OCV valve test stand gas measurement system and method

Abstract

The application discloses an OCV valve test bench gas detection system and a gas detection method, and relates to the field of air tightness detection.The gas detection system comprises two clamping positioning modules symmetrically arranged inside a test bench main body, a detection unit arranged at the bottom end of the clamping positioning module, the detection unit being arranged inside the test bench main body, an analysis unit arranged at the right end of the test bench main body, and a leakage capturing module arranged at the bottom end of the side of the clamping positioning module, wherein the test bench main body serves as a mounting end of various functional components and functional modules, and provides power, a gas source and communication connection; the clamping positioning module is used for driving the action of a clamp through a gas cylinder, and is used for automatically positioning and clamping the electromagnetic valve to be detected; the three-dimensional coordinates of a leakage source are accurately calculated, and the three-dimensional coordinates are mapped to the surface of the electromagnetic valve to be detected, the leakage area is quickly positioned, the frequency of occurrence of the abnormal area and the change trend of the abnormal area with time are identified, and potential defects in the production process are quickly positioned.

Description

Technical Field

[0001] This invention relates to the field of airtightness testing technology, specifically to an OCV valve test bench air testing system and air testing method. Background Technology

[0002] With the rapid development of automotive technology, the performance requirements of its core component - the solenoid valve - have also increased. This is because the solenoid valve plays an important role in the liquid cooling system, braking system and air management system of automobiles. In order to ensure the safety, reliability and energy efficiency of automobiles, the solenoid valve must be subjected to comprehensive performance testing and quality evaluation.

[0003] Traditional methods rely on manual identification of solenoid valve models and geometric features, which is inefficient, prone to misidentification, and cannot be automatically correlated with test data. Conventional gas detection can only determine the presence of leaks, lacking three-dimensional coordinate modeling and gradient correlation rules based on the spatial distribution of multiple sensors, resulting in insufficient accuracy in locating leak areas. Existing testing equipment mostly uses fixed pressure values ​​for testing, which cannot simulate multi-pressure step conditions, and the dynamic response of pressure regulation is poor, affecting the authenticity of the leak flow curve. Historical data is not deeply correlated with production batch and process information, making it difficult to trace the root cause of production defects through the distribution of leak areas, resulting in delayed fault attribution. Summary of the Invention

[0004] (a) Technical problems to be solved

[0005] In view of the above-mentioned shortcomings of the prior art, the present invention provides an OCV valve test bench gas measurement system and gas measurement method, which can effectively solve the problems of the prior art.

[0006] (II) Technical Solution

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] In a first aspect, the present invention discloses an OCV valve test bench gas measurement system, comprising two clamping and positioning modules symmetrically installed inside the test bench body. A detection unit is provided at the bottom end of each clamping and positioning module, and the detection unit is installed inside the test bench body. An analysis unit is installed at the right end of the test bench body. A leakage detection module is installed at the bottom end of the side of each clamping and positioning module. Wherein:

[0009] The main body of the test bench serves as the mounting point for various functional components and modules, providing power, air supply, and communication connections.

[0010] The clamping and positioning module is used to drive the clamping action through a cylinder to complete the automatic alignment and clamping of the solenoid valve under test.

[0011] The detection unit is used to electrically identify the model, serial number and geometric features of the solenoid valve under test, provide the solenoid valve under test with a preset air source pressure, and perform a sealing test on the solenoid valve under test under the action of several air pressure intensities, and output the air tightness data of the original air pressure flow curve.

[0012] The leak detection module is used to deploy gas sensors to monitor the concentration of tracer gases in the air in real time. When the reading of any sensor exceeds the set threshold, the geometric position of the corresponding sensor and valve body is obtained. The leak area is located by combining the data from several gas sensors, and the three-dimensional coordinates are output.

[0013] The analysis unit is used to collect and store air pressure, flow rate, leakage location and timestamp data in real time at each test stage, compare the air tightness data with preset thresholds, determine the qualified status of the solenoid valve under test, and statistically analyze the distribution and trend of abnormal areas based on the leakage area data of several solenoid valves under test in the same production batch. Combined with the trend of abnormal areas, the production process problem coefficient that caused the failure is calculated.

[0014] Furthermore, the detection unit is equipped with sub-modules, including a component identification module, a pressure control module, and an airtightness measurement module. The pressure control module is interconnected with the component identification module and the airtightness measurement module via a wireless network.

[0015] The component identification module is used to identify the QR code and shape features on the end face of the solenoid valve, obtain the model and serial number through the image matching algorithm, and record them in the system database. If the identification fails, it will trigger voice or interface prompts and wait for manual intervention.

[0016] The pressure control module is used to distribute the central air source provided by the main body of the test bench to each test channel and issue the target pressure value, and maintain stable pressure through real-time PID adjustment;

[0017] The airtightness measurement module is used to apply N pressure steps sequentially according to a preset test program. At each pressure step, it measures the leakage flow rate output by the flow meter and transmits the leakage flow rate data to the analysis unit.

[0018] Furthermore, the process of locating the leakage area in the leakage detection module is as follows:

[0019] Based on the preset three-dimensional coordinate positions of each gas sensor, a sensor distribution space model consisting of solid models of several solenoid valves is constructed.

[0020] Establish a correlation rule between the location of the leak source and the gas concentration detected by each sensor, wherein the correlation rule reflects the gradient distribution characteristics of the leak gas concentration as a function of distance;

[0021] The three-dimensional coordinates of the leakage source are used as the dependent variable, and the concentration weighting coefficients and corresponding spatial coordinates of each sensor are used as independent variables. A multivariate linear relationship equation is established, and the equation parameters are determined by fitting using the least squares method. The initial solution of the leakage source coordinates is then output.

[0022] Based on the initially solved coordinates of the leak source, the theoretical gas concentration distribution is simulated. The residuals of the actual sensor detection values ​​and the theoretical values ​​are compared. The coordinate parameters are adjusted through multiple iterations to minimize the residuals, and the optimized three-dimensional coordinate data is output.

[0023] The optimized 3D coordinate data is mapped onto the surface of the solid model of the solenoid valve under test, marking the spatial location of the leakage area and associating it with the production batch and process information of the solenoid valve.

[0024] Furthermore, when a leak occurs, the leak detection module simultaneously acquires real-time concentration values ​​from multiple sensors, eliminates outlier noise data caused by environmental interference, and retains the effective concentration detection signal.

[0025] Furthermore, the analysis unit is further equipped with sub-modules, including a data acquisition and storage module, a qualification analysis module, a trend analysis module, and a fault analysis module, wherein:

[0026] The data acquisition and storage module is used to acquire the sensor data, voltage regulation data and component identification data provided by the detection unit, write them to the local database in real time, and generate CSV / JSON log files in batches. After the test is completed, the data is periodically or as needed uploaded to the cloud database for backup.

[0027] The qualification analysis module is used to read the collected pressure-flow curve and compare it with the preset maximum allowable leakage curve. If the leakage value of any pressure point exceeds the standard, it is judged as unqualified, and the corresponding leakage area coordinates are marked and the judgment result is output.

[0028] The trend analysis module is used to call the cloud database interface to extract leakage area data of all test pieces in the same production batch, count the frequency of anomalies in the specified area, and generate data reflecting the distribution of abnormal areas and their changing trends over production time.

[0029] The fault analysis module establishes a process defect mapping model, inputs the change trend data of abnormal areas, calculates the problem factor weights of each process based on the model, and outputs the ranking of the processes that caused the faults and the problem coefficients.

[0030] Furthermore, the specified areas statistically analyzed by the trend analysis module include: valve body interface, threaded connection, sealing ring area and valve body shell.

[0031] Furthermore, the calculation formula for the working logic of the process defect mapping model constructed by the fault analysis module is as follows:

[0032]

[0033] In the formula, K i The problem coefficient represents the i-th process step, m represents the total number of leakage area categories, and a j N represents the weighting factor for the j-th type of leakage region. ij N represents the number of failures in the current batch caused by the i-th process leading to the j-th type of leakage area. j The problem coefficient K represents the total number of failures in the j-th type of leakage area in the current batch. i After sorting in descending order, the corresponding process priority ranking and quantification problem coefficient are output to locate the process that caused the fault.

[0034] Secondly, this invention discloses a gas measurement method for an OCV valve test bench, comprising the following steps:

[0035] Step 1: Set up the test bench and load test resources, and provide the system with power, multiple gas supply sources and communication connections through the mounting terminal;

[0036] Step 2: Drive the cylinder clamp to automatically position and clamp the solenoid valve under test, including using two symmetrically installed cylinders to perform alignment action, and deploying several gas sensors at the bottom side of the clamp to connect to the valve body, with the gas sensors forming an array.

[0037] Step 3: Identify the model and geometric features of the solenoid valve under test, including scanning the end face QR code and the shape image for model matching. If identification fails, manual intervention is triggered. At the same time, based on the central air source, the air is diverted to multiple test channels. After PID regulation and stabilization, N pressure steps are applied according to the preset program. Leakage flow data under each step is collected to generate the original air pressure flow curve.

[0038] Step 4: Monitor and locate the leak area. The gas sensor acquires multi-sensor concentration data in real time. After removing environmental noise, a spatial distribution model is constructed based on the three-dimensional coordinates of the gas sensor. The association rule between the leak source and the concentration gradient is established. The three-dimensional coordinates of the leak source are calculated through multivariate equation fitting and iterative optimization. The coordinates are then mapped to the valve body model and the leak location is marked.

[0039] Step 5: Determine the qualified status of the valve body and analyze production defects. Store test data in real time, compare the leakage flow with the preset threshold to output the judgment result, extract the leakage coordinates of all valve bodies in the same batch at the same time, and count the abnormal frequency of valve body interface, threaded connection, sealing ring and shell to generate spatiotemporal distribution trend.

[0040] Step 6: Establish a process defect mapping model, calculate the problem factor weights of each production process based on the abnormal area trend, output the fault process ranking and problem coefficient, and link it to the cloud database for batch quality traceability.

[0041] Furthermore, in step 2, the gas sensor is a semiconductor or infrared absorption type high-sensitivity sensor with a detection accuracy of not less than ±5ppm, and the detected gas includes helium, nitrogen, or tracer gas in the air medium.

[0042] Furthermore, in step 2, the array of several gas sensors is arranged in a ring around the solenoid valve under test, with the spacing between adjacent sensors being 10-30mm, and the polar coordinate data corresponding to each sensor is pre-written into the system configuration file.

[0043] (III) Beneficial Effects

[0044] Compared with the known prior art, the technical solution provided by this invention has the following beneficial effects:

[0045] 1. By deploying multiple leak detection modules on the side of the clamping and positioning module, a spatial distribution model is constructed based on the three-dimensional coordinates of the leak detection modules. By setting the correlation rules between the location of the leak source and the gas concentration detected by each sensor, the multivariate least squares method is used for parameter fitting and iterative optimization. The three-dimensional coordinates of the leak source are accurately calculated and mapped onto the surface of the solenoid valve under test, which improves the accuracy of leak detection. It can quickly and accurately locate the leak area, providing reliable data support for subsequent maintenance and improvement, and strengthening the airtightness guarantee in automotive applications.

[0046] 2. The automated identification of solenoid valve model, serial number, and geometric features by the detection unit reduces the need for manual intervention, avoids identification errors caused by human factors, and improves overall detection efficiency. Combined with the automatic alignment function of the clamping and positioning module, clamping and airtightness testing are completed in a single operation, greatly shortening the detection cycle. The central air source is used to divert air to multiple test channels, and dynamic pressure stabilization is achieved through PID control algorithm, ensuring test accuracy and consistency under multiple pressure levels, improving the automation level of the production line, and promoting the standardization and efficiency of the detection process.

[0047] 3. By collecting air pressure, flow rate, leak location, and timestamp data in real time at each testing stage through the analysis unit, a complete database system is constructed. This system can deeply correlate test results with production batch information, generate detailed log files after each test, ensure data traceability and integrity, and perform centralized management and analysis in the cloud database. By statistically analyzing the leakage area data of all solenoid valves in the same production batch, the frequency of abnormal areas and their changing trends over time can be identified, allowing for rapid location of potential defects in the production process. This achieves closed-loop feedback in quality control and improves the transparency and manageability of the production process. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0049] Figure 1 This is a schematic diagram of the overall three-dimensional structure of the OCV valve test bench gas measurement system in this invention;

[0050] Figure 2 For the present invention Figure 1 A magnified schematic diagram of the partial structure at point A in the middle;

[0051] Figure 3 This is a schematic diagram of the overall three-dimensional structure of the OCV valve test bench gas measurement system in this invention from another angle;

[0052] Figure 4 This is a schematic diagram of the overall framework of the OCV valve test bench gas measurement system in this invention;

[0053] Figure 5 This is a schematic diagram of the detection unit in this invention;

[0054] Figure 6 This is a schematic diagram of the analysis unit in this invention.

[0055] The labels in the diagram represent: 1. Test bench main body; 2. Clamping and positioning module; 3. Detection unit; 31. Component identification module; 32. Pressure control module; 33. Air tightness measurement module; 4. Leakage detection module; 5. Analysis unit; 51. Data acquisition and storage module; 52. Qualification analysis module; 53. Trend analysis module; 54. Fault analysis module. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0057] The present invention will be further described below with reference to embodiments.

[0058] Example 1

[0059] This embodiment provides an OCV valve test bench gas measurement system, such as... Figure 1 As shown, two clamping and positioning modules 2 are symmetrically installed inside the main body 1 of the test bench. A detection unit 3 is located at the bottom of each clamping and positioning module 2, and the detection unit 3 is installed inside the main body 1 of the test bench. An analysis unit 5 is installed at the right end of the main body 1 of the test bench. A leakage detection module 4 is installed at the bottom of the side of each clamping and positioning module 2. Wherein:

[0060] The main body of the test bench 1 serves as the mounting point for various functional components and modules, providing power, air supply, and communication connections;

[0061] Clamping and positioning module 2 is used to drive the clamping action through a cylinder to complete the automatic alignment and clamping of the solenoid valve under test;

[0062] The detection unit 3 is used to electrically identify the model, serial number and geometric features of the solenoid valve under test, provide the solenoid valve under test with a preset air source pressure, and perform a sealing test on the solenoid valve under test under the action of several air pressure intensities, and output the air tightness data of the original air pressure flow curve.

[0063] The detection unit 3 has sub-modules deployed below it, including a component identification module 31, a pressure control module 32, and an airtightness measurement module 33. The pressure control module 32 interacts with the component identification module 31 and the airtightness measurement module 33 via a wireless network.

[0064] Component identification module 31 is used to identify the QR code and shape features on the end face of the solenoid valve, obtain the model and serial number through image matching algorithm, and record them in the system database. If the identification fails, it triggers voice or interface prompts and waits for manual intervention.

[0065] The pressure control module 32 is used to distribute the central air source provided by the test bench body 1 to each test channel and issue the target pressure value, and maintain stable pressure through real-time PID adjustment;

[0066] The air tightness measurement module 33 is used to apply N pressure steps in sequence according to a preset test program. At each pressure step, it measures the leakage flow rate output by the flow meter and transmits the leakage flow rate data to the analysis unit 5.

[0067] Leak detection module 4 is used to deploy gas sensors to monitor the concentration of tracer gases in the air in real time. When the reading of any sensor exceeds a set threshold, the geometric position of the corresponding sensor and valve body is obtained. By combining the data from several gas sensors, the leak area is located and three-dimensional coordinates are output. The process of locating the leak area is as follows:

[0068] Based on the preset three-dimensional coordinate positions of each gas sensor, a sensor distribution space model consisting of solid models of several solenoid valves is constructed.

[0069] Establish a correlation rule between the location of the leak source and the gas concentration detected by each sensor, where the correlation rule reflects the gradient distribution characteristics of the leak gas concentration as a function of distance;

[0070] The three-dimensional coordinates of the leakage source are used as the dependent variable, and the concentration weighting coefficients and corresponding spatial coordinates of each sensor are used as independent variables. A multivariate linear relationship equation is established, and the equation parameters are determined by fitting using the least squares method. The initial solution of the leakage source coordinates is then output.

[0071] Based on the initially solved coordinates of the leak source, the theoretical gas concentration distribution is simulated. The residuals of the actual sensor detection values ​​and the theoretical values ​​are compared. The coordinate parameters are adjusted through multiple iterations to minimize the residuals, and the optimized three-dimensional coordinate data is output.

[0072] The optimized three-dimensional coordinate data is mapped onto the surface of the solid model of the solenoid valve under test, marking the spatial location of the leakage area and associating it with the production batch and process information of the solenoid valve.

[0073] When a leak occurs, the leak detection module 4 simultaneously acquires the real-time concentration values ​​from multiple sensors, eliminates outlier noise data caused by environmental interference, and retains the effective concentration detection signal.

[0074] Analysis unit 5 is used to collect and store air pressure, flow rate, leakage location and timestamp data in real time at each test stage, compare air tightness data with preset thresholds, determine the qualified status of the solenoid valve under test, and statistically analyze the distribution and trend of abnormal areas based on leakage area data of several solenoid valves under test in the same production batch, and calculate the production process problem coefficient that caused the failure by combining the abnormal area trend.

[0075] Analysis unit 5 has sub-modules deployed below it, including a data acquisition and storage module 51, a qualification analysis module 52, a trend analysis module 53, and a fault analysis module 54, wherein:

[0076] The data acquisition and storage module 51 is used to acquire the sensor data, voltage regulation data and component identification data provided by the detection unit 3, write them to the local database in real time, and generate CSV / JSON log files in batches. After the test is completed, the data is periodically or as needed uploaded to the cloud database for backup.

[0077] The qualification analysis module 52 is used to read the collected pressure-flow curve and compare it with the preset maximum allowable leakage curve. If the leakage value of any pressure point exceeds the standard, it is judged as unqualified, and the corresponding leakage area coordinates are marked and the judgment result is output.

[0078] The trend analysis module 53 is used to call the cloud database interface to extract leakage area data of all test pieces in the same production batch, count the frequency of abnormal occurrences in valve body interface, threaded connection, sealing ring part and valve body shell area, and generate data reflecting the distribution of abnormal areas and the trend of change with production time.

[0079] The fault analysis module 54 establishes a process defect mapping model, inputs the change trend data of abnormal areas, calculates the problem factor weights of each process based on the model, and outputs the ranking of the processes that caused the faults and the problem coefficients.

[0080] Compared with existing technologies, this technology organically integrates pressure testing, multi-point gas sensing and three-dimensional leak location, cloud data management, and process defect mapping. It can collect pressure, flow rate, and trace tracer gas concentration in real time during the fully automated process. Through multi-sensor fusion and least squares iterative algorithms, it can achieve high-precision three-dimensional location of leak sources. Combined with batch traceability and cloud big data analysis, it can not only quickly determine the airtightness of solenoid valves, but also statistically analyze the distribution and trends of abnormal areas and quantify the problem coefficients of production processes, providing a scientific basis for quality control and process optimization.

[0081] Example 2

[0082] At other levels, this embodiment also provides another optimization mechanism based on Embodiment 1, specifically a gas measurement method for an OCV valve test bench, including the following steps:

[0083] Step 1: Set up the test bench and load test resources, and provide the system with power, multiple gas supply sources and communication connections through the mounting terminal;

[0084] Step 2: The drive cylinder clamp automatically positions and clamps the solenoid valve under test. This includes using two symmetrically installed cylinders to perform alignment actions, and deploying several gas sensors at the bottom side of the clamp to connect to the valve body. The gas sensors are arrayed. The gas sensors are semiconductor or infrared absorption type high-sensitivity sensors with a detection accuracy of not less than ±5ppm. The types of gases detected include helium, nitrogen, or tracer gases in air. The array of several gas sensors is arranged in a ring around the solenoid valve under test, with a spacing of 20mm between adjacent sensors. The polar coordinate data of each sensor is pre-written into the system configuration file.

[0085] Step 3: Identify the model and geometric features of the solenoid valve under test, including scanning the end face QR code and the shape image for model matching. If identification fails, manual intervention is triggered. At the same time, based on the central air source, the air is diverted to multiple test channels. After PID regulation and stabilization, N pressure steps are applied according to the preset program. Leakage flow data under each step is collected to generate the original air pressure flow curve.

[0086] Step 4: Monitor and locate the leak area. The gas sensor acquires multi-sensor concentration data in real time. After removing environmental noise, a spatial distribution model is constructed based on the three-dimensional coordinates of the gas sensor. The association rule between the leak source and the concentration gradient is established. The three-dimensional coordinates of the leak source are calculated through multivariate equation fitting and iterative optimization. The coordinates are then mapped to the valve body model and the leak location is marked.

[0087] Step 5: Determine the qualified status of the valve body and analyze production defects. Store test data in real time, compare the leakage flow with the preset threshold to output the judgment result, extract the leakage coordinates of all valve bodies in the same batch at the same time, and count the abnormal frequency of valve body interface, threaded connection, sealing ring and shell to generate spatiotemporal distribution trend.

[0088] Step 6: Establish a process defect mapping model, calculate the problem factor weights of each production process based on the abnormal area trend, output the fault process ranking and problem coefficient, and link it to the cloud database for batch quality traceability.

[0089] Example 3

[0090] This embodiment provides a calculation formula for the working logic of a process defect mapping model:

[0091]

[0092] In the formula, K i The problem coefficient represents the i-th process step, m represents the total number of leakage area categories, and a j The representative represents the weighting factor for the j-th type of leakage area, determined by the contribution of this type of leakage to the overall non-compliance rate in historical data, N. ij N represents the number of failures in the current batch caused by the i-th process leading to the j-th type of leakage area. j The problem coefficient K represents the total number of failures in the j-th type of leakage area in the current batch. i After sorting in descending order, the corresponding process priority ranking and quantification problem coefficient are output to locate the process that caused the fault.

[0093] In this embodiment, based on historical data statistics, the impact of different leakage areas on product failure is reflected. For example, leakage at the valve body sealing surface (a) j The probability of correlation is likely higher than that of minor leakage from the outer casing. This represents the percentage of responsibility for defects in a specific leakage area at the i-th process. For example, if the total number of leaks in the valve body threads of a certain batch is N... j =20, where N is the number of steps caused by assembly process i. ij If K = 15, then the association probability is 75%. Calculate K cumulatively. iBy comprehensively considering the impact of all leakage areas on process i, the overall problem coefficient of the process is quantified. The larger the value, the stronger the correlation between process defects. By dynamically linking leakage area data with production processes, the vague "abnormal trend" is transformed into a quantifiable problem coefficient, enabling precise location of process weaknesses and avoiding the lag and subjectivity of traditional manual experience analysis.

[0094] In summary, this invention integrates solenoid valve identification, image matching algorithms, and automatic cylinder clamping technology to achieve unmanned operation of solenoid valve model identification and clamping positioning. It also employs multi-pressure step testing and PID dynamic pressure stabilization control to significantly improve testing efficiency and pressure regulation accuracy, overcoming the low efficiency and error accumulation problems caused by traditional manual operation. Based on a three-dimensional spatial distribution model of multiple gas sensors, combined with a leak source coordinate iterative optimization algorithm and noise data filtering mechanism, it achieves millimeter-level positioning accuracy of the leak area. At the same time, it eliminates the influence of environmental interference through residual minimization processing, solving the defects of fuzzy positioning and high false alarm rate in the prior art.

[0095] By constructing a correlation mapping model between leakage data and production processes, and by statistically analyzing the spatiotemporal distribution trends of leakage areas in the same batch and calculating process problem coefficients, we can achieve reverse tracing from anomalies at the testing end to the root causes of defects at the manufacturing end, providing quantitative basis for process optimization and breaking through the limitations of isolated data analysis in traditional testing.

[0096] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An OCV valve test bench gas measurement system, characterized in that, The test bench body (1) includes two clamping and positioning modules (2) symmetrically installed inside. The bottom of the clamping and positioning module (2) is provided with a detection unit (3), which is installed inside the test bench body (1). An analysis unit (5) is installed on the right end of the test bench body (1). A leakage detection module (4) is installed on the bottom side of the clamping and positioning module (2). The test bench body (1) serves as the mounting end for various functional components and modules, providing power, air supply and communication connection. The clamping and positioning module (2) is used to drive the clamping action through a cylinder to complete the automatic alignment and clamping of the solenoid valve under test. Tight; Detection unit (3), used to electrically identify the model, serial number and geometric features of the solenoid valve under test, provide the solenoid valve under test with a preset index of air source pressure, and perform a sealing test on the solenoid valve under test under the action of several index air pressure intensities, and output the air tightness data of the original air pressure flow curve; Leakage capture module (4), used to deploy gas sensors to monitor the concentration of tracer gas in the air in real time, and when the reading of any sensor exceeds the set threshold, obtain the geometric position of the corresponding sensor and valve body, locate the leakage area by combining the data of several gas sensors, and output three-dimensional coordinates; Analysis unit (5), used to collect and store each test stage in real time. The air pressure, flow rate, leakage location, and timestamp data are compared with the air tightness data and preset thresholds to determine the qualified status of the solenoid valve under test. Based on the leakage area data of several solenoid valves under test in the same production batch, the distribution and trend of abnormal areas are statistically analyzed. Combined with the trend of abnormal areas, the production process problem coefficient that caused the failure is calculated. The detection unit (3) has sub-modules deployed below it. The sub-modules include a component identification module (31), a pressure control module (32), and an air tightness measurement module (33). The pressure control module (32) is connected to the component identification module (31) and the air tightness measurement module (33) through a wireless network. Among them: the component identification module (31) is used to identify the QR code and shape features of the solenoid valve end face, obtain the model and serial number through the image matching algorithm, and record them in the system database. If the identification fails, it triggers voice or interface prompts and waits for manual intervention; the pressure control module (32) is used to distribute the central air source provided by the test bench body (1) to each test channel and issue the target pressure value, and maintain stable pressure in real time with PID adjustment; the air tightness measurement module (33) is used to apply N pressure steps in sequence according to the preset test program, measure the leakage flow rate output by the flow meter under each pressure step, and transmit the leakage flow rate data to the analysis unit (5).

2. The OCV valve test bench gas measurement system according to claim 1, characterized in that, The process of locating the leakage area in the leakage detection module (4) is as follows: Based on the preset three-dimensional coordinate positions of each gas sensor, a sensor distribution space model composed of several solenoid valve solid models is constructed; the correlation rules between the leakage source position and the gas concentration detected by each sensor are set, wherein the correlation rules reflect the gradient distribution characteristics of the leakage gas concentration as a function of distance; the three-dimensional coordinates of the leakage source are used as the dependent variable, and the concentration weight coefficients and corresponding spatial coordinates of each sensor are used as independent variables to establish a multivariate linear relationship equation, and the equation parameters are determined by least squares fitting, and the initial solution of the leakage source coordinates is output; based on the initial solution of the leakage source coordinates, the theoretical gas concentration distribution is simulated, the residual between the actual sensor detection value and the theoretical value is compared, and the coordinate parameters are adjusted through multiple iterations to minimize the residual, and the optimized three-dimensional coordinate data is output; the optimized three-dimensional coordinate data is mapped onto the surface of the solid model of the solenoid valve under test, the spatial position of the leakage area is marked, and it is associated with the production batch and process information of the solenoid valve.

3. The OCV valve test bench gas measurement system according to claim 1, characterized in that, When a leak occurs, the leakage capture module (4) simultaneously acquires the real-time concentration values ​​of multiple sensors, eliminates outlier noise data caused by environmental interference, and retains the effective concentration detection signal.

4. The OCV valve test bench gas measurement system according to claim 1, characterized in that, The analysis unit (5) has sub-modules deployed below it. The sub-modules include a data acquisition and storage module (51), a qualification analysis module (52), a trend analysis module (53), and a fault analysis module (54). The data acquisition and storage module (51) is used to acquire the sensor data, pressure regulation data, and component identification data provided by the detection unit (3), write them to the local database in real time, and generate CSV / JSON log files in batches. After the test is completed, the logs are uploaded to the cloud database for backup periodically or as needed. The qualification analysis module (52) is used to read the collected pressure and flow curves and compare them with the preset maximum allowable leakage curve. If the leakage value of any pressure point exceeds the standard, it is judged as unqualified, and the corresponding leakage area coordinates are marked and the judgment result is output. The trend analysis module (53) is used to call the cloud database interface, extract the leakage area data of all test pieces in the same production batch, count the frequency of abnormal occurrence in the specified area, and generate data reflecting the distribution of abnormal areas and the trend of change with production time. The fault analysis module (54) establishes a process defect mapping model, inputs the trend data of abnormal areas, calculates the problem factor weight of each process in combination with the model, and outputs the sorting of the fault-causing processes and the problem coefficient.

5. The OCV valve test bench gas measurement system according to claim 4, characterized in that, The trend analysis module (53) includes the following areas: valve body interface, threaded connection, sealing ring part and valve body shell.

6. The OCV valve test bench gas measurement system according to claim 4, characterized in that, The calculation formula for the working logic of the process defect mapping model constructed by the fault analysis module (54) is as follows: In the formula, Representing the Problem coefficient of each process step Represents the total number of categories of leaked areas. The representative indicated the first Weighting factors for leaky regions Represents the current batch due to the first The process leads to the first Number of failures in leak-like areas Represents the first in the current batch Total number of failures and problem coefficient in leak-like areas After sorting in descending order, the corresponding process priority ranking and quantification problem coefficient are output to locate the process that caused the fault.

7. A gas measurement method for an OCV valve test bench, wherein the gas measurement method is an implementation method of the OCV valve test bench gas measurement system according to any one of claims 1-6, characterized in that, The process includes the following steps: Step 1: Set up the test bench and load test resources, providing power, multiple gas sources, and communication connections to the system via the mounting end; Step 2: Drive the cylinder clamp to automatically position and clamp the solenoid valve under test, including using two symmetrically installed cylinders to perform alignment actions, and deploying several gas sensors on the bottom side of the clamp to connect to the valve body, with the gas sensors forming an array; Step 3: Identify the model and geometric characteristics of the solenoid valve under test, including scanning the end face QR code and shape image for model matching. If identification fails, manual intervention is triggered. Simultaneously, based on the central gas source, the gas is diverted to multiple test channels. After PID regulation and stabilization, N pressure steps are applied according to a preset program, and leakage flow data at each step is collected to generate the original gas pressure-flow curve; Step 4: Monitor and locate the leakage area, and the gas... The sensor acquires multi-sensor concentration data in real time. After removing environmental noise, a spatial distribution model is constructed based on the three-dimensional coordinates of the gas sensor. The association rule between the leakage source and the concentration gradient is established. The three-dimensional coordinates of the leakage source are calculated through multivariate equation fitting and iterative optimization, mapped to the valve body model, and the leakage location is marked. Step 5: Determine the qualified status of the valve body and analyze production defects. Test data is stored in real time. The leakage flow rate is compared with the preset threshold to output the judgment result. The leakage coordinates of all valve bodies in the same batch are extracted simultaneously. The abnormal frequency of valve body interface, threaded connection, sealing ring and shell is statistically analyzed to generate spatiotemporal distribution trend. Step 6: Establish a process defect mapping model. The problem factor weight of each production process is calculated based on the abnormal area trend. The fault process ranking and problem coefficient are output and linked to the cloud database for batch quality traceability.

8. The gas measurement method for an OCV valve test bench according to claim 7, characterized in that, In step 2, the gas sensor is a semiconductor or infrared absorption type high-sensitivity sensor with a detection accuracy of not less than ±5ppm. The types of gases detected include helium, nitrogen, or tracer gases in the air medium.

9. The gas measurement method for an OCV valve test bench according to claim 7, characterized in that, In step 2, the array of several gas sensors is arranged in a ring around the solenoid valve under test. The distance between adjacent sensors is 10-30mm, and the polar coordinate data of each sensor is pre-written into the system configuration file.

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