Intelligent gas leakage detection platform for multi-gas joint detection

Abstract

The invention relates to the technical field of gas detection, and discloses an intelligent gas leakage detection platform for multi-gas joint detection, which comprises a gas analysis module, a leakage detection mode switching module, a parameter optimization module, a leakage diagnosis module and a visual report module. According to the platform, ion signal acquisition of various leak indicating gases is realized through the mass spectrometry device, normal pressure, vacuum dynamic and vacuum accumulation leak detection modes are supported, and leak detection parameters can be optimized according to real-time monitoring data. The leakage diagnosis module analyzes and positions a leakage point based on ion flow data, and the visual reporting module presents a result through a graphical interface and generates a detailed report. The system can meet the requirements of complex working conditions, improves the detection efficiency and precision, provides a scientific basis for leakage maintenance, and improves the stability and practicability of the system.

Description

Technical Field

[0001] This invention relates to the field of gas detection technology, specifically to an intelligent leak detection platform for multi-gas joint detection. Background Technology

[0002] Existing leak detection equipment typically requires manual switching of gas types or replacement of detection modules when detecting multiple indicator gases, resulting in low detection efficiency. Especially under complex operating conditions, users must rely on experience to select appropriate leak detection modes and parameters, increasing operational complexity. Due to the significant differences in characteristics among different indicator gases—for example, inert gases such as He, Kr, and Ar are easily affected by background contamination when coexisting with reactive gases—existing equipment struggles to achieve multi-gas joint detection while maintaining high sensitivity. Furthermore, existing equipment often lacks intelligent adaptive adjustment functions to meet the different operating conditions of the tested components, such as atmospheric pressure, vacuum dynamic, or vacuum cumulative leak detection, affecting the accuracy and consistency of detection results. Therefore, existing leak detection equipment has certain limitations in addressing diverse detection needs. Summary of the Invention

[0003] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes an intelligent leak detection platform for multi-gas joint detection. By integrating multiple detection units and intelligent control modules, it can realize the simultaneous or sequential detection of multiple leak detection gases, and supports multiple leak detection modes such as normal pressure, vacuum dynamic, and vacuum accumulation, thereby adapting to the different operating conditions of the tested components.

[0004] One embodiment of the present invention provides an intelligent leak detection platform for multi-gas joint detection, comprising: a gas analysis module for acquiring ion signals of various leak detection gases using a mass spectrometry analysis device; a leak detection mode switching module for selecting atmospheric pressure, vacuum dynamic, or vacuum cumulative leak detection modes according to the operating conditions of the tested component; a parameter optimization module for adjusting leak detection parameters based on the background gas composition of the system monitored in real time; a leak diagnosis module for generating diagnostic results of leak location and size based on ion flow data; and a visualization report module for presenting the data during the leak detection process to the user in a graphical form.

[0005] The gas analysis module employs a quadrupole mass spectrometer, which is used to separate and detect leak gas ion signals with molecular weights ranging from 1 to 200. The gas analysis module is connected to multiple gas channels via pneumatic valves, each channel corresponding to a different leak gas. Switching between channels allows for rapid detection of different gas types.

[0006] The leak detection mode switching module includes a dynamic leak detection chamber and a vacuum accumulation chamber. The dynamic leak detection chamber is connected to the test piece via a pipeline and is suitable for vacuum dynamic leak detection; the vacuum accumulation chamber is used for cumulative leak detection of small, fully sealed test pieces. The gas flow direction between the leak detection chambers is controlled by pneumatic valves to ensure flexible switching between different leak detection modes. The dynamic leak detection chamber is equipped with an adsorption pump, which has a selective gas extraction function, capable of removing reactive gases (such as N2, O2, H2) while retaining inert gases (such as He, Ar, Kr) for leak detection.

[0007] The parameter optimization module includes a processor, memory, and control software. The processor automatically adjusts the leak detection parameters by monitoring the system's background gas composition in real time and combining this with a pre-stored leak detection parameter database in the memory. The control software has a built-in rule engine that can generate the optimal parameter combination based on the current leak detection mode and the type of leaking gas. Furthermore, the parameter optimization module supports machine learning algorithms, which gradually improve the accuracy of parameter adjustments by learning from historical leak detection data.

[0008] The leak diagnosis module identifies leak patterns and locates leak points by analyzing the changing trends of ion current intensity. For atmospheric pressure leak detection, a gas sample is drawn from the area surrounding the test piece using a suction gun. The gas analysis module obtains the ion current intensity of the leak-indicating gas and compares it with standard leak data to calculate the leak value. For vacuum dynamic leak detection, the test piece is connected to the vacuum side, and the leak-indicating gas enters the dynamic leak detection chamber through the leak hole. The system dynamically calculates the leak value based on the ion current intensity, supporting detection in both forward and reverse pumping directions. For vacuum accumulation leak detection, the test piece is placed in a vacuum accumulation chamber, and an adsorption pump accumulates the inert gas signal. The system monitors the ion current rise rate and calculates the leak amount, suitable for detecting minute leaks.

[0009] The visualization report module displays real-time data via a touchscreen or remote terminal, allowing users to set parameters and view leak detection results through the interface. After the leak detection data is recorded and analyzed, a visualization report is generated that includes the leak location, size, and recommended actions. The report supports exporting to multiple formats for easy archiving or further processing.

[0010] According to some embodiments of the present invention, the gas analysis module further includes a gas switching component for rapid switching between different leak gases. The gas switching component consists of a pneumatic valve and a vacuum pump. The pneumatic valve controls the opening and closing of the gas channel, and the vacuum pump is responsible for introducing the selected gas into the mass spectrometer. During the switching process, the system automatically removes residual gas to avoid cross-contamination.

[0011] According to some embodiments of the present invention, the leak detection mode switching module further includes a sensitivity calibration component for calibrating the detection sensitivity of the system. The sensitivity calibration component includes positive pressure standard leak holes and negative pressure standard leak holes, used to simulate leakage under different pressure conditions. The system automatically calculates the leakage value by comparing the detection data of the standard leak holes with that of the tested component.

[0012] According to some embodiments of the present invention, the parameter optimization module further includes an environmental compensation component for eliminating the influence of external environmental factors on the leak detection results. The environmental compensation component monitors changes in temperature, humidity, and air pressure through sensors and inputs the monitoring data into a processor, which then adjusts the leak detection parameters according to a preset algorithm.

[0013] According to some embodiments of the present invention, the leak diagnosis module further includes a leak pattern recognition component for distinguishing the characteristics of different types of leaks. The leak pattern recognition component extracts leak characteristics and classifies them into minor, moderate, or severe leaks based on time-series analysis of ion flow data. The classification results are used to guide subsequent maintenance work.

[0014] According to some embodiments of the present invention, the visualization report module further includes a remote monitoring component for transmitting leak detection data to a remote server via a wireless communication network. The remote server performs secondary analysis on the received data and generates a more detailed diagnostic report. Users can access the remote server via mobile devices to view the leak detection progress and results in real time.

[0015] The embodiments of this invention offer at least the following beneficial effects: The platform of these embodiments integrates a gas analysis module and a leak detection mode switching module, enabling simultaneous or sequential detection of multiple leak-indicating gases and supporting multiple leak detection modes to meet the needs of different tested components under various operating conditions. Through the real-time adjustment function of the parameter optimization module, the system can adapt to complex operating conditions, reducing human intervention and improving detection efficiency. The leak diagnosis module, through in-depth analysis of ion flow data, accurately locates leak points and assesses the degree of leakage, providing a scientific basis for subsequent maintenance. The visualization report module enhances the user experience through an intuitive graphical interface and detailed diagnostic reports. Furthermore, the introduction of environmental compensation and remote monitoring components further enhances the system's stability and practicality, enabling it to perform excellently in diverse application scenarios. Attached Figure Description

[0016] Figure 1 This is an overall structural block diagram of the module in an embodiment of the present invention; Figure 2 This is a block diagram of the gas analysis module in an embodiment of the present invention; Figure 3 This is a block diagram of the leak detection mode switching module in an embodiment of the present invention; Figure 4 This is a block diagram of the visualization report module in an embodiment of the present invention; Figure 5 This is a flowchart illustrating the leak detection mode switching process in an embodiment of the present invention. Detailed Implementation

[0017] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] The multi-gas joint detection intelligent leak detection gas platform of this invention, as described in this embodiment, is as follows: Figure 1 As shown, the overall structure includes a gas analysis module, a leak detection mode switching module, and a visualization report module. The gas analysis module is located on the left side of the platform and is connected to the leak detection mode switching module via a pipe. The visualization report module is located on the right side of the platform and is connected to both the gas analysis module and the leak detection mode switching module via a data cable. Figure 2 As shown, the core component of the gas analysis module is a quadrupole mass spectrometer, which is directly connected via an internal channel and located near the gas inlet. A gas switching assembly is positioned at the front end of the gas analysis module and connects to multiple gas channels via pneumatic valves, each channel corresponding to a different leak gas. A vacuum pump in the gas switching assembly introduces the selected gas into the quadrupole mass spectrometer for analysis via a pipeline.

[0019] Leak detection mode switching module, such as Figure 3 As shown, the module includes a dynamic leak detection chamber and a vacuum accumulation chamber, both controlled by pneumatic valves. The dynamic leak detection chamber, located at the top of the module, is connected to the test piece via piping and is suitable for dynamic vacuum leak detection. The vacuum accumulation chamber, located at the bottom of the module, is used for cumulative leak detection of small, fully sealed test pieces. The dynamic leak detection chamber is equipped with an adsorption pump, connected to the side wall of the chamber via piping. This pump selectively removes reactive gases such as N2, O2, and H2 while retaining inert gases such as He, Ar, and Kr for leak detection. A sensitivity calibration component is located on one side of the leak detection mode switching module, including positive and negative pressure standard leak holes, used to simulate leaks under different pressure conditions. The sensitivity calibration component is connected to the dynamic leak detection chamber and the vacuum accumulation chamber via piping to calibrate the system's detection sensitivity.

[0020] Visualized reporting modules, such as Figure 4As shown, the system includes a touchscreen, which connects to the gas analysis module and the leak detection mode switching module via a data cable. The touchscreen interface is divided into a data display area and a parameter setting area. The data display area shows the real-time ion flow intensity change curve and leak diagnosis results, while the parameter setting area allows users to manually adjust the leak detection parameters. The touchscreen also supports remote monitoring, transmitting leak detection data to a remote server via a wireless communication network. Users can access the server via mobile devices to view detailed diagnostic reports.

[0021] In actual operation, the gas switching component first selects a specific gas channel according to user settings. A pneumatic valve opens the selected channel while closing other channels, and a vacuum pump introduces the selected gas into a quadrupole mass spectrometer for analysis. The quadrupole mass spectrometer separates and detects leak gas ion signals with molecular weights ranging from 1 to 200. The gas analysis module is connected to multiple gas channels via pneumatic valves, each channel corresponding to a different leak gas. Switching between valves enables rapid detection of different gas types. During switching, the system automatically removes residual gas to prevent cross-contamination.

[0022] like Figure 5 As shown, the leak detection mode switching module selects between atmospheric pressure, vacuum dynamic, or vacuum accumulation leak detection modes based on the operating conditions of the tested component. In atmospheric pressure leak detection mode, a suction gun is used to sample the gas around the tested component. The gas analysis module obtains the ion current intensity of the leak-indicating gas and compares it with standard leak data to calculate the leak value. In vacuum dynamic leak detection mode, the tested component is connected to the vacuum side of the dynamic leak detection chamber. The leak-indicating gas enters the dynamic leak detection chamber through the leak hole. The system dynamically calculates the leak value based on the ion current intensity, supporting detection in both forward and reverse pumping directions. In vacuum accumulation leak detection mode, the tested component is placed in the vacuum accumulation chamber. An adsorption pump accumulates the inert gas signal, and the system monitors the ion current rise rate to calculate the leak amount, suitable for detecting minute leaks. A pneumatic valve controls the gas flow direction between the dynamic leak detection chamber and the vacuum accumulation chamber, ensuring flexible switching between different leak detection modes.

[0023] The parameter optimization module monitors the system's background gas composition in real time through the processor and automatically adjusts the leak detection parameters based on a pre-stored leak detection parameter database in memory. The control software has a built-in rule engine that generates the optimal parameter combination based on the current leak detection mode and the type of leaking gas. The environmental compensation component monitors changes in temperature, humidity, and air pressure through sensors and inputs the monitoring data into the processor, which then adjusts the leak detection parameters according to a preset algorithm. The parameter optimization module also supports machine learning algorithms, gradually improving the accuracy of parameter adjustments by learning from historical leak detection data.

[0024] The leak diagnosis module identifies leak patterns and locates leak points by analyzing the changing trends of ion current intensity. For atmospheric pressure leak detection, a gas sample is drawn from the area surrounding the tested component using a suction gun. The gas analysis module obtains the ion current intensity of the leak-indicating gas and compares it with standard leak data to calculate the leak value. For vacuum dynamic leak detection, the tested component is connected to the vacuum side of the dynamic leak detection chamber. The leak-indicating gas enters the chamber through the leak hole, and the system dynamically calculates the leak value based on the ion current intensity, supporting detection in both forward and reverse pumping directions. For vacuum accumulation leak detection, the tested component is placed in a vacuum accumulation chamber, and an inert gas signal is accumulated using an adsorption pump. The system monitors the ion current rise rate to calculate the leak amount, suitable for detecting minute leaks. The leak pattern identification component extracts leak characteristics based on time-series analysis of ion current data and classifies them into minute, moderate, or severe leaks. The classification results guide subsequent maintenance work.

[0025] The visualization reporting module displays real-time data via a touchscreen, allowing users to set parameters and view leak detection results through the interface. After recording and analysis, leak detection data generates a visualization report containing the leak location, size, and recommended actions. The report supports export to various formats for user archiving or further processing. The remote monitoring component transmits leak detection data to a remote server via a wireless communication network. The remote server performs secondary analysis on the received data and generates a more detailed diagnostic report. Users can access the remote server via mobile devices to view the leak detection progress and results in real time.

[0026] The platform in this invention integrates a gas analysis module and a leak detection mode switching module to achieve simultaneous or sequential detection of multiple leak-indicating gases, and supports multiple leak detection modes to meet the needs of different tested components under various operating conditions. Through the real-time adjustment function of the parameter optimization module, the system can adapt to complex operating conditions, reducing human intervention and improving detection efficiency. The leak diagnosis module accurately locates leak points and assesses the degree of leakage through in-depth analysis of ion flow data, providing a scientific basis for subsequent maintenance. The visualization report module enhances the user experience through an intuitive graphical interface and detailed diagnostic reports. Furthermore, the introduction of environmental compensation components and remote monitoring components further enhances the system's stability and practicality, enabling it to perform excellently in diverse application scenarios.

[0027] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. An intelligent leak detection platform for multi-gas combined leak detection, characterized in that, The method comprises the following steps: a gas analysis module for collecting ion signals of multiple tracer gases by a mass spectrometer; a leak detection mode switching module for selecting normal pressure, vacuum dynamic or vacuum accumulation leak detection mode according to the working condition of the detected part; a parameter optimization module for adjusting leak detection parameters according to the real-time monitored system background gas composition; a leak diagnosis module for generating a diagnosis result of the leak location and size based on ion current data; a visual report module for presenting the data in the leak detection process to the user in a graphical form.

2. The intelligent leak detection platform for multi-gas combined leak detection according to claim 1, characterized in that, The gas analysis module adopts a quadrupole mass spectrometer, wherein: The quadrupole mass spectrometer is used to separate and detect ion signals of tracer gases with molecular weight ranging from 1 to 200; The gas analysis module is connected to multiple gas channels through pneumatic valves, each channel corresponding to a tracer gas, and the rapid detection of different gas types is realized through valve switching. 3.The intelligent leak detection platform of claim 1, wherein, The leak detection mode switching module includes a dynamic leak detection chamber and a vacuum accumulation chamber, wherein: The dynamic leak detection chamber is connected to the detected part through a pipeline and is suitable for vacuum dynamic leak detection; The vacuum accumulation chamber is used for the accumulation leak detection of small full-sealed detected parts; the gas path flow direction between the leak detection chambers is controlled through pneumatic valves to ensure flexible switching between different leak detection modes; The dynamic leak detection chamber is equipped with a sorption pump, which has a selective pumping function and can pump away active gases while retaining inert gases for leak detection.

4. The intelligent leak detection platform for multi-gas combined leak detection according to claim 1, characterized in that, The parameter optimization module includes a processor, a memory and control software, the processor automatically adjusts the leak detection parameters by real-time monitoring of the system background gas composition combined with the pre-stored leak detection parameter database in the memory; the control software has a built-in rule engine that can generate the optimal parameter combination according to the current leak detection mode and tracer gas type; the parameter optimization module also supports machine learning algorithms to gradually improve the accuracy of parameter adjustment through learning from historical leak detection data.

5. The intelligent leak detection platform for multi-gas combined leak detection according to claim 1, characterized in that, The leak diagnosis module identifies the leak mode and locates the leak point by analyzing the trend of ion current intensity; For normal pressure leak detection mode, the gas sample around the detected part is sucked by a suction gun, the ion current intensity of the tracer gas is obtained by the gas analysis module, and the leak value is calculated by comparing with the standard leak hole data; For vacuum dynamic leak detection mode, the detected part is connected to the vacuum side of the dynamic leak detection chamber, the tracer gas enters the dynamic leak detection chamber through the leak hole, and the system calculates the leak value based on the ion current intensity; For vacuum accumulation leak detection mode, the detected part is placed in the vacuum accumulation chamber, the inert gas signal is accumulated by the sorption pump, and the system monitors the ion current rise rate to calculate the leak amount.

6. The intelligent leak detection platform for multi-gas combined leak detection according to claim 1, wherein, The visual report module includes a touch screen connected to the gas analysis module and the leak detection mode switching module through data lines for displaying real-time data; The user can set parameters and view leak detection results through the interface; Leak detection data is recorded and analyzed to generate a visual report containing the leak location, size and recommended measures; The report supports export in multiple formats for user archiving or further processing.

7. The intelligent leak detection platform for multi-gas combined leak detection according to claim 2, characterized in that, The gas analysis module also includes a gas switching assembly for rapid switching between different tracer gases; The gas switching assembly consists of a pneumatic valve and a vacuum pump, the pneumatic valve controls the opening and closing of the gas channel, and the vacuum pump is responsible for introducing the selected gas into the mass spectrometer. During the switching process, the system automatically removes residual gas to avoid cross contamination.

8. The intelligent leak detection platform for multi-gas combined leak detection according to claim 3, characterized in that, The leak detection mode switching module further comprises a sensitivity calibration component for calibrating the detection sensitivity of the system; The sensitivity calibration component comprises a positive pressure standard leak and a negative pressure standard leak, which are respectively used to simulate leakage conditions under different pressure conditions; The system automatically calculates the leakage value by comparing the detection data of the standard leak and the detected part.

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