Intelligent laboratory gas path monitoring system

Abstract

The invention provides an intelligent laboratory gas path monitoring system which comprises a data acquisition module, a feature detection module, a data analysis module and a risk early warning module. The data acquisition module is used for constructing a gas path monitoring database; the data acquisition module comprises a data processing unit and a database construction unit, and the data processing unit is used for acquiring gas path monitoring data from a plurality of data sources and preprocessing and cleaning the gas path monitoring data; the database construction unit constructs a gas path monitoring database according to the gas path monitoring data; the feature detection module is used for detecting gas path index features and constructing a gas path feature curve according to the gas path monitoring database and the gas path index features; the feature detection module comprises a flow measurement and calculation unit, a gas path operation state feature construction unit and a gas path parameter feature construction unit; the flow measuring and calculating unit is used for acquiring flow data and calculating real-time flow data entering the equipment and the container through a flow meter.

Description

Technical Field

[0001] The present invention belongs to the field of monitoring, and particularly relates to a smart laboratory gas pipeline monitoring system. Background Art

[0002] At present, the smart laboratory gas pipeline monitoring system plays an increasingly important role in modern laboratory management, especially in ensuring laboratory environmental safety, improving experimental efficiency, and optimizing resource management. By real-time monitoring parameters such as gas flow, pressure, temperature, and humidity in the laboratory, the system can timely detect potential safety hazards and ensure the health of experimental personnel and the smooth progress of experiments. However, there are still some significant defects in the current gas pipeline monitoring technology in practical applications, which limit its performance and promotion.

[0003] The existing gas pipeline monitoring systems have deficiencies in the selection and accuracy of sensors. Many systems use sensors that cannot meet the requirements of high-standard laboratories in terms of sensitivity and accuracy. Especially when monitoring some low-concentration harmful gases, the response speed and detection range of the sensors may be insufficient. This results in the system being unable to issue an alarm in time when detecting gas leakage or abnormal concentration, thus increasing the safety hazards in the laboratory. In addition, the problems of sensor aging and drift will also affect the accuracy of monitoring data, leading laboratory managers to rely on unreliable information when making decisions.

[0004] The existing technologies are also insufficient in data processing and analysis capabilities. Although many gas pipeline monitoring systems can collect a large amount of data, they often lack effective data analysis tools and are unable to deeply mine and analyze these data. This makes it difficult for laboratory managers to extract valuable information from the data, thereby affecting the comprehensive understanding and optimized management of the laboratory environment. Many systems only provide basic monitoring and recording functions, lacking intelligent data analysis and early warning mechanisms, resulting in a lag in the laboratory's response to emergencies.

[0005] The user interfaces and operation experiences of the existing gas pipeline monitoring systems are often not friendly enough. The operation interfaces of many systems are complex and lack intuitive visualization functions, making laboratory personnel spend more time learning and adapting when using them. This inconvenient user experience not only reduces the use efficiency of the system but also may lead to operation errors in case of emergencies. In addition, the functions of the system in data display and report generation are also relatively single and cannot meet the diverse needs of laboratory personnel for data analysis and reports.

[0006] The existing technologies also have limitations in system integration and interconnection. Many gas path monitoring systems often operate independently and lack effective integration with other laboratory equipment and systems. This information island phenomenon prevents laboratory managers from obtaining a comprehensive real-time laboratory status, affecting the overall management efficiency. An ideal gas path monitoring system should be able to seamlessly interface with the laboratory's environmental monitoring, equipment control, and data management systems to achieve information sharing and collaborative work.

[0007] The existing gas path monitoring systems also have relatively high requirements for maintenance and upgrading. Many systems were not designed with sufficient consideration for the convenience of daily maintenance, resulting in a cumbersome and time-consuming repair process when faults occur. This maintenance difficulty not only increases labor costs but also may lead to an extended system downtime, affecting the normal operation of the laboratory. Especially in a high-intensity laboratory environment, the reliability and maintainability of equipment are particularly important. Therefore, improving the maintainability and design rationality of the gas path monitoring system is an urgent issue to be solved.

[0008] The intelligent laboratory gas path monitoring system still has obvious defects in aspects such as sensor accuracy, data processing ability, user experience, system integration, and maintenance management. These problems not only affect the performance and service life of the system but also reduce the efficiency and safety of laboratory management. Therefore, conducting in-depth research and improvement on these technical defects will help improve the overall performance of the gas path monitoring system to better meet the needs of modern laboratories. Summary of the Invention

[0009] The present invention proposes an intelligent laboratory gas path monitoring system. This intelligent laboratory gas path monitoring system solves the problems of low gas path monitoring accuracy, insufficient data analysis ability, lagging risk warning, and poor system integration in the existing technologies through the collaborative work of multiple modules including data acquisition, feature detection, data analysis, and risk warning, and realizes real-time monitoring, precise analysis, and intelligent warning of the gas path operation status.

[0010] The technical solution of the present invention is implemented as follows: An intelligent laboratory gas path monitoring system includes a data acquisition module, a feature detection module, a data analysis module, and a risk warning module;

[0011] The data acquisition module is used to construct a gas path monitoring database; the data acquisition module includes a data processing unit and a database construction unit. The data processing unit is used to obtain gas path monitoring data from multiple data sources and perform preprocessing and cleaning on it; the database construction unit constructs a gas path monitoring database based on the gas path monitoring data;

[0012] The feature detection module is used to detect the characteristics of the gas path indicators, and construct a gas path characteristic curve based on the gas path monitoring database and the gas path indicator characteristics; the feature detection module includes a flow rate calculation unit, a gas path operation state characteristic construction unit, and a gas path parameter characteristic construction unit; the flow rate calculation unit is used to obtain flow rate data and calculate the real-time flow rate data entering the equipment and the container interior through a flow meter; the gas path operation state characteristic construction unit is used to obtain real-time gas collection data, equipment and container parameter data; the gas path parameter characteristic construction unit is used to construct a gas path characteristic curve according to the real-time collection data, equipment and container parameter data, and the set analysis rules;

[0013] The data analysis module is used to analyze and process the gas path monitoring data, and generate a gas path operation risk assessment report according to the analysis results; the data analysis module includes an information extraction unit, a parameter modeling unit, and a risk assessment unit; among them, the information extraction unit is used to obtain the gas path operation data from the data collection module for information extraction, and perform parameter modeling according to the extracted parameters; the parameter modeling unit builds a gas path model based on the parameters, and analyzes the gas path operation parameters through the gas path model; the risk assessment unit performs real-time risk assessment according to the gas path operation state and the gas path operation parameters, and imports the assessment parameters into the risk warning module;

[0014] The risk warning module is used to give warnings for abnormal data and trend changes.

[0015] Through the data processing unit and the database construction unit in the data collection module, gas path monitoring data is obtained from multiple data sources, and preprocessing and cleaning are performed to ensure the integrity and accuracy of the data. The database construction unit constructs a gas path monitoring database according to the cleaned data, providing high-quality data support for subsequent analysis. The technical difficulty of this lies in how to construct a comprehensive and reliable gas path monitoring database through multi-source data fusion and efficient cleaning.

[0016] This system, through the flow rate calculation unit, the gas path operation state characteristic construction unit, and the gas path parameter characteristic construction unit in the feature detection module, obtains real-time flow rate data, gas collection data, equipment and container parameter data, and constructs a gas path characteristic curve according to the set analysis rules. The technical difficulty of this lies in how to construct a characteristic curve that can accurately reflect the gas path operation state through the collaborative analysis of multi-parameter data. The information extraction unit, the parameter modeling unit, and the risk assessment unit in the data analysis module extract key parameters from the gas path monitoring data, establish a gas path model, and obtain the gas path operation parameters and risk assessment results through model analysis. The technical difficulty of this lies in how to achieve accurate assessment of the gas path operation state and risk prediction through parameter modeling and model analysis.

[0017] Through the risk warning module, this system monitors the operation status and parameters of the gas pipeline in real time, discovers abnormal data and trend changes in a timely manner, and generates warning signals. The technical difficulty lies in how to achieve accurate warning and rapid response to the operation risks of the gas pipeline through real-time data analysis and trend prediction. Through the risk warning module, this system monitors the operation status and parameters of the gas pipeline in real time, discovers abnormal data and trend changes in a timely manner, and generates warning signals. The technical difficulty lies in how to achieve accurate warning and rapid response to the operation risks of the gas pipeline through real-time data analysis and trend prediction.

[0018] As a preferred embodiment, the data processing unit includes a data synchronization unit, a data cleaning unit, and a database construction unit. The data synchronization unit obtains gas pipeline monitoring data from multiple data sources and synchronizes the data. The data cleaning unit is used to detect and process outliers, missing values, duplicate values, and error data in the data. The database construction unit is used to store the cleaned gas pipeline monitoring data into the gas pipeline monitoring database.

[0019] As a preferred embodiment, the feature detection module further includes a pipeline status analysis unit. A pipeline status model is established based on the real-time gas collection data and environmental condition data obtained by the pipeline status analysis unit, and the corrosion, air pressure, and temperature status of the pipeline are analyzed in real time.

[0020] As a preferred embodiment, the pipeline status analysis unit internally includes a model construction module, a pipeline processing module, and a control module. The model construction module establishes a pipeline status model based on the real-time gas collection data and environmental condition data obtained, and analyzes the corrosion degree, air pressure, and temperature status of the pipeline in real time. The pipeline processing module processes and analyzes the pipeline status based on the detection data of the corrosion degree, air pressure, and temperature status of the pipeline and the environmental condition data. The control module issues control instructions according to the analysis results, and issues abnormal warnings for abnormal temperature and flow of the pipeline.

[0021] As a preferred embodiment, the risk warning module internally has safety thresholds, which include flow velocity characteristic values, flow rate characteristic values, pressure characteristic values, and humidity characteristic values. According to the historical data and potential risks of the gas pipeline monitoring data, the safety thresholds of the flow velocity characteristic values, flow rate characteristic values, pressure characteristic values, and humidity characteristic values are set and stored in the gas pipeline safety database. The safety thresholds are set based on the flow velocity, flow rate of the gas in the gas pipeline, and the airtightness of the gas pipeline system.

[0022] As a preferred embodiment, the risk warning module includes an alarm unit and a visualization unit. The alarm unit is used to give an alarm when an abnormal situation is detected. The visualization unit is used to display the gas pipeline monitoring data, characteristic curves, and safety thresholds.

[0023] After adopting the above technical solution, the beneficial effects of the present invention are as follows: Through the collaborative work of the data acquisition module, feature detection module, data analysis module, and risk warning module, the intelligent laboratory gas pipeline monitoring system realizes the real-time monitoring, precise analysis, and intelligent warning of the operation status of the gas pipeline.

[0024] The data acquisition module constructs a comprehensive and reliable gas pipeline monitoring database through multi-source data fusion and efficient cleaning, providing high-quality data support for subsequent analysis. The feature detection module, through the flow measurement unit, the gas pipeline operation status feature construction unit, and the gas pipeline parameter feature construction unit, obtains flow data, gas collection data, and equipment and container parameter data in real time, and constructs a feature curve reflecting the operation status of the gas pipeline, providing a basis for the precise analysis of the operation status of the gas pipeline. The data analysis module, through the information extraction unit, the parameter modeling unit, and the risk assessment unit, extracts key parameters from the gas pipeline monitoring data, establishes a gas pipeline model, and obtains the operation parameters and risk assessment results of the gas pipeline through model analysis, realizing the in-depth analysis and risk prediction of the operation status of the gas pipeline.

[0025] The risk warning module, through the real-time monitoring of the operation status and parameters of the gas pipeline, timely discovers abnormal data and trend changes, and generates warning signals, realizing the precise warning and rapid response to the operation risks of the gas pipeline. Through the data interaction and collaborative control of multiple modules, the system realizes the comprehensive acquisition, precise analysis, and intelligent warning of gas pipeline monitoring data, improving the operation efficiency and stability of the system. This system not only solves the problems of low gas pipeline monitoring accuracy, insufficient data analysis ability, lagging risk warning, and poor system integration in the existing technology, but also provides an efficient, precise, and intelligent solution for the safe operation of laboratory gas pipelines, with significant technical advantages and application values. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0027] Figure 1 It is the system flow block diagram of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0028] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0029] Embodiment:

[0030] As Figure 1 shown, the intelligent laboratory gas pipeline monitoring system described in this application aims to provide real-time gas monitoring and management for the laboratory to ensure the safety and efficiency of the laboratory. A specific implementation scenario can be envisioned as a chemical laboratory that needs to monitor the gas flow rate, pressure, and composition in real time to ensure the safety and reliability of the experimental process.

[0031] In this implementation scenario, the overall structure of the system includes a data acquisition module, a feature detection module, a data analysis module, and a risk warning module. First, the data acquisition module is responsible for constructing a gas pipeline monitoring database. This module consists of a data processing unit and a database construction unit. The data processing unit obtains gas pipeline monitoring data from multiple data sources, including devices such as flow meters, pressure sensors, and gas composition analyzers, and performs preprocessing and cleaning to ensure the accuracy and integrity of the data. Through this process, the system can collect real-time data on gas flow rate, pressure, and composition changes in the laboratory, providing a reliable basis for subsequent analysis.

[0032] The database construction unit then stores the processed gas pipeline monitoring data in the gas pipeline monitoring database, forming a centralized management data platform. This database not only facilitates subsequent data analysis but also provides the function of historical data query for laboratory management personnel to help them understand the long-term operating status of the gas pipeline.

[0033] The feature detection module is used to detect the characteristics of gas pipeline indicators. This module includes a flow rate calculation unit, a gas pipeline operation status feature construction unit, and a gas pipeline parameter feature construction unit. The flow rate calculation unit obtains real-time flow rate data entering the equipment and containers through the flow meter and performs real-time monitoring to ensure that the gas flow during the experiment meets the expectations. The gas pipeline operation status feature construction unit analyzes the operation status of the gas pipeline by collecting real-time gas data and equipment parameter data. The gas pipeline parameter feature construction unit constructs a gas pipeline characteristic curve based on real-time data, equipment parameters, and set analysis rules to provide a visual display of the gas pipeline operation status.

[0034] The role of the data analysis module is to deeply analyze the gas path monitoring data and generate a gas path operation risk assessment report based on the analysis results. The information extraction unit obtains the gas path operation data from the data acquisition module for information extraction and performs parameter modeling according to the extracted parameters. The parameter modeling unit establishes a gas path model based on the extracted parameters and obtains the key parameters of the gas path operation through model analysis. This process not only helps laboratory managers understand the current gas path status but also enables the prediction of potential risks.

[0035] The risk assessment unit conducts real-time risk assessment based on the gas path operation status and operation parameters and imports the assessment results into the risk warning module. The risk warning module is responsible for warning of abnormal data and trend changes. When the system detects abnormal flow, pressure, or composition changes in the gas path, the module will immediately issue an alarm to notify laboratory staff to take corresponding measures. This mechanism greatly improves the safety of the laboratory and reduces potential safety hazards.

[0036] In the entire workflow, each component cooperates with each other to form an efficient gas path monitoring system. The data acquisition module is responsible for real-time monitoring and data storage, the feature detection module conducts data analysis and feature extraction, the data analysis module provides in-depth analysis and risk assessment, and the risk warning module ensures that the laboratory can respond in a timely manner in case of abnormalities.

[0037] The intelligent laboratory gas path monitoring system realizes the comprehensive monitoring and management of the laboratory gas path through advanced technical means. The effective implementation of its working principle and process not only improves the safety and efficiency of the laboratory but also provides strong support for the intelligent management of the laboratory, promoting the modernization process of laboratory management. As a preferred implementation manner, the data processing unit includes a data synchronization unit, a data cleaning unit, and a database construction unit. Among them, the data synchronization unit obtains gas path monitoring data from multiple data sources and realizes data synchronization; the data cleaning unit is used to detect and process outliers, missing values, duplicate values, and error data in the data; the database construction unit is used to store the cleaned gas path monitoring data into the gas path monitoring database.

[0038] The feature detection module also includes a pipeline status analysis unit. A pipeline status model is established based on the real-time gas acquisition data and environmental condition data obtained by the pipeline status analysis unit, and the corrosion, air pressure, and temperature status of the pipeline are analyzed in real time. In the feature detection module, the design of the pipeline status analysis unit can establish a pipeline status model by obtaining real-time gas acquisition data and environmental condition data, and can analyze the corrosion, air pressure, and temperature status of the pipeline in real time. The use of this technical solution in a specific working scenario is reflected in its importance for pipeline health monitoring. For example, in industries such as chemical engineering, petroleum, and natural gas, pipelines often carry high-pressure gases and corrosive substances. Pipeline corrosion and temperature changes may lead to serious safety hazards and economic losses. Through real-time monitoring and analysis, enterprises can timely detect potential problems in pipelines, such as an increase in corrosion degree, abnormal air pressure, or too high temperature, and thus take preventive measures to avoid accidents. For example, if it is detected that the corrosion degree exceeds the safety range, the enterprise can arrange maintenance personnel for inspection and repair to ensure the safe operation of the pipeline.

[0039] The pipeline status analysis unit is built-in with a model construction module, a pipeline processing module, and a control module. The model construction module establishes a pipeline status model based on the real-time gas acquisition data and environmental condition data obtained, and analyzes the corrosion degree, air pressure, and temperature status of the pipeline in real time; the pipeline processing module processes and analyzes the pipeline status according to the detection data of the corrosion degree, air pressure, and temperature status of the pipeline and the environmental condition data; the control module issues control instructions according to the analysis results, and issues abnormal warnings for abnormal pipeline temperature and abnormal flow.

[0040] In the design of the model construction module, pipeline processing module, and control module built into the pipeline status analysis unit, the model construction module uses the real-time acquired data to establish a pipeline status model and analyzes the corrosion degree, air pressure, and temperature status of the pipeline in real time. The application of this solution in a specific working scenario can achieve intelligent monitoring and management of pipelines. Through the pipeline processing module, the system can not only analyze the status of the pipeline, but also perform data processing and decision support according to the detected corrosion degree, air pressure, and temperature status. The control module issues control instructions according to the analysis results and warns of abnormal pipeline temperature and abnormal flow. This comprehensive monitoring and control mechanism can help enterprises achieve refined management of pipelines and improve safety and efficiency. For example, when abnormal air pressure is detected, the system can automatically adjust the valve to reduce the pressure and avoid the risk of pipeline rupture.

[0041] The risk warning module is built-in with safety thresholds, which include flow velocity characteristic values, flow rate characteristic values, pressure characteristic values, and humidity characteristic values. The safety thresholds of the flow velocity characteristic values, flow rate characteristic values, pressure characteristic values, and humidity characteristic values are set according to the historical data and potential risks of the gas path monitoring data and stored in the gas path safety database. The safety thresholds are set based on the flow velocity, flow rate of the gas in the gas path, and the airtightness of the gas path system. In the design of the risk warning module, the built-in safety thresholds include flow velocity characteristic values, flow rate characteristic values, pressure characteristic values, and humidity characteristic values, and these characteristic values are set according to the historical data and potential risks of the gas path monitoring data. The application of this technical solution in specific working scenarios ensures the safe operation of the gas path system. For example, in a natural gas pipeline, if the flow velocity or pressure exceeds the set safety threshold, serious consequences such as leakage or explosion may occur. By real-time monitoring and storing these characteristic values, enterprises can timely identify potential risks and take corresponding preventive measures, thereby effectively reducing safety hazards. Such a risk management system is particularly important in high-risk industries and can ensure the safety of employees and the normal operation of equipment.

[0042] The risk warning module includes an alarm unit and a visualization unit. The alarm unit is used to give an alarm when an abnormal situation is detected. The visualization unit is used to display the gas path monitoring data, characteristic curves, and safety thresholds. In the risk warning module, the design of the alarm unit and the visualization unit enables the system to give an alarm when an abnormal situation is detected and display the gas path monitoring data, characteristic curves, and safety thresholds through the visualization unit. The instructions for using this design in specific working scenarios can provide an intuitive monitoring interface and real-time alarm information for operators. When abnormal parameters such as gas flow rate, pressure, or temperature are monitored, the alarm will immediately give an alarm to remind the operator to take emergency measures. At the same time, the visualization unit displays real-time data through charts and curves, enabling the operator to quickly judge the system status and make corresponding decisions. The combination of this alarm and visualization improves the response speed of the system and the convenience of operation, ensuring that immediate action can be taken in case of an abnormal situation to ensure safety.

[0043] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A smart laboratory gas path monitoring system, characterized in that: It includes data collection module, feature detection module, data analysis module and risk warning module; The data acquisition module is used to construct a gas path monitoring database; the data acquisition module includes a data processing unit and a database construction unit, wherein the data processing unit is used to obtain gas path monitoring data from multiple data sources, and pre-process and clean the data; the database construction unit constructs a gas path monitoring database based on the gas path monitoring data; The characteristic detection module is used to detect the characteristics of gas path indicators and construct a gas path characteristic curve according to the gas path monitoring database and the gas path indicator characteristics; the characteristic detection module includes a flow measurement unit, a gas path operation status characteristic construction unit and a gas path parameter characteristic construction unit; the flow measurement unit is used to obtain flow data and calculate the real-time flow data entering the equipment and container through a flow meter; the gas path operation status characteristic construction unit is used to obtain real-time gas collection data, equipment and container parameter data; the gas path parameter characteristic construction unit constructs a gas path characteristic curve according to the real-time collection data, equipment and container parameter data and set analysis rules; The data analysis module is used to analyze and process the gas circuit monitoring data, and generate a gas circuit operation risk assessment report based on the analysis results; the data analysis module includes an information extraction unit, a parameter modeling unit and a risk assessment unit; The information extraction unit is used to obtain the gas circuit operation data from the data acquisition module for information extraction, and perform parameter modeling based on the extracted parameters; the parameter modeling unit establishes a gas circuit model based on the parameters, and obtains the gas circuit operation parameters through gas circuit model analysis; the risk assessment unit performs real-time risk assessment based on the gas circuit operation status and gas circuit operation parameters, and imports the assessment parameters into the risk warning module; The risk warning module is used to warn of abnormal data and trend changes.

2. The intelligent laboratory gas path monitoring system according to claim 1, characterized in that: The data processing unit includes a data synchronization unit, a data cleaning unit and a database construction unit, wherein the data synchronization unit obtains gas path monitoring data from multiple data sources and realizes data synchronization; the data cleaning unit is used to detect and process abnormal values, missing values, duplicate values ​​and erroneous data in the data; The database construction unit is used to store the cleaned gas path monitoring data into the gas path monitoring database.

3. The intelligent laboratory gas path monitoring system according to claim 1, characterized in that: The feature detection module also includes a pipeline state analysis unit, which establishes a pipeline state model through the real-time gas collection data and environmental condition data obtained by the pipeline state analysis unit, and analyzes the corrosion, air pressure and temperature status of the pipeline in real time.

4. The intelligent laboratory gas path monitoring system according to claim 3, characterized in that: The pipeline state analysis unit has a built-in model building module, a pipeline processing module and a control module. The model building module establishes a pipeline state model according to the acquired real-time gas collection data and environmental condition data, and analyzes the corrosion degree, air pressure and temperature state of the pipeline in real time; the pipeline processing module processes and analyzes the pipeline state according to the detection data of the corrosion degree, air pressure and temperature state of the pipeline and the environmental condition data; the control module issues a control instruction according to the analysis result, and issues an abnormal warning for abnormal temperature and abnormal flow of the pipeline.

5. The intelligent laboratory gas path monitoring system according to claim 1, characterized in that: The risk warning module has built-in safety thresholds, which include velocity characteristic values, flow characteristic values, pressure characteristic values ​​and humidity characteristic values; according to the historical data and potential risks of the gas path monitoring data, the safety thresholds of the velocity characteristic values, flow characteristic values, pressure characteristic values ​​and humidity characteristic values ​​are set and stored in the gas path safety database; The safety threshold is set based on the gas flow speed and flow volume in the gas path and the air tightness of the gas path system.

6. The intelligent laboratory gas path monitoring system according to claim 5, characterized in that: The risk warning module includes an alarm unit and a visualization unit; the alarm unit is used to alarm when an abnormal situation is detected; the visualization unit is used to display gas path monitoring data, characteristic curves and safety thresholds.

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