A gas micro-leakage detection method, device, equipment and medium

Abstract

This application discloses a method, apparatus, equipment, and medium for detecting micro-leaks in gas pipelines. The method includes: responding to a trigger by sending a pressure detection start command to multiple gas meters in a target area during a preset low gas consumption period, controlling the gas meters to close their built-in electronically controlled valves to form a closed pressure-holding section in the indoor gas pipeline; collecting pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure-holding process, and using the pressure sequence data and micro-flow data together as pipeline sealing state characteristic data; performing micro-leak analysis on the pipeline sealing state characteristic data through a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leak state; if the indoor gas pipeline is determined to be in a micro-leak state, outputting a micro-leak alarm and automatically generating a maintenance work order. This application can achieve non-indoor, fully automatic, high-frequency, batch detection of micro-leaks in indoor gas pipelines, improving detection coverage, identification accuracy, and response efficiency, while reducing operation and maintenance costs and user interference.

Description

Technical Field

[0001] This application relates to the field of CNC machine tool processing monitoring technology, and in particular to a method, device, equipment and medium for detecting micro-leaks in gas. Background Technology

[0002] With the continuous expansion of urban gas users, micro-leakage in indoor gas pipelines, valves, and joints has become a significant hidden danger leading to safety accidents. Currently, the mainstream method for indoor gas safety inspection still relies on the traditional approach of manual entry, on-site valve closure, pressure gauge maintenance, and manual reading for judgment. This method has several inherent drawbacks: low inspection frequency, typically only 1-2 times per year, making it difficult to detect slow micro-leakage in a timely manner; poor real-time detection, with potential hazards delayed by several months; large human error, making it difficult to identify minute leaks and resulting in a high rate of missed detections; high costs in terms of manpower, transportation, and time; and the need for appointments for in-home visits, disrupting users' normal lives, and making it difficult to effectively cover older communities, high-rise buildings, and long-term unoccupied households, resulting in low inspection coverage.

[0003] Although existing smart gas meters have remote data transmission and valve control functions, they can only report the status of a single meter. They have not formed an automated detection mechanism that includes valve closure and pressure maintenance, synchronous acquisition of pressure and micro-flow, cloud-based batch scheduling, and multi-parameter fusion judgment. Therefore, they cannot meet the needs of non-indoor, silent, high-frequency, and high-precision indoor gas safety monitoring.

[0004] Therefore, how to achieve indoor gas micro-leakage monitoring that is non-invasive, automated, batch-detected, and accurately identified is a key technical issue for improving gas safety operation and maintenance and reducing accident risks. Summary of the Invention

[0005] The purpose of this application is to provide a method, device, equipment and medium for detecting micro-leaks in gas pipelines, which can realize non-indoor, fully automatic, high-frequency and batch pressure detection and micro-leak identification of indoor gas pipelines, improve detection coverage, identification accuracy and response efficiency, and reduce operation and maintenance costs and user interference.

[0006] To achieve the above objectives: In a first aspect, embodiments of this application provide a method for detecting micro-leaks in gas, including: In response to triggering, a pressure detection start command is sent in batches to multiple gas meters in the target area during a preset low gas consumption period, and the gas meters are controlled to close their built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline; During the pressure holding process, pressure sequence data and microflow data of the indoor gas pipeline are collected, and the pressure sequence data and microflow data are used together as pipeline sealing status characteristic data. By using a preset fusion judgment model to perform micro-leakage analysis on the pipeline sealing status characteristic data, it can be determined whether the indoor gas pipeline is in a micro-leakage state. If the indoor gas pipeline is determined to be in a state of minor leakage, a minor leakage alarm will be output and a maintenance work order will be automatically generated.

[0007] In one embodiment, the step of responding to triggering a batch issuance of pressure detection start commands to multiple gas meters in a target area during a preset low gas consumption period includes: Based on the pre-configured area detection tasks and timing strategies of the IoT cloud platform, determine the preset low gas consumption period, target area, and the time for issuing pressure detection start commands in batches; The IoT cloud platform issues pressure detection start commands to multiple gas meters in the target area in a segmented, time-based, and batch-based manner according to the preset area division rules.

[0008] In one embodiment, the acquisition of pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure holding process includes: Pressure sequence data is obtained by continuously collecting pressure change samples during the pressure holding process using a pressure sensor, resulting in multiple sets of time-series data. By continuously collecting minute flow velocities in a pipeline under static conditions using an ultrasonic metering module, micro-flow data composed of multiple sets of time-series data is obtained.

[0009] In one embodiment, using the pressure sequence data and microflow data together as pipeline sealing status characteristic data includes: Extract the pressure decay rate and pressure stability characteristics from the pressure sequence data, as well as the duration and flow amplitude characteristics from the microflow data; The pressure decay rate feature, the pressure stability feature, the duration feature, and the flow amplitude feature are fused to construct pipeline sealing state feature data.

[0010] In one embodiment, the step of performing micro-leakage analysis on the pipeline sealing state characteristic data using a preset fusion judgment model includes: Based on a preset fusion judgment model, the pipeline sealing status feature data are subjected to multi-dimensional cross-validation and feature mapping to generate a safety score that characterizes the sealing integrity of the indoor gas pipeline.

[0011] In one embodiment, determining whether the indoor gas pipeline is in a state of minor leakage includes: When the safety score does not meet the preset safety score threshold, the indoor gas pipeline is determined to be in a state of minor leakage.

[0012] In one embodiment, after outputting a leakage alarm and automatically generating a maintenance work order, the method further includes: Obtain feedback from maintenance personnel regarding the actual leakage status of pipelines on site; Based on the actual leakage state and the micro-leakage state obtained from the analysis of the fusion judgment model, at least one of the pressure attenuation threshold and the micro-flow determination threshold in the fusion judgment model is adjusted to optimize the fusion judgment model.

[0013] Secondly, embodiments of this application provide a gas micro-leakage detection device, comprising: The valve control module is used to respond to triggering a batch of pressure detection start commands to multiple gas meters in a target area during a preset low gas consumption period, and to control the gas meters to close their built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline; The data acquisition module is used to collect pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure holding process, and to use the pressure sequence data and micro-flow data together as pipeline sealing status characteristic data. The micro-leakage analysis module is used to perform micro-leakage analysis on the pipeline sealing status characteristic data through a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leakage state. The alarm work order module is used to output a leak alarm and automatically generate a maintenance work order when it is determined that the indoor gas pipeline is in a state of minor leakage.

[0014] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor, wherein the memory stores executable program code, and when the executable program code is executed by the processor, it implements the steps of the gas micro-leakage detection method as described in the first aspect.

[0015] Fourthly, embodiments of this application provide a readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the gas micro-leakage detection method as described in the first aspect.

[0016] The gas micro-leakage detection method, apparatus, equipment, and medium provided in this application include: responding to a trigger by sending a pressure detection start command to multiple gas meters in a target area during a preset low gas consumption period, controlling the gas meters to close their built-in electronically controlled valves to form a closed pressure-holding section in the indoor gas pipeline; collecting pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure-holding process, and using the pressure sequence data and micro-flow data together as pipeline sealing state characteristic data; performing micro-leakage analysis on the pipeline sealing state characteristic data through a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leakage state; if the indoor gas pipeline is determined to be in a micro-leakage state, outputting a micro-leakage alarm and automatically generating a maintenance work order. This application can achieve non-indoor, fully automatic, high-frequency, batch indoor gas pipeline micro-leakage detection, improving detection coverage, identification accuracy, and response efficiency, while reducing operation and maintenance costs and user interference. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic flowchart of the gas micro-leakage detection method provided in an embodiment of the present invention.

[0019] Figure 2 This is a schematic diagram of the structure of the gas micro-leakage detection device provided in an embodiment of the present invention.

[0020] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0021] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0022] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, components, features, and elements with the same names in different embodiments of this application may have the same meaning or different meanings, the specific meaning of which must be determined by its interpretation in that specific embodiment or further in conjunction with the context of that specific embodiment.

[0023] It should be understood that although the terms first, second, third, etc., may be used herein to describe various information, such information should not be limited to these terms. These terms are used only to distinguish information of the same type from one another. For example, without departing from the scope of this document, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if," as used herein, can be interpreted as "when," "when," or "in response to determination." Furthermore, as used herein, the singular forms "a," "an," and "the" are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms "comprising," "including," indicate the presence of the stated feature, step, operation, element, component, item, kind, and / or group, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups. The terms "or" and "and / or" as used herein are to be interpreted as inclusive, or mean any one or any combination thereof. Therefore, "A, B, or C" or "A, B, and / or C" means "any one of the following: A; B; C; A and B; A and C; B and C; A, B, and C". Exceptions to this definition will only occur if the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0024] It should be understood that although the steps in the flowcharts of this application's embodiments are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0025] It should be noted that step designations such as S101 and S102 are used in this document for the purpose of more clearly and concisely describing the corresponding content, and do not constitute a substantial limitation on the order. In specific implementation, those skilled in the art may execute S102 first and then S101, etc., but these should all be within the protection scope of this application.

[0026] It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0027] In the following description, the use of suffixes such as "module," "part," or "unit" to denote elements is solely for the purpose of illustrative purposes and has no specific meaning in itself. Therefore, "module," "part," or "unit" may be used interchangeably.

[0028] First Embodiment See Figure 1 This application provides a method for detecting micro-leaks in gas. This method can be executed by a gas micro-leak detection device provided in this application. The system can be implemented using software and / or hardware. In this embodiment, the gas micro-leak detection device is taken as the executing entity of the method. The gas micro-leak detection method provided in this embodiment includes the following steps: Step S101: In response to the trigger, a pressure detection start command is sent in batches to multiple gas meters in the target area during a preset low gas consumption period, and the gas meters are controlled to close their built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline.

[0029] Understandably, preset low gas consumption periods are typically times when users consume very little gas (e.g., from 00:00 to 05:00 at night), when pipeline pressure is stable (e.g., user gas consumption rate <3%) and there are no gas consumption fluctuations. This ensures the accuracy of pressure monitoring without affecting normal gas usage. Target areas can be divided by community, building, administrative district, or user ID range, supporting large-scale batch processing.

[0030] In one embodiment, in response to triggering a batch issuance of pressure detection start commands to multiple gas meters in a target area during a preset low gas consumption period, the method includes: Based on the pre-configured area detection tasks and timing strategies of the IoT cloud platform, the preset low gas consumption period, target area, and time for batch issuance of pressure detection start commands are determined; the IoT cloud platform issues pressure detection start commands to multiple gas meters in the target area in sections, times, and batches according to the preset area division rules.

[0031] It is understandable that by using the IoT cloud platform to distribute commands to multiple gas meters in a target area in a segmented, time-segmented, and batch-segmented manner (e.g., 50 to 200 meters per batch) according to the preset area division rules, network congestion, communication failures, or excessive platform load caused by a large number of concurrent commands can be avoided, thereby improving command delivery rate and system stability.

[0032] Furthermore, after the IoT cloud platform issues instructions according to the preset strategy, the gas meter receives the instructions and completes the legality verification, and automatically closes the electrical control valve after the meter, so that the indoor gas pipeline forms a closed and independent pressure-holding cavity, providing the necessary environment for subsequent pressure decay and micro-flow detection.

[0033] Step S102: Collect pressure sequence data and micro-flow data of indoor gas pipeline during the pressure holding process, and use both as pipeline sealing status characteristic data.

[0034] It is understandable that during the closed pressure holding period (e.g., set to 120 seconds), the meter simultaneously starts two acquisition channels: one channel continuously samples from the pressure sensor at fixed time intervals to obtain the pressure sequence that changes over time, reflecting the pipeline sealing performance; the other channel uses the ultrasonic metering module in a high-sensitivity mode to collect the micro-flow rate in the static pipeline, capturing extremely small media flows (e.g., media on the order of 0.04 to 0.3 L / h).

[0035] In one embodiment, pressure sequence data and micro-flow data of the indoor gas pipeline are collected during the pressure holding process, including: Pressure sequence data composed of multiple sets of time-series data is obtained by continuously collecting pressure change samples during the pressure holding process using a pressure sensor; micro-flow rate data composed of multiple sets of time-series data is obtained by continuously collecting micro-flow rate samples under static conditions in the pipeline using an ultrasonic metering module.

[0036] In one embodiment, pressure sequence data and microflow data are used together as pipeline sealing status characteristic data, including: The pressure decay rate and pressure stability features of the pressure sequence data, as well as the duration and flow amplitude features of the micro-flow data, are extracted. The pressure decay rate, pressure stability, duration, and flow amplitude features are then fused to construct pipeline sealing state feature data.

[0037] It is understandable that the pressure decay rate reflects the speed of leakage, the pressure stability reflects the tightness of the pipeline, the flow amplitude reflects the size of the leakage, and the duration eliminates the interference of instantaneous fluctuations. These four characteristics together provide a highly reliable basis for judgment.

[0038] Step S103: Perform micro-leakage analysis on the pipeline sealing status characteristic data using a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leakage state.

[0039] It is understandable that the fusion judgment model adopts cross-validation of pressure and flow rate. Only when the pressure decay and micro flow rate simultaneously meet the threshold conditions is it judged as a micro-leakage. This overcomes the shortcomings of single pressure detection being susceptible to temperature drift and insufficient sensitivity in long pipelines, as well as the shortcomings of single flow rate detection being susceptible to disturbance interference.

[0040] Furthermore, by continuously collecting pressure and flow curves, it can be seen that when there is no leakage in the pipeline, the pressure curve remains horizontal and stable without significant decline, and the flow curve remains at 0 with no flow signal; when there is a slight leakage in the pipeline, the pressure curve shows a slow, stable, and continuous downward trend, and the flow curve simultaneously shows a continuous slight flow signal.

[0041] In one embodiment, a micro-leakage analysis is performed on the pipeline sealing state characteristic data using a preset fusion judgment model, including: Based on a pre-defined fusion judgment model, multi-dimensional cross-validation and feature mapping are performed on the pipeline sealing status feature data to generate a safety score that characterizes the sealing integrity of indoor pipelines.

[0042] Understandably, a higher score indicates better sealing, while a lower score indicates a higher risk of leakage.

[0043] In one embodiment, determining whether an indoor gas pipeline is in a state of minor leakage includes: When the safety score does not meet the preset safety score threshold, the indoor gas pipeline is determined to be in a state of minor leakage.

[0044] Understandably, the threshold can be configured in the cloud based on pipeline length, service life, and user type to adapt to different scenarios.

[0045] Step S104: If it is determined that the indoor gas pipeline is in a state of minor leakage, output a minor leakage alarm and automatically generate a maintenance work order.

[0046] Understandably, once the cloud platform detects a leak, it immediately reports an alarm and automatically generates a maintenance work order, which includes the user's address, meter number, detection time, anomaly type, and risk level, and pushes it to the maintenance terminal for rapid handling.

[0047] In one implementation, after outputting a leak alarm and automatically generating a maintenance work order, the method further includes: Obtain the actual leakage status reported by maintenance personnel during on-site verification; based on the actual leakage status and the micro-leakage status obtained from the fusion judgment model analysis, adjust at least one of the pressure attenuation threshold and micro-flow determination threshold in the fusion judgment model to optimize the fusion judgment model.

[0048] In summary, the implementation method of this application sends batch detection commands to gas meters in the area during low gas consumption periods through an IoT cloud platform, automatically closes the valve to form a closed pressure-maintaining section, and simultaneously collects pressure sequence and ultrasonic micro-flow data. After judgment by a dual-dimensional fusion model, it automatically identifies micro-leakage and dispatches work orders, realizing full-process non-indoor, unmanned, automated, and high-frequency safety detection. This significantly improves the accuracy and coverage of micro-leakage identification, greatly reduces operation and maintenance costs, does not interfere with users, and effectively improves the safety of gas use.

[0049] Second Embodiment Based on the first embodiment of this application, a gas micro-leakage detection device is provided in this embodiment, see reference. Figure 2 The device includes: The valve control module 21 is used to respond to triggering a batch of pressure detection start commands to multiple gas meters in the target area during a preset low gas consumption period, and to control the gas meters to close the built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline.

[0050] Data acquisition module 22 is used to acquire pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure holding process, and use the pressure sequence data and micro-flow data together as pipeline sealing status characteristic data.

[0051] The micro-leakage analysis module 23 is used to perform micro-leakage analysis on the pipeline sealing status characteristic data through a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leakage state.

[0052] The alarm work order module 24 is used to output a leak alarm and automatically generate a maintenance work order when it is determined that the indoor gas pipeline is in a state of minor leakage.

[0053] In one embodiment, the valve control module 21 is further configured to: Based on the pre-configured area detection tasks and timing strategies of the IoT cloud platform, the preset low gas consumption period, target area, and time for batch issuance of pressure detection start commands are determined; the IoT cloud platform issues pressure detection start commands to multiple gas meters in the target area in sections, times, and batches according to the preset area division rules.

[0054] In one embodiment, the data acquisition module 22 is further configured to: Pressure sequence data composed of multiple sets of time-series data is obtained by continuously collecting pressure change samples during the pressure holding process using a pressure sensor; micro-flow rate data composed of multiple sets of time-series data is obtained by continuously collecting micro-flow rate samples under static conditions in the pipeline using an ultrasonic metering module.

[0055] In one embodiment, the data acquisition module 22 is further configured to: The pressure decay rate and pressure stability features of the pressure sequence data, as well as the duration and flow amplitude features of the micro-flow data, are extracted. The pressure decay rate, pressure stability, duration, and flow amplitude features are then fused to construct pipeline sealing state feature data.

[0056] In one embodiment, the micro-leakage analysis module 23 is further configured to: Based on a pre-defined fusion judgment model, multi-dimensional cross-validation and feature mapping are performed on the pipeline sealing status feature data to generate a safety score that characterizes the sealing integrity of indoor pipelines.

[0057] In one embodiment, the micro-leakage analysis module 23 is further configured to: When the safety score does not meet the preset safety score threshold, the indoor gas pipeline is determined to be in a state of minor leakage.

[0058] It should be noted that the description of the gas micro-leakage detection device above is similar to the description of the gas micro-leakage detection method above, and the beneficial effects of the same method will not be repeated. For technical details not disclosed in the embodiments of the gas micro-leakage detection device of the present invention, please refer to the description of the embodiments of the gas micro-leakage detection method of the present invention.

[0059] Third Embodiment Based on the same inventive concept as the foregoing embodiments, this application provides an electronic device, such as... Figure 3 As shown, the device includes: a processor 301 and a memory 302 storing a computer program; wherein, Figure 3 The processor 301 shown in the diagram does not indicate that there is only one processor 301, but only indicates the positional relationship of processor 301 relative to other devices. In practical applications, there can be one or more processors 301; similarly, Figure 3 The memory 302 shown in the diagram has the same meaning, that is, it is only used to indicate the positional relationship of the memory 302 relative to other devices. In practical applications, there can be one or more memories 302. When the processor 301 runs the computer program, it implements the above-mentioned gas micro-leakage detection method.

[0060] The device may also include at least one network interface 303. The various components of the device are coupled together via a bus system 304. It is understood that the bus system 304 is used to implement communication between these components. In addition to a data bus, the bus system 304 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 3 The general designated all buses as Bus System 304.

[0061] The memory 302 can be volatile memory or non-volatile memory, or both. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), ferromagnetic random access memory (FRAM), flash memory, magnetic surface memory, optical disc, or compact disc read-only memory (CD-ROM); magnetic surface memory can be disk storage or magnetic tape storage. Volatile memory can be random access memory (RAM), used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), SyncLink Dynamic Random Access Memory (SLDRAM), and Direct Rambus Random Access Memory (DRRAM).The memory 302 described in the embodiments of this application is intended to include, but is not limited to, these and any other suitable types of memory.

[0062] Fourth embodiment Based on the same inventive concept as the foregoing embodiments, this embodiment also provides a computer-readable storage medium storing a computer program. The computer-readable storage medium can be a magnetic random access memory (FRAM), a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a flash memory, a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM), etc.; it can also be various devices including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc. When the computer program stored in the computer-readable storage medium is executed by a processor, it implements the above-described charging current adjustment method. For the specific steps implemented when the computer program is executed by the processor, please refer to [link to relevant documentation]. Figure 2 The description of the illustrated embodiments will not be repeated here.

[0063] In this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions are generally described in detail only when they appear for the first time. When they appear again, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of this application, the same or similar terms, concepts, technical solutions and / or application scenario descriptions that are not described in detail later can be referred to their previous relevant detailed descriptions.

[0064] In this application, the descriptions of the various embodiments have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0065] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0066] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method of detecting a gas micro-leakage, characterized by, The method includes: In response to triggering, a pressure detection start command is sent in batches to multiple gas meters in the target area during a preset low gas consumption period, and the gas meters are controlled to close their built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline; During the pressure holding process, pressure sequence data and microflow data of the indoor gas pipeline are collected, and the pressure sequence data and microflow data are used together as pipeline sealing status characteristic data. By using a preset fusion judgment model to perform micro-leakage analysis on the pipeline sealing status characteristic data, it can be determined whether the indoor gas pipeline is in a micro-leakage state. If the indoor gas pipeline is determined to be in a state of minor leakage, a minor leakage alarm will be output and a maintenance work order will be automatically generated.

2. The method of claim 1, wherein, The response to triggering the batch issuance of pressure detection start commands to multiple gas meters in the target area during a preset low gas consumption period includes: Based on the pre-configured area detection tasks and timing strategies of the IoT cloud platform, determine the preset low gas consumption period, target area, and the time for issuing pressure detection start commands in batches; The IoT cloud platform issues pressure detection start commands to multiple gas meters in the target area in a segmented, time-based, and batch-based manner according to the preset area division rules.

3. The method of claim 1, wherein, The pressure sequence data and micro-flow data of the indoor gas pipeline collected during the pressure holding process include: Pressure sequence data is obtained by continuously collecting pressure change samples during the pressure holding process using pressure sensors, resulting in multiple sets of time-series data. By continuously collecting minute flow velocities in a pipeline under static conditions using an ultrasonic metering module, micro-flow data composed of multiple sets of time-series data is obtained.

4. The method of claim 3, wherein, The step of using the pressure sequence data and microflow data together as pipeline sealing status characteristic data includes: Extract the pressure decay rate and pressure stability characteristics from the pressure sequence data, as well as the duration and flow amplitude characteristics from the microflow data; The pressure decay rate feature, the pressure stability feature, the duration feature, and the flow amplitude feature are fused to construct pipeline sealing state feature data.

5. The method of claim 1, wherein, The step of performing micro-leakage analysis on the pipeline sealing state characteristic data using a preset fusion judgment model includes: Based on a preset fusion judgment model, the pipeline sealing status feature data are subjected to multi-dimensional cross-validation and feature mapping to generate a safety score that characterizes the sealing integrity of the indoor gas pipeline.

6. The method of claim 5, wherein, Determining whether the indoor gas pipeline is in a state of minor leakage includes: When the safety score does not meet the preset safety score threshold, the indoor gas pipeline is determined to be in a state of minor leakage.

7. The method of claim 1, wherein, After outputting a leakage alarm and automatically generating a maintenance work order, the method further includes: Obtain feedback from maintenance personnel regarding the actual leakage status of pipelines on site; Based on the actual leakage state and the micro-leakage state obtained from the analysis of the fusion judgment model, at least one of the pressure attenuation threshold and the micro-flow determination threshold in the fusion judgment model is adjusted to optimize the fusion judgment model.

8. A gas micro-leakage detection apparatus, characterized by, include: The valve control module is used to respond to triggering a batch of pressure detection start commands to multiple gas meters in a target area during a preset low gas consumption period, and to control the gas meters to close their built-in electronically controlled valves to form a closed pressure-maintaining section in the indoor gas pipeline; The data acquisition module is used to collect pressure sequence data and micro-flow data of the indoor gas pipeline during the pressure holding process, and to use the pressure sequence data and micro-flow data together as pipeline sealing status characteristic data. The micro-leakage analysis module is used to perform micro-leakage analysis on the pipeline sealing status characteristic data through a preset fusion judgment model to determine whether the indoor gas pipeline is in a micro-leakage state. The alarm work order module is used to output a leak alarm and automatically generate a maintenance work order when it is determined that the indoor gas pipeline is in a state of minor leakage.

9. An electronic device, comprising: The electronic device includes a memory and a processor, wherein the memory stores executable program code, and when the executable program code is executed by the processor, it implements the steps of the gas micro-leakage detection method as described in any one of claims 1 to 7.

10. A readable storage medium, characterized by, The readable storage medium stores a computer program that, when executed by a processor, implements the steps of the gas micro-leakage detection method as described in any one of claims 1 to 7.

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