Gas leakage monitoring method and system based on gas metering
By installing gas sensors and developing data processing algorithms in the gas leakage monitoring system, establishing a baseline model and designing logic to identify potential leakage situations, the problem of false alarms or missed alarms in the existing technology is solved, and accurate identification and timely notification of gas leakage is achieved, and the reliability and response speed of the system are improved.
Patent Information
- Application Number
- CN202411757005.9
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-03
- Publication Date
- 2025-04-25
AI Technical Summary
The existing gas leak monitoring technology has the problem of false alarms or missed reports, and lacks effective data processing capabilities, making it difficult to accurately identify potential leakage situations, and lacks an intelligent alarm mechanism, which leads to the inability to notify relevant personnel in time during leakage.
The gas leakage monitoring method based on gas metering is adopted, and by installing gas sensors and developing data processing algorithms, establishing a baseline model and designing logic to identify potential leakage conditions, defining alarm conditions and triggering standards, and realizing a multi-channel instant notification mechanism.
Improves the accuracy of gas concentration information, enhances the ability to identify potential leakage situations, reduces the time delay from leak detection to action, and ensures the long-term reliable operation of the system through the system self-test maintenance module.
Smart Images
Figure CN119888971A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of gas leakage monitoring, and in particular to a gas leakage monitoring method and system based on gas metering. Background Art
[0002] As an efficient and clean energy source, gas has been widely used in households, industries and commercial fields. However, gas leakage not only wastes resources, but more seriously may cause fire or explosion accidents, posing a huge threat to people's lives and property safety. Although the existing gas leakage monitoring technology has reduced these risks to a certain extent, it still has many shortcomings.
[0003] Traditional gas leak monitoring methods mainly rely on simple gas sensors and alarm devices. These devices can usually only provide basic concentration detection functions and are sensitive to environmental noise and interference, which can easily cause false alarms or missed alarms. In addition, many existing systems lack effective data processing capabilities and find it difficult to accurately extract useful information from complex data, which makes them inaccurate in identifying potential leaks. In addition, due to the lack of an intelligent alarm mechanism, once a leak occurs, relevant personnel are often not notified in time to take action, thus delaying the best time to respond. Therefore, we propose a gas leak monitoring method and system based on gas metering. Summary of the invention
[0004] The main purpose of the present invention is to provide a gas leakage monitoring method and system based on gas metering and a preparation method, which can effectively solve the problems in the background technology.
[0005] To achieve the above object, the technical solution adopted by the present invention is: A gas leakage monitoring method based on gas metering comprises the following steps: S1: Identify system requirements and determine the best solution through market and technical research; S2: Select appropriate hardware platform and software framework to build the basic architecture of the monitoring system; S3: Install gas sensors and develop data processing algorithms to obtain accurate gas concentration information; S4: Establish a baseline based on normal operating modes and develop algorithms to identify potential leaks; S5: Define alarm conditions and trigger criteria, and implement multi-channel instant notification mechanism; S6: Continuously adjust and improve system performance based on actual application feedback.
[0006] Preferably, in S1, the step of clarifying system requirements is: S101: Determine the technical indicators and user requirements of the monitoring system; S102: Investigate existing gas leak monitoring technologies and products on the market.
[0007] Preferably, in S2, the step of constructing the monitoring system infrastructure is: S201: Select a suitable single-chip microcomputer as the core control unit; S202: Select a suitable gas sensor; S203: Planning the software module structure, including data collection, processing, storage and communication functions.
[0008] Preferably, in S201, the single chip microcomputer is an ATmega328P single chip microcomputer; in 202, the gas sensor is a catalytic combustion sensor and an infrared gas sensor.
[0009] Preferably, in S3, the step of developing a data processing algorithm is: S301: cleaning and correcting the raw data, removing outliers and performing necessary baseline correction; S302: Selecting an appropriate filter type according to noise characteristics and application requirements; S303: Apply filtering algorithm to process data; S304: Adjust filter parameters to optimize filtering effects and meet system requirements.
[0010] Preferably, in S302, the filter types are low-pass, high-pass and band-pass filters; in S303, the filtering algorithms are moving average, exponentially weighted moving average, Kalman filtering and median filtering algorithms; in S304, the filter parameters are window size and smoothing coefficient.
[0011] Preferably, in S4, the step of developing an algorithm to identify potential leakage situations is: S401: Establishing a baseline model of gas usage based on a normal working mode; S402: Designing logic to identify changes exceeding a preset threshold as a potential leak indication; S403: Automated build, test, and deployment processes to accelerate the frequency and reliability of software updates; S404: Using machine learning algorithms to improve prediction accuracy.
[0012] Preferably, in S401, the algorithm for establishing the baseline model of gas usage is a time series analysis algorithm; and in S404, the machine learning algorithm is a long short-term memory network.
[0013] Preferably, in S5, the alarm condition is an alarm condition based on a relative threshold change, and the trigger criterion is a trigger criterion based on multiple detections within a time window. The present invention also discloses a gas leakage monitoring system based on gas metering, which is used to implement the above-mentioned gas leakage monitoring method based on gas metering, including a data acquisition module, a data processing and filtering module, a baseline modeling and anomaly detection module, an alarm mechanism module, a communication transmission module, a security encryption module and a system self-checking and maintenance module; The data acquisition module is responsible for collecting gas concentration data in real time through the gas sensor; The data processing and filtering module preprocesses, filters and reduces noise on the collected data to improve the accuracy and reliability of the data; The baseline modeling and anomaly detection module establishes a baseline model of normal gas usage and uses algorithms to identify changes that exceed preset thresholds to detect potential leaks; The alarm mechanism module immediately issues an alarm notification when an abnormality is detected according to the set alarm conditions and triggering criteria; The communication transmission module transmits data to a central server or mobile device via wired or wireless means; The security encryption module implements data encryption and security measures to protect the security of data transmission and storage and prevent unauthorized access; The system self-check and maintenance module periodically performs self-checks on the system, checks the status of sensors and other components, and provides maintenance suggestions and fault diagnosis.
[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention develops a special data processing algorithm, including steps such as data cleaning, correction and filtering, and uses time series analysis to establish a baseline model for gas use; through the design of logic to identify changes beyond the preset threshold as potential leak indications, and using machine learning algorithms such as long short-term memory networks (LSTM) to improve the accuracy of leak prediction. This comprehensive approach not only improves the accuracy of gas concentration information, but also enhances the ability to identify potential leaks.
[0015] 2. The present invention defines alarm conditions based on relative threshold changes and trigger criteria based on multiple detections within a time window, and implements a multi-channel instant notification mechanism. This enables rapid response when a potential leak is detected and alerts relevant personnel through multiple communication means, effectively reducing the time delay between discovering a leak and taking action.
[0016] 3. The present invention proposes a complete gas leak monitoring system based on gas metering. In addition to the core monitoring function, it also includes a system self-checking and maintenance module: this module regularly checks the status of sensors and other components, provides maintenance suggestions and fault diagnosis. This self-diagnosis and maintenance capability helps ensure the long-term reliable operation of the system, while reducing the risk of false alarms or missed alarms due to equipment failures. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] Figure 1 This is a flow chart of a gas leakage monitoring method based on gas metering of the present invention; Figure 2 The present invention is a structural block diagram of a gas leakage monitoring system based on gas metering. DETAILED DESCRIPTION
[0018] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.
[0019] Example like Figure 1 As shown, a gas leakage monitoring method based on gas metering includes the following steps: S1: Identify system requirements and determine the best solution through market and technical research; The steps to clarify system requirements are: S101: Determine the technical indicators and user requirements of the monitoring system; S102: Investigate existing gas leak monitoring technologies and products on the market.
[0020] S2: Select appropriate hardware platform and software framework to build the basic architecture of the monitoring system; The steps to build the monitoring system infrastructure are: S201: Select a suitable single-chip microcomputer as the core control unit; Furthermore, the single chip microcomputer is an ATmega328P single chip microcomputer; in 202, the gas sensor is a catalytic combustion sensor and an infrared gas sensor.
[0021] S202: Select a suitable gas sensor; S203: Planning the software module structure, including data collection, processing, storage and communication functions.
[0022] S3: Install gas sensors and develop data processing algorithms to obtain accurate gas concentration information; The steps to develop a data processing algorithm are: S301: cleaning and correcting the raw data, removing outliers and performing necessary baseline correction; S302: Selecting an appropriate filter type according to noise characteristics and application requirements; Furthermore, the filter types are low-pass, high-pass and band-pass filters; in S303, the filtering algorithms are moving average, exponentially weighted moving average, Kalman filtering and median filtering algorithms.
[0023] S303: Apply filtering algorithm to process data; S304: Adjust filter parameters to optimize filtering effects and meet system requirements.
[0024] Furthermore, the parameters of the filter are the window size and the smoothing coefficient.
[0025] S4: Establish a baseline based on normal operating modes and develop algorithms to identify potential leaks; The steps to develop an algorithm to identify potential leaks are: S401: Establishing a baseline model of gas usage based on a normal working mode; Furthermore, the algorithm for establishing the baseline model of gas usage is a time series analysis algorithm.
[0026] S402: Designing logic to identify changes exceeding a preset threshold as a potential leak indication; S403: Automated build, test, and deployment processes to accelerate the frequency and reliability of software updates; S404: Using machine learning algorithms to improve prediction accuracy.
[0027] Furthermore, the machine learning algorithm is a long short-term memory network.
[0028] S5: Define alarm conditions and trigger criteria, and implement multi-channel instant notification mechanism; The alarm condition is an alarm condition based on a relative threshold change, and the trigger criterion is a trigger criterion based on multiple detections within a time window.
[0029] S6: Continuously adjust and improve system performance based on actual application feedback.
[0030] like Figure 2 As shown, the present invention also discloses a gas leakage monitoring system based on gas metering, which is used to implement the above-mentioned gas leakage monitoring method based on gas metering, including a data acquisition module, a data processing and filtering module, a baseline modeling and anomaly detection module, an alarm mechanism module, a communication transmission module, a security encryption module and a system self-checking and maintenance module; The data acquisition module is responsible for collecting gas concentration data in real time through gas sensors; The data processing and filtering module preprocesses, filters and reduces noise on the collected data to improve the accuracy and reliability of the data; The baseline modeling and anomaly detection module establishes a baseline model of normal gas usage and uses algorithms to identify changes that exceed preset thresholds to detect potential leaks; The alarm mechanism module will issue an alarm notification immediately when an abnormality is detected based on the set alarm conditions and triggering criteria; The communication transmission module transmits data to a central server or mobile device via wired or wireless means; The security encryption module implements data encryption and security measures to protect the security of data transmission and storage and prevent unauthorized access; The system self-check and maintenance module regularly performs self-checks on the system, checks the status of sensors and other components, and provides maintenance recommendations and fault diagnosis.
[0031] The present invention develops a special data processing algorithm, including steps such as data cleaning, correction and filtering, and uses time series analysis to establish a baseline model for gas use; designs logic to identify changes beyond preset thresholds as potential leak indications, and uses machine learning algorithms such as long short-term memory networks (LSTM) to improve the accuracy of leak prediction. This comprehensive approach not only improves the accuracy of gas concentration information, but also enhances the ability to identify potential leaks; the present invention defines alarm conditions based on relative threshold changes and trigger criteria based on multiple detections within a time window, and implements a multi-channel instant notification mechanism. This enables rapid response when a potential leak is detected, and alerts relevant personnel through multiple communication means, thereby effectively reducing the time delay between leak discovery and action; the present invention proposes a complete gas leak monitoring system based on gas metering, which, in addition to the core monitoring function, also includes a system self-check maintenance module: the module regularly checks the status of sensors and other components, provides maintenance recommendations and fault diagnosis. This self-diagnosis and maintenance capability helps ensure the long-term reliable operation of the system, while reducing the risk of false alarms or missed alarms due to equipment failures.
[0032] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.
Claims
1. A gas leakage monitoring method based on gas metering, characterized in that: The following steps are involved: S1: Identify system requirements and determine the best solution through market and technical research; S2: Select appropriate hardware platform and software framework to build the basic architecture of the monitoring system; S3: Install gas sensors and develop data processing algorithms to obtain accurate gas concentration information; S4: Establish a baseline based on normal operating modes and develop algorithms to identify potential leaks; S5: Define alarm conditions and trigger criteria, and implement multi-channel instant notification mechanism; S6: Continuously adjust and improve system performance based on actual application feedback.
2. A gas leakage monitoring method based on gas metering according to claim 1, characterized in that: In S1, the step of clarifying system requirements is: S101: Determine the technical indicators and user requirements of the monitoring system; S102: Investigate existing gas leak monitoring technologies and products on the market.
3. A gas leakage monitoring method based on gas metering according to claim 1, characterized in that: In S2, the steps of constructing the monitoring system infrastructure are: S201: Select a suitable single-chip microcomputer as the core control unit; S202: Select a suitable gas sensor; S203: Planning the software module structure, including data collection, processing, storage and communication functions.
4. A gas leakage monitoring method based on gas metering according to claim 3, characterized in that: In the S201, the single chip microcomputer is an ATmega328P single chip microcomputer; in the 202, the gas sensor is a catalytic combustion sensor and an infrared gas sensor.
5. A gas leakage monitoring method based on gas metering according to claim 1, characterized in that: In S3, the step of developing a data processing algorithm is: S301: cleaning and correcting the raw data, removing outliers and performing necessary baseline correction; S302: Selecting an appropriate filter type according to noise characteristics and application requirements; S303: Apply filtering algorithm to process data; S304: Adjust filter parameters to optimize filtering effects and meet system requirements.
6. A gas leakage monitoring method based on gas metering according to claim 5, characterized in that: In S302, the filter types are low-pass, high-pass and band-pass filters; in S303, the filtering algorithms are moving average, exponentially weighted moving average, Kalman filtering and median filtering algorithms; in S304, the filter parameters are window size and smoothing coefficient.
7. A gas leakage monitoring method based on gas metering according to claim 1, characterized in that: In said S4, the step of developing an algorithm to identify potential leakage situations is: S401: Establishing a baseline model of gas usage based on a normal working mode; S402: Designing logic to identify changes exceeding a preset threshold as a potential leak indication; S403: Automated build, test, and deployment processes to accelerate the frequency and reliability of software updates; S404: Using machine learning algorithms to improve prediction accuracy.
8. A gas leakage monitoring method based on gas metering according to claim 7, characterized in that: In the S401, the algorithm for establishing the baseline model of gas usage is a time series analysis algorithm; in the S404, the machine learning algorithm is a long short-term memory network.
9. A gas leakage monitoring method based on gas metering according to claim 1, characterized in that: In S5, the alarm condition is an alarm condition based on a relative threshold change, and the trigger criterion is a trigger criterion based on multiple detections within a time window.
10. A gas leakage monitoring system based on gas metering, used to implement a gas leakage monitoring method based on gas metering as claimed in any one of claims 1 to 9, characterized in that: It includes data acquisition module, data processing and filtering module, baseline modeling and anomaly detection module, alarm mechanism module, communication transmission module, security encryption module and system self-check and maintenance module; The data acquisition module is responsible for collecting gas concentration data in real time through the gas sensor; The data processing and filtering module preprocesses, filters and reduces noise on the collected data to improve the accuracy and reliability of the data; The baseline modeling and anomaly detection module establishes a baseline model of normal gas usage and uses algorithms to identify changes that exceed preset thresholds to detect potential leaks; The alarm mechanism module immediately issues an alarm notification when an abnormality is detected according to the set alarm conditions and triggering criteria; The communication transmission module transmits data to a central server or mobile device via wired or wireless means; The security encryption module implements data encryption and security measures to protect the security of data transmission and storage and prevent unauthorized access; The system self-check and maintenance module periodically performs self-checks on the system, checks the status of sensors and other components, and provides maintenance suggestions and fault diagnosis.