondence is formed among the three, with the target temperature point sequence number as the core index. Each valid data record contains four associated fields: target temperature point sequence number, target temperature value, original leak rate detection data at that temperature point, and geometric fidelity coefficient of the sealing interface at that temperature point. By using any one of these fields, the other three fields in the same group can be retrieved in reverse, achieving bidirectional and accurate positioning between temperature point, temperature value, original leak rate detection data, and geometric fidelity coefficient. Following the above binding and storage method, the data association, verification, and archiving of all target temperature points in the temperature control sequence are completed sequentially, ultimately forming a three-dimensional correspondence that covers the entire temperature range, is structurally complete, logically clear, traceable, and queryable. This correspondence provides a unified and reliable data foundation for subsequent geometric fidelity correction of the original leak rate data and analysis of temperature, leak rate, and deformation characteristics.

[0102] In a preferred embodiment of the present invention, step 5 above may include:

[0103] Step 5.1: Obtain the correspondence between each target temperature point and the original leak rate detection data, and simultaneously obtain the initial dynamic sealing performance curve. Specifically, this includes: retrieving the established complete correspondence containing target temperature point numbers, target temperature values, original leak rate detection data, and geometrical fidelity coefficients; performing dual verification of completeness and consistency on all retrieved data; checking each temperature point number for completeness and missing entries; verifying the temperature values ​​and corresponding data for matching and consistency; filtering out invalid null values ​​and abnormal entries; and confirming that each target temperature point has complete and qualified associated data. Simultaneously, [the text abruptly ends here, likely due to an incomplete translation or missing information]. In step 2.4, based on the pressure decay test data and the initial dynamic sealing performance curve generated by fitting using the least squares method, the temperature coordinate range, temperature point numbering and sorting rules, and temperature scale values ​​used in the curve are checked item by item to confirm that the curve parameters are completely consistent with the test conditions. The verified data correspondence and the verified initial dynamic sealing performance curve are classified into the same temperature control sequence system, and the temperature coordinate range, temperature point numbering order, data accuracy, storage format, and test sampling conditions are unified to eliminate benchmark differences and format conflicts. This establishes a stable, unified, and comparable data benchmark for data compensation correction and curve fusion reconstruction.

[0104] Step 5.2: For each target temperature point, extract the original leak rate detection data and the corresponding geometric fidelity coefficient at that temperature point. Using the geometric fidelity coefficient as a correction factor, compensate and correct the original leak rate detection data according to the compensation correction function that is positively correlated with the geometric fidelity coefficient to obtain the corrected leak rate detection result at the temperature point. Specifically, for each target temperature point in the temperature control sequence, according to the pre-set temperature point numbering order, accurately extract the original leak rate detection data after preprocessing and outlier removal at the current temperature point from the one-to-one correspondence relationship between the target temperature point, the original leak rate detection data, and the geometric fidelity coefficient established in Step 4.4. At the same time, extract the geometric fidelity coefficient of the sealing interface, which is completely bound to the temperature point number and temperature value and calculated by Step 3.4. The geometric fidelity coefficient can objectively and quantitatively characterize the magnitude of the surface deformation of the sealing interface caused by thermal expansion and contraction under the current target temperature and the degree of deviation of the sealing fit state. It can directly reflect the actual influence of geometric deformation on the tracer gas leakage diffusion process and the leak rate detection result.

[0105] Among them, the correction factor specifically used to eliminate temperature deformation interference is the aforementioned geometric fidelity coefficient. This correction factor is directly converted from the deformation rate of the sealing interface at the corresponding temperature. It can quantitatively reflect the degree of interference of temperature-induced geometric deformation such as expansion, contraction, warping or misalignment of the sealing interface on the leakage detection results. Its value is positively correlated with the degree of deformation interference. That is, the larger the value of the geometric fidelity coefficient, the greater the correction range of the original leakage rate detection data. It can accurately remove the non-real leakage component caused by deformation. This correction factor does not change the basic trend of leakage detection, but is only used to remove the non-real leakage component caused by thermal deformation. It is a key parameter for achieving accurate correction of leakage rate data.

[0106] Using the geometric fidelity coefficient as a correction factor specifically designed to eliminate temperature deformation interference, and assuming the valve's current temperature field is completely stable, in thermal equilibrium, and the internal test pressure remains constant, a complete compensation correction is performed based on the original leak rate detection data and using the geometric fidelity coefficient as the correction criterion. The original leak rate detection data is then adjusted point-by-point, time-by-time, and scan-by-scan position according to a compensation correction function positively correlated with the geometric fidelity coefficient. As an example, the preset compensation correction function can be adjusted using the following linear compensation correction formula: ;in, The results are the corrected leak rate detection results. This is the raw leak rate detection data. This is the geometric fidelity coefficient (area deformation rate) at the current temperature point. This formula achieves the effect that the larger the value of the geometric fidelity coefficient, the larger the correction range, thereby eliminating the non-real leakage component introduced by the thermal deformation of the sealing interface. It is understandable that other forms of compensation correction functions can also be used in practical applications, as long as they can correct the original leakage rate data based on the geometric fidelity coefficient in a positive correlation with the degree of deformation.

[0107] The portion of the leakage rate that is artificially high due to excessive deformation of the sealing interface and gap expansion is reasonably deducted, while the portion of the leakage rate that is artificially low due to insufficient deformation of the sealing interface and excessive tightness is reasonably supplemented. By precisely matching the degree of deformation, the non-real leakage component introduced by temperature thermal deformation in the original leakage rate detection data is gradually corrected, and the systematic detection deviation caused by the geometric deformation of the sealing interface is completely eliminated. This ensures that the corrected leakage rate value can truly restore the actual leakage level of the valve under ideal sealing interface conditions without additional thermal deformation. Finally, the corrected leakage rate detection result is obtained point by point at the target temperature point, which is real, accurate, reliable and fully compensated.

[0108] Step 5.3: The corrected leakage rate detection results at each target temperature point are fused with the initial dynamic sealing performance curve under the same temperature coordinate. That is, the corrected leakage rate detection results are used as the true leakage rate at that temperature point, replacing the original basic leakage rate value of the corresponding temperature point in the initial dynamic sealing performance curve. Smooth interpolation is performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve. Specifically, this includes: first, summarizing the leakage rate detection results corresponding to all target temperature points in the temperature control sequence after complete compensation and correction; extracting the initial dynamic sealing performance curve data generated in step 2.4; preprocessing the two sets of data; unifying the temperature range, numerical accuracy, measurement unit and data layout format; eliminating data conflicts caused by format differences and benchmark deviations; and ensuring that the parameters of the two sets of data are consistent. A two-dimensional coordinate reference system is then established based on temperature. All temperature ranges involved in the test are evenly distributed as the horizontal axis scale, and the leakage rate value is set as the vertical axis scale. The vertical axis scale unit and division value are completely consistent with the initial dynamic sealing performance curve, so that the two sets of data can be processed based on the same coordinate reference, and a unified reference standard is built for data matching and curve fusion.

[0109] Under a unified temperature benchmark, time-series and numerical matching of the two sets of data were performed. Using the target temperature point number and corresponding temperature value as the sole matching basis, the corrected leakage rate detection result at each target temperature point was matched one-to-one with the leakage rate value corresponding to the same temperature point on the initial dynamic sealing performance curve. The numerical correlation and trend consistency of the two sets of data at the same temperature point were verified to complete the precise pairing of data points. Then, the connection and reconstruction of the two sets of data were carried out. First, the initial dynamic sealing performance curve was used as the basic reference curve, retaining its overall trend and core data characteristics. Then, the corrected leakage rate values ​​of each temperature point were precisely embedded into the corresponding temperature coordinate points to correct the numerical deviations in the initial curve caused by not considering the deformation of the sealing interface. The data of adjacent temperature points were transitioned to ensure that the corrected leakage rate values ​​and the initial curve data fit seamlessly without any discontinuities or misalignments. The reconstructed curve not only retains the original regularity of the initial sealing performance curve but also incorporates the real leakage rate data after deformation correction, achieving deep integration of the two sets of data.

[0110] After data connection and reconstruction, smoothing interpolation is performed on the curve to fill in the missing data between test temperature points. The interpolation is based on the reconstructed discrete data points, and a piecewise linear smoothing interpolation algorithm is selected. It follows the original trend of the curve and does not change the true value of the original test point. Interpolation calculations are performed sequentially on the blank temperature intervals between two adjacent target temperature points to generate the leakage rate estimate value corresponding to the intermediate temperature point. During the interpolation process, the magnitude of numerical change is strictly controlled to avoid abrupt changes in values ​​or steep rises and falls in the curve. At the same time, the curve is smoothed as a whole, eliminating local abnormal fluctuations and small jumps, and smoothing the edges at the curve junctions to make the overall curve trend smooth and continuous, ensuring that the curve is continuous and uninterrupted throughout the entire temperature range, which conforms to the actual change law of valve sealing leakage performance.

[0111] The final temperature-corrected leakage rate correlation curve is a continuous two-dimensional curve with temperature as the independent variable and the corrected leakage rate as the dependent variable. The horizontal axis covers the entire temperature gradient range of this test, and the vertical axis reflects the actual leakage rate of the valve after deformation correction. The curve completely retains the measured correction data and interpolation fitting data at each temperature point, and can intuitively and accurately reflect the actual sealing and leakage characteristics of the valve sealing interface after eliminating thermal deformation interference under different temperature conditions. It clearly shows the overall trend, abrupt change nodes and stable range of leakage rate with temperature change. It not only eliminates the detection error caused by deformation, but also restores the true performance of valve sealing. It can be directly used for valve sealing performance evaluation, temperature sensitivity analysis and structural optimization reference, and is the core result curve of this test.

[0112] Step 5.4: Output the temperature-corrected leak rate correlation curve as the test result. Specifically, this includes: defining the temperature-corrected leak rate correlation curve after data correction, curve fusion, and smoothing as the final test result of this positive pressure internal leakage test under the valve gradient temperature condition, and determining this curve as the core evaluation basis. Simultaneously, organize the complete set of correlation data corresponding to the curve, and collect the corrected leak rate value, matching geometric fidelity coefficient, original leak rate detection data, and basic parameters such as temperature control sequence parameters, thermal balance judgment criteria, and test pressure conditions for each temperature point in the order of target temperature point numbering. All the organized data are checked step by step to check for omissions and mismatches, confirming that each piece of data is true and valid and the correspondence is accurate. Then, the temperature-corrected leak rate correlation curve is integrated with the checked complete set of data to form a complete test result data package.

[0113] In accordance with standardized archiving rules, test result data packages are classified, stored, and marked for record-keeping, preserving complete data traceability paths and processing records to ensure that all test data is searchable, verifiable, and traceable. The integrated test results can provide effective, authentic, and reliable data support for valve sealing performance level evaluation, sealing structure optimization design, in-depth analysis of leakage mechanisms, product factory quality verification, and subsequent operating condition adaptation improvements, providing detailed test basis for improving valve sealing reliability.

[0114] like Figure 2 As shown, embodiments of the present invention also provide a detection system for internal leakage of a positive pressure helium detection valve, comprising:

[0115] The positive pressure internal leakage pre-inspection module is used to apply test gas at the rated working pressure to the valve under test. It monitors the pressure change inside the valve in real time under the rated working pressure and performs positive pressure internal leakage pre-inspection. If the pressure remains stable, the result of passing the pre-inspection is obtained. If the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued.

[0116] The dynamic operating condition simulation module is used to control the temperature conditions of the valve under test during the continuous application of test gas based on the judgment results of passing the pre-inspection. It repeatedly performs positive pressure internal leakage test at different temperatures, records the basic leakage rate at each temperature point, and obtains the initial dynamic sealing performance curve of leakage rate as a function of temperature.

[0117] The sealing interface deformation detection module is used to simultaneously deploy multiple characteristic spatial markers at the sealing interface on the outer surface of the valve, collect the three-dimensional spatial coordinates of each characteristic spatial marker in real time, fit them into a spatial closed surface, calculate the surface deformation rate of the spatial closed surface relative to the initial state, and obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

[0118] The helium mass spectrometry leak detection module is used to perform helium mass spectrometry leak detection at various temperature points, scan the outer surface of the valve, capture the tracer gas molecules that escape from the leak, and obtain the raw leak rate detection data at the corresponding temperature point.

[0119] The data processing and fusion module is used to compensate and correct the original leakage rate detection data at the corresponding temperature point using the geometric fidelity coefficient at the same temperature point as a correction factor, to obtain the corrected leakage rate detection result. The corrected leakage rate detection result at each temperature point is then fused with the initial dynamic sealing performance curve. That is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original basic leakage rate value at the corresponding temperature point in the initial dynamic sealing performance curve. Smoothing interpolation is then performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, thus completing the output of the test results.

[0120] 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.

[0121] 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.

[0122] 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.

[0123] 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 detecting internal leakage in a positive pressure helium detection valve, characterized in that, The method includes: Step 1: Apply test gas at the rated working pressure to the valve under test, and monitor the pressure change inside the valve in real time under the rated working pressure to perform positive pressure internal leakage pre-inspection; if the pressure remains stable, the result of passing the pre-inspection is obtained; if the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued. Step 2: Based on the judgment result of passing the pre-inspection, during the continuous application of test gas, control the temperature conditions of the valve under test, repeat the positive pressure internal leakage test at different temperatures, record the basic leakage rate at each temperature point, and obtain the initial dynamic sealing performance curve. Step 3: Simultaneously deploy multiple characteristic spatial markers at the sealing interface on the outer surface of the valve, collect the three-dimensional spatial coordinates of each characteristic spatial marker in real time, use them to fit a spatial closed surface, calculate the surface deformation rate of the spatial closed surface relative to the initial state, and obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature. Step 4: At each temperature point, perform helium mass spectrometry leak detection, scan the outer surface of the valve, capture the tracer gas molecules that escape from the leak, and obtain the raw leak rate detection data at the corresponding temperature point. Step 5: Using the geometric fidelity coefficient at the same temperature point as a correction factor, the original leakage rate detection data at the corresponding temperature point is compensated and corrected to obtain the corrected leakage rate detection result. The corrected leakage rate detection result at each temperature point is then fused with the initial dynamic sealing performance curve to obtain the temperature-corrected leakage rate correlation curve.

2. The method for detecting internal leakage in a positive pressure helium detection valve according to claim 1, characterized in that, Test gas at the rated working pressure is applied to the valve under test, and after the pressure stabilizes, the internal pressure change of the valve is monitored in real time at the rated working pressure to perform positive pressure internal leakage pre-inspection. If the pressure remains stable, the test is deemed successful. If the pressure fluctuation exceeds a set threshold, the test is terminated and an alarm signal is issued, including: Test gas is introduced into the valve under test until the internal pressure of the valve reaches the rated working pressure. After the rated working pressure is reached, the gas introduction is stopped to obtain the initial stable pressure value. Based on the initial stable pressure value, the internal pressure data of the valve is continuously collected, and the pressure fluctuation amplitude between the current pressure value and the initial stable pressure value is calculated in real time with a preset sampling period. The pressure fluctuation amplitude is compared with a set threshold. If the pressure fluctuation amplitude is always lower than the set threshold during the preset monitoring period, the pressure is determined to be stable, and the result of passing the pre-inspection is obtained. If the pressure fluctuation exceeds the set threshold within the preset monitoring period, it is determined that the pressure fluctuation exceeds the allowable range, the test is immediately terminated, and an alarm signal is output.

3. The method for detecting internal leakage in a positive pressure helium detection valve according to claim 2, characterized in that, Based on the pre-inspection results, during the continuous application of test gas, the temperature conditions of the valve under test are controlled, and the positive pressure internal leakage test is repeatedly performed at different temperatures. The baseline leakage rate at each temperature point is recorded, and the initial dynamic sealing performance curve of leakage rate versus temperature is obtained, including: After obtaining the result of passing the pre-inspection, maintain the internal test gas pressure of the valve at the rated working pressure and set the temperature control sequence; wherein, the temperature control sequence includes multiple target temperature points that increase or decrease according to preset step size; The ambient temperature of the valve is adjusted to each target temperature point in turn. After thermal equilibrium is reached at each target temperature point, the pressure decay data of the valve's internal pressure over time is continuously collected. Based on the pressure decay data collected at each target temperature point, the basic leakage rate corresponding to this temperature point is calculated, and the correspondence between each target temperature point and the basic leakage rate is obtained. Using the target temperature point as the x-axis and the basic leakage rate as the y-axis, the basic leakage rate at each target temperature point is curve-fitted to form the initial dynamic sealing performance curve of leakage rate as a function of temperature.

4. The method for detecting internal leakage in a positive pressure helium detection valve according to claim 3, characterized in that, Multiple characteristic spatial markers are simultaneously deployed at the sealing interface on the outer surface of the valve. The three-dimensional spatial coordinates of each characteristic spatial marker are collected in real time and used to fit a spatial closed surface. The surface deformation rate of the spatial closed surface relative to the initial state is calculated to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature, including: The temperature control sequence that has been set for the valve under test is retrieved from the control terminal. Before performing the positive pressure internal leakage test at each target temperature point, the initial three-dimensional spatial coordinates of multiple characteristic spatial markers at the sealing interface on the outer surface of the valve are collected. The characteristic spatial markers are located in the contact ring area between the valve seat sealing surface and the valve disc, as well as the circumferential area at the junction of the valve stem and the stuffing box. During the positive pressure internal leakage test at each target temperature point, once the target temperature point reaches thermal equilibrium, the real-time three-dimensional spatial coordinates of the same set of characteristic spatial markers at the current temperature are simultaneously collected. The real-time three-dimensional spatial coordinates collected at the current temperature are spatially matched with the initial three-dimensional spatial coordinates to fit the initial spatial closed surface and the current spatial closed surface respectively. Calculate the surface deformation rate of the current spatial closed surface relative to the initial spatial closed surface, and use the surface deformation rate as the geometric fidelity coefficient of the sealing interface at the current target temperature point to obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature.

5. The method for detecting internal leakage in a positive pressure helium detection valve according to claim 4, characterized in that, At each temperature point, helium mass spectrometry was used to scan the outer surface of the valve to capture tracer gas molecules escaping from the leak, obtaining the raw leak rate detection data for the corresponding temperature point, including: Obtain the geometric fidelity coefficient of the sealing interface at each target temperature. For each target temperature, after performing a positive pressure internal leak test at this temperature and reaching thermal equilibrium, start the helium mass spectrometry leak detection process. The device moves along a preset scanning path on the outer surface of the valve to continuously scan the outer surface of the valve in order to capture the concentration signal of tracer gas molecules escaping from the leak point in real time. The captured tracer gas molecule concentration signal is converted into a leak rate value to obtain the raw leak rate detection data at the current temperature point; The original leak rate detection data at the current temperature point is associated with the geometric fidelity coefficient at this temperature point and stored to form a correspondence between each target temperature point and the original leak rate detection data.

6. The method for detecting internal leakage in a positive pressure helium detection valve according to claim 5, characterized in that, Using the geometric fidelity coefficient at the same temperature point as a correction factor, the original leakage rate detection data at the corresponding temperature point are compensated and corrected to obtain the corrected leakage rate detection result. The corrected leakage rate detection results at each temperature point are then fused with the initial dynamic sealing performance curve to obtain the temperature-corrected leakage rate correlation curve, thus completing the output of the test results, including: The correspondence between each target temperature point and the original leak rate detection data is obtained, and the initial dynamic sealing performance curve is obtained at the same time. For each target temperature point, the original leak rate detection data and the corresponding geometric fidelity coefficient at this temperature point are extracted. The geometric fidelity coefficient is used as a correction factor, and the original leak rate detection data is compensated and corrected according to the compensation correction function that is positively correlated with the geometric fidelity coefficient to obtain the corrected leak rate detection result at the temperature point. The corrected leakage rate detection results at each target temperature point are fused with the initial dynamic sealing performance curve under the same temperature coordinate. That is, the corrected leakage rate detection results are used as the true leakage rate at this temperature point, replacing the original basic leakage rate value of the corresponding temperature point in the initial dynamic sealing performance curve. Smooth interpolation is performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve. The temperature-corrected leak rate correlation curve is output as the test result.

7. A detection system for internal leakage of a positive pressure helium detection valve, the system implementing the method as described in any one of claims 1 to 6, characterized in that, include: The positive pressure internal leakage pre-inspection module is used to apply test gas at the rated working pressure to the valve under test. It monitors the pressure change inside the valve in real time under the rated working pressure and performs positive pressure internal leakage pre-inspection. If the pressure remains stable, the result of passing the pre-inspection is obtained. If the pressure fluctuation exceeds the set threshold, the test is terminated and an alarm signal is issued. The dynamic operating condition simulation module is used to control the temperature conditions of the valve under test during the continuous application of test gas based on the judgment results of passing the pre-inspection. It repeatedly performs positive pressure internal leakage test at different temperatures, records the basic leakage rate at each temperature point, and obtains the initial dynamic sealing performance curve of leakage rate as a function of temperature. The sealing interface deformation detection module is used to simultaneously deploy multiple characteristic spatial markers at the sealing interface on the outer surface of the valve, collect the three-dimensional spatial coordinates of each characteristic spatial marker in real time, fit them into a spatial closed surface, calculate the surface deformation rate of the spatial closed surface relative to the initial state, and obtain the geometric fidelity coefficient of the sealing interface at the corresponding temperature. The helium mass spectrometry leak detection module is used to perform helium mass spectrometry leak detection at various temperature points, scan the outer surface of the valve, capture the tracer gas molecules that escape from the leak, and obtain the raw leak rate detection data at the corresponding temperature point. The data processing and fusion module is used to compensate and correct the original leakage rate detection data at the corresponding temperature point using the geometric fidelity coefficient at the same temperature point as a correction factor, to obtain the corrected leakage rate detection result. The corrected leakage rate detection result at each temperature point is then fused with the initial dynamic sealing performance curve. That is, the corrected leakage rate detection result is used as the true leakage rate at that temperature point, replacing the original basic leakage rate value at the corresponding temperature point in the initial dynamic sealing performance curve. Smoothing interpolation is then performed between adjacent temperature points to reconstruct a new temperature-corrected leakage rate correlation curve, thus completing the output of the test results.

8. A computing device, characterized in that, include: 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 as described in any one of claims 1 to 6.

9. 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 6.

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