Gas leakage detection device and method, terminal and medium

Abstract

The invention belongs to the technical field of gas leakage detection, and particularly discloses and provides a gas leakage detection device and method, a terminal and a medium, the detection device comprises a three-axis moving structure and a sensor array plate, and a plurality of gas sensors are distributed on the sensor array plate; the device further comprises a data acquisition module, a control module, a data processing module and an alarm feedback module. The three-axis moving structure is used for realizing coverage detection of a target area; when any sensor detects abnormal concentration data, the control module controls the three-axis structure to carry out local scanning, so that repeated cross validation of multiple sensors is realized; and constructing a multi-dimensional feature vector based on the concentration peak value, the change rate, the space gradient, the response time difference and the synchronization degree, wherein the multi-dimensional feature vector is used for judging the leakage position, direction, rate and danger level. The scheme has active analysis and adaptive response capabilities, and the intelligent judgment and on-site response capabilities of the device to the complex leakage situation are improved.

Description

Technical Field

[0001] This invention belongs to the field of gas leak detection technology, specifically relating to a gas leak detection device, method, terminal, and medium. Background Technology

[0002] With the widespread use of high-risk media (such as flammable, highly toxic, and corrosive gases) in large-scale plants in industries such as petrochemicals, power, and metallurgy, gas leaks have become a significant threat to operational safety and environmental protection. To promptly detect and address gas leaks, there is an urgent need to deploy gas monitoring systems with high reliability, high accuracy, and low false alarm rates to achieve rapid detection and effective early warning of leaks.

[0003] Existing gas leak monitoring methods typically involve deploying 2-3 fixed gas sensors at potential leak points within the plant area. Leakage is confirmed through cross-verification of simultaneous anomalies from multiple sensors. This approach is simple in structure and easy to implement, and can improve the robustness of localized detection to some extent. However, the number of sensors is limited, their installation locations are fixed, and their detection capability is highly dependent on deployment accuracy and initial configuration strategy.

[0004] However, existing fixed-deployment sensing methods have significant limitations: First, these methods typically only collect discrete point data on a two-dimensional plane, failing to dynamically construct a three-dimensional distribution model of the leaking gas in space, resulting in an inability to accurately determine key information such as the direction of leakage and diffusion rate; second, the data processing methods between sensors are relatively primitive, lacking mechanisms for fusing multi-point data and intelligently judging trend changes, often relying solely on preset thresholds for simple judgments, making it difficult to effectively distinguish between false alarms and actual leaks, thus limiting the adaptability and intelligence level of the monitoring system under complex operating conditions. Summary of the Invention

[0005] This invention addresses the problems in the prior art by providing a gas leak detection device, method, terminal, and medium, which solves the problem that the prior art cannot accurately determine key information such as the leak direction and diffusion rate.

[0006] The technical solution adopted in this invention is as follows: In a first aspect, this application provides a gas leak detection device, which includes a three-axis moving structure and a sensor array plate. The sensor array plate is disposed on the end moving platform of the three-axis moving structure. Multiple gas sensors are arranged on the sensor array plate to acquire gas concentration data at different locations. The three-axis moving structure is used to drive the sensor array to move in three-dimensional space to cover the area to be tested. The detection device also includes a data acquisition module, a control module, a data processing module, and an alarm feedback module; The data acquisition module is used to acquire real-time concentration data output from multiple gas sensors; The control module is used to control the three-axis moving structure to move the sensor array plate according to a preset path or dynamic feedback information, and to trigger a local scan when abnormal concentration data is detected; The data processing module is used to perform consistency analysis and fusion processing on data collected by multiple gas sensors in order to determine whether a leak event exists. The alarm feedback module is used to output an alarm signal and send the analysis results to the remote monitoring platform when a leakage event is determined to be true.

[0007] Furthermore, the three-axis motion mechanism includes a Z-axis lifting assembly and an XY slide assembly; The Z-axis lifting assembly includes a vertical guide rail and a platform drive unit for driving the lifting. The platform drive unit includes a lifting motor, a lifting screw, and a lifting platform. The Z-axis lifting assembly is used to adjust the height position of the sensor array plate in the vertical direction. The XY slide assembly is mounted on the lifting platform of the Z-axis lifting assembly. The XY slide assembly includes a first drive unit and a second drive unit respectively arranged along the X-axis and Y-axis. The first drive unit includes a first drive motor and a first lead screw for driving movement along the X-axis. The second drive unit includes a second drive motor and a second lead screw for driving movement along the Y-axis. The XY slide assembly is used to drive the sensor array plate to move in the horizontal plane.

[0008] Furthermore, the sensor array board has a matrix arrangement structure, with multiple gas sensors evenly arranged on the surface of the array board in an M×N matrix manner; Multiple gas sensors are connected via a bus, which includes power lines and signal lines, used to transmit the detection signals from the multiple sensors to the data acquisition module.

[0009] Secondly, this application provides a gas leak detection method based on the gas leak detection device described in the first aspect, comprising the following steps: Step S1: Deploy detection devices at each leakage risk point and establish a three-dimensional environmental spatial model; Step S2: Control the three-axis moving structure in the detection device to move the sensor array plate to the preset detection height and detection area; Step S3: Collect gas concentration data at multiple locations using the sensor array board. The data is then transmitted in real time from the data acquisition module to the data processing module. Step S4: The control module preprocesses the collected concentration data. When the concentration value output by a certain sensor exceeds the set threshold, a local scan is performed, and the three-axis moving structure is controlled to drive the sensor array board to further detect in the abnormal area. Step S5: The data processing module performs consistency analysis and fusion processing on the multi-sensor data obtained from the local scan to determine whether it is a real leakage event. Step S6: If a leakage event is determined, the alarm feedback module outputs an alarm signal, synchronously updates the leakage event information in the three-dimensional spatial model, and uploads it to the remote monitoring platform.

[0010] Furthermore, in step S4, when the concentration data of a certain sensor exceeds the set threshold, the control module controls the three-axis moving structure to make local fine adjustments with the location of the sensor as the center. During the local scanning process, the three-axis moving structure uses the XYZ three-axis linkage to control the sensor array board to make joint adjustments to the vertical height and planar position in this area, driving the sensor array board to generate multiple detection points around this position, so that multiple different sensors can repeatedly detect the same leakage area.

[0011] Furthermore, in step S5, when multiple gas sensors on the sensor array board detect abnormal concentration data, the data processing module uses a combination of fitting analysis and reverse derivation based on the concentration time-series changes, response time differences, and concentration spatial gradients of multiple sensors at different locations in three-dimensional space. The sensor region that responds earliest is identified, and the initial spatial location of the leak point is deduced by using the response time difference between it and the surrounding points. By combining the concentration growth rate and the spatial gradient direction, the diffusion direction and diffusion rate of the leaked gas are calculated. A leakage hazard level scoring model was constructed by using peak concentration, concentration change rate, gradient intensity, and response synchronization as multiple input factors. The hazard level is determined by a leakage hazard level scoring model, and the prediction results are updated synchronously with the hazard level in the three-dimensional spatial model.

[0012] Furthermore, after the leak direction is simultaneously marked on the three-dimensional spatial model, the control module adjusts the alarm threshold of the sensors on the platform corresponding to the adjacent detection devices along the path pointed to by the leak direction vector, based on the position distance weighting function and the risk reduction model. The alarm threshold adjustment includes a preset maximum reduction range, and the target threshold for each sensor in each adjacent detection platform is calculated based on a spatial weighting function.

[0013] Furthermore, when the real-time concentration value of any sensor in an adjacent platform reaches the dynamically adjusted alarm threshold, the control module triggers the detection device of that platform to perform a local scanning process, record the sensor data, and match and compare it with the leakage diffusion direction recorded in the three-dimensional model. The comparison process uses a concentration response consistency calculation model, and based on the spatial direction error threshold and response time window, confirms that the direction is the actual diffusion direction of the current leak, and updates the state of the three-dimensional spatial model.

[0014] Thirdly, this application provides a terminal, including: Memory, used to store gas leak detection simulation programs; A processor is used to implement the steps of the gas leak detection method as described in the second aspect when executing the gas leak detection device.

[0015] Fourthly, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the gas leak detection method as described in the second aspect.

[0016] As can be seen from the above technical solutions, the advantages of the present invention are: (1) By deploying a detection device with three-axis linkage capability at each leakage risk point, and setting up a sensor array plate arranged in an M×N matrix at its end, combined with high-density coverage in the XY horizontal plane and vertical height adjustment capability in the Z axis, a spatial full-coverage scan of the target detection area can be achieved. When a single gas sensor detects an abnormal concentration change, the device controls the sensor array plate to perform XYZ three-axis joint fine adjustment around the abnormal point through a local scanning strategy to achieve multi-sensor cross-verification. Compared with the existing technology that directly determines whether there is a leak by using only two or three fixed sensors, this solution significantly improves the detection accuracy and false alarm filtering capability, effectively solves the technical problems of low single-point detection fault tolerance and large influence of sensor drift, and ensures the robustness and practicality of the detection device in actual industrial environments.

[0017] (2) By introducing multiple parameters such as concentration time-series changes, spatial distribution gradients, and response time differences into the data processing module, a spatiotemporal fusion analysis model for spatial location of leak sources, determination of diffusion direction, and estimation of leakage rate is constructed, thereby forming a leakage hazard level scoring mechanism. By performing trend fitting and reverse derivation on the abnormal response patterns of multiple sensors at different locations, the spatial location of the leak point and the gas diffusion direction can be dynamically predicted, and the leakage level can be quantified based on the concentration peak and gradient amplitude. The prediction results are further updated synchronously to the three-dimensional spatial model and drive the adjacent areas to dynamically adjust the detection threshold, achieving secondary confirmation and rapid response. Compared with existing passive detection methods, this solution has active analysis and adaptive response capabilities, improving the device's intelligent judgment and on-site response capabilities to complex leakage situations, and is suitable for the deployment of leakage early warning systems in highly safety-sensitive industries such as petrochemical, power, and semiconductor plants. Attached Figure Description

[0018] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the description will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the device structure in a specific embodiment of the present invention; Figure 2 This is a flowchart illustrating a specific embodiment of the method of the present invention.

[0020] In the diagram: 1. Vertical guide rail; 2. Lifting motor; 3. Lifting lead screw; 4. Lifting platform; 5. First drive motor; 6. First lead screw; 7. Second drive motor; 8. Second lead screw; 9. Sensor array board. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Please see Figure 1 As shown, this application provides a gas leak detection device. The detection device includes a three-axis moving structure and a sensor array plate 9. The sensor array plate 9 is disposed on the end moving platform of the three-axis moving structure. Multiple gas sensors are arranged on the sensor array plate 9 to acquire gas concentration data at different locations. The three-axis moving structure is used to drive the sensor array to move in three-dimensional space to cover the area to be tested. By employing a three-axis moving structure, the detection device can flexibly cover multiple spatial points within the detection area, thus achieving multi-point inspection without increasing the number of sensors. Compared to traditional fixed-point deployment, this solution enables "multi-point reuse" through spatial movement, effectively reducing device costs.

[0023] The detection device also includes a data acquisition module, a control module, a data processing module, and an alarm feedback module; The data acquisition module is used to acquire real-time concentration data output from multiple gas sensors; The control module is used to control the three-axis moving structure to move the sensor array board 9 according to a preset path or dynamic feedback information, and to trigger a local scan when abnormal concentration data is detected; The data processing module is used to perform consistency analysis and fusion processing on data collected by multiple gas sensors in order to determine whether a leak event exists. Employing fusion algorithms (such as weighted time difference analysis and multi-point response mean judgment) can improve the device's ability to distinguish between real leaks and occasional noise, effectively avoiding single-point false alarms.

[0024] When the concentrations of multiple adjacent sensors rise synchronously and exceed the threshold, the device determines it to be a valid leak; if a single point experiences a short-term spike without a response from neighboring sensors, it is recorded as temporary fluctuation data. The fusion algorithm introduces a response synchronicity scoring index R_sync, with a threshold of 0.7 set as the benchmark for leak event determination.

[0025] The alarm feedback module is used to output an alarm signal and send the analysis results to the remote monitoring platform when a leakage event is determined to be established. Alarm signals can be used not only for on-site audible and visual warnings, but also linked with the plant's central control system via a communication module to achieve automated coordinated responses (such as closing valves or starting ventilation). The remote upload function allows the operations and maintenance center to have a comprehensive view of the situation.

[0026] When the device detects a leak in a certain area, it immediately triggers a flashing red warning light and simultaneously uploads information such as the leak time, concentration, and location coordinates to the remote monitoring system interface via the communication module.

[0027] In some embodiments, the three-axis moving mechanism includes a Z-axis lifting assembly and an XY slide assembly; The Z-axis lifting assembly includes a vertical guide rail 1 and a platform drive unit for driving the lifting. The platform drive unit includes a lifting motor 2, a lifting screw 3, and a lifting platform 4. The Z-axis lifting assembly is used to adjust the height position of the sensor array plate 9 in the vertical direction. The XY slide assembly is mounted on the lifting platform 4 of the Z-axis lifting assembly. The XY slide assembly includes a first drive unit and a second drive unit respectively arranged along the X-axis and Y-axis. The first drive unit includes a first drive motor 5 and a first lead screw 6 for driving movement along the X-axis. The second drive unit includes a second drive motor 7 and a second lead screw 8 for driving movement along the Y-axis. The XY slide assembly is used to drive the sensor array plate 9 to move in the horizontal plane.

[0028] In some embodiments, the sensor array plate 9 is a matrix arrangement structure, and multiple gas sensors are uniformly arranged on the surface of the array plate in an M×N matrix manner. Multiple gas sensors are connected via a bus, which includes power lines and signal lines, used to transmit the detection signals from the multiple sensors to the data acquisition module.

[0029] The sensor array board 9 measures 15cm x 15cm and contains 25 electrochemical gas sensors arranged in a 5x5 configuration. All sensors are connected to the control board via a four-wire bus, and signal interference is filtered before entering the main control unit.

[0030] In some embodiments, please refer to Figure 2 As shown, the present invention provides a gas leak detection method, comprising the following steps: Step S1: Deploy detection devices at each leakage risk point and establish a three-dimensional environmental spatial model; By retrieving historical leakage event data, manual experience rules, or knowledge base systems, the plant area is risk-identified and classified into regions to determine high-risk locations that require key monitoring. A three-dimensional coordinate system is then constructed in modeling software for precise deployment and subsequent data visualization.

[0031] For example, in a high-pressure gas transmission plant, the system imports leakage alarm records and equipment maintenance data from the past three years, and the expert system identifies key pipeline interfaces, valve groups, storage tanks and other areas as high-risk points. Based on the BIM model, a digital three-dimensional coordinate map is generated, marking the deployment location and numbering information of the detection devices.

[0032] Step S2: Control the three-axis moving structure in the detection device to move the sensor array plate 9 to the preset detection height and detection area; Based on the inspection path or designated points set in the 3D model, the control module activates the three-axis drive structure to move the sensor array board 9 to the target spatial position, realizing multi-point inspection deployment with adjustable height and precise positioning.

[0033] Step S3: Collect gas concentration data at multiple locations using the sensor array board 9. The data is then transmitted in real time from the data acquisition module to the data processing module. Using a matrix-deployed multi-sensor array board 9 as the sensing front end, the concentration values ​​of each point within the coverage area are collected and transmitted to the control system in real time via a bus to construct a spatiotemporal distribution feature map.

[0034] The sensor array board 9 is equipped with 25 gas sensors, which are connected to the data acquisition module via a bus. The data is acquired at a frequency of 1Hz and cached at the edge node. The concentration data is then uploaded to the control module of the host processing system.

[0035] Step S4: The control module preprocesses the collected concentration data. When the concentration value output by a certain sensor exceeds the set threshold, a local scan is performed, and the three-axis moving structure is controlled to drive the sensor array board 9 to further detect in the abnormal area. When the device detects an abnormal increase in any sensor concentration (exceeding the set concentration threshold), it triggers a three-dimensional local rescanning mechanism to perform compensation measurements centered on that point, ensuring that the leak judgment is based on the consistency of multi-point data rather than a single-point anomaly.

[0036] For example, in this embodiment, if a unit in the sensor array detects a concentration value exceeding 60 ppm, the device controls the triaxial mechanism to generate a scanning grid with a radius of 30 cm around that point, and the array plate performs a re-inspection action within this range in an XYZ linkage manner to eliminate occasional false alarms.

[0037] When the concentration data of a certain sensor exceeds the set threshold, the control module controls the three-axis moving structure to make local fine adjustments with the location of the sensor as the center. During the local scanning process, the three-axis moving structure uses the XYZ three-axis linkage to control the sensor array board 9 to make joint adjustments to the vertical height and planar position in the area, and drives the sensor array board 9 to generate multiple detection points around the location, so that multiple different sensors can repeatedly detect the same leakage area. By generating multiple detection points around a suspected point and staggering them in space, multiple sensors at different angles can cross-measure the same location, thereby improving the accuracy and robustness of leak detection.

[0038] In this embodiment, the device sets the local detection radius to 40cm, uses a triaxial interpolation algorithm to generate 9 staggered detection points, performs full-dimensional movement, measures the planar data of three layers with heights of 100cm, 120cm, and 140cm respectively, and compares the concentration change trend to determine the intensity distribution of the leakage source.

[0039] Step S5: The data processing module performs consistency analysis and fusion processing on the multi-sensor data obtained from the local scan to determine whether it is a real leakage event. By comparing the response delay, spatial distribution pattern, and concentration gradient intensity among multiple data points, the device uses consistency analysis to determine whether the data source is a transient disturbance, equipment failure, or an actual leakage event.

[0040] In this embodiment, the device determines a real leak based on rules such as "response time window < 5s", "concentration values ​​of more than 3 points are higher than the threshold", and "spatial gradient > 10ppm / m", and then performs subsequent alarm and model update operations.

[0041] When multiple gas sensors on sensor array board 9 detect abnormal concentration data, the data processing module uses a combination of fitting analysis and reverse derivation based on the concentration time-series changes, response time differences, and concentration spatial gradients of multiple sensors at different locations in three-dimensional space. The sensor region that responds earliest is identified, and the initial spatial location of the leak point is deduced by using the response time difference between it and the surrounding points. By combining the concentration growth rate and the spatial gradient direction, the diffusion direction and diffusion rate of the leaked gas are calculated. A leakage hazard level scoring model was constructed by using peak concentration, concentration change rate, gradient intensity, and response synchronization as multiple input factors. The hazard level is determined by a leakage hazard level scoring model, and the prediction results are updated synchronously with the hazard level in the three-dimensional spatial model. By using empirical parameters from typical leakage events to set up a scoring model and combining it with real-time detection data for quantitative assessment, dynamic, accurate, and visible hazard classification can be achieved.

[0042] The scoring model uses a five-dimensional feature vector {C_peak, dC / dt, ∇C, ΔT, R_sync} and employs a support vector machine (SVM) classification algorithm to output four risk levels: "low, medium, high, and very high". The corresponding risk volume regions are marked with different colors in the three-dimensional model.

[0043] Wherein: C_peak (concentration peak): refers to the maximum value among all concentration data collected by all sensors during the local scanning process, reflecting the upper limit of the leakage intensity.

[0044] dC / dt (concentration change rate): refers to the rate of change of concentration value of a certain sensor within a set time window, used to characterize the release rate of leaked gas in a short period of time.

[0045] ∇C (concentration spatial gradient): refers to the concentration difference between multiple adjacent sensors divided by the spatial distance, reflecting the diffusion trend and directionality of the concentration around the leakage source.

[0046] ΔT (response time difference): refers to the time difference between different sensors when the concentration first detects that the concentration exceeds the threshold, reflecting the speed and time series characteristics of the leak propagation.

[0047] R_sync (response synchronization level): refers to the proportion of sensors that simultaneously detect abnormal signals within a unit time window to the total number of sensors, used to reflect the overall consistency level of multi-point data.

[0048] Step S6: If a leakage event is determined, the alarm feedback module outputs an alarm signal, synchronously updates the leakage event information in the three-dimensional spatial model, and uploads it to the remote monitoring platform. By combining a 3D visualization platform, the spatial marking of the leak location and the real-time display of the risk propagation area can be achieved. At the same time, information is uploaded to the cloud platform to realize coordinated emergency response.

[0049] After the alarm feedback module is activated, it transmits the alarm number, concentration peak, predicted source coordinates, diffusion direction vector and level assessment results to the central control system, updates the volume rendering layer in the 3D model and pushes it to the cloud platform web terminal.

[0050] After the three-dimensional spatial model is synchronously labeled with the leakage direction, the control module adjusts the alarm threshold of the sensors of the platform corresponding to the adjacent detection devices along the path pointed to by the leakage direction vector. This adjustment is based on the position distance weighting function and the risk reduction model. The alarm threshold adjustment includes a preset maximum reduction range, and the target threshold for each sensor in each adjacent detection platform is calculated based on a spatial weighting function. Based on the diffusion path, the potential affected area is inferred. By using a regional weighting strategy, the sensitivity of the sensors of the detection device along the path is dynamically adjusted to improve the rapid identification capability.

[0051] For example, in this embodiment, the leakage direction is 45° east of northeast. The device detects three sets of devices within 1 to 10 meters of the leakage point in this direction and calculates their sensor threshold reduction ratios as 10%, 7%, and 5% to avoid missing early diffusion signals of low concentration.

[0052] When the real-time concentration value of any sensor in an adjacent platform reaches the dynamically adjusted alarm threshold, the control module triggers the detection device of that platform to perform a local scanning process, record the sensor data, and match and compare it with the leakage diffusion direction recorded in the three-dimensional model. The comparison process uses a concentration response consistency calculation model, and based on the spatial direction error threshold and response time window, confirms that the direction is the actual diffusion direction of the current leak, and updates the state of the three-dimensional spatial model.

[0053] By setting spatial offset and response delay thresholds and verifying the accuracy of direction prediction by combining multi-point concentration evolution paths, the leakage diffusion model can be corrected in real time and dynamically evolved.

[0054] For example, in this embodiment, if the directional offset angle is less than 15° and the response time difference is no more than 8 seconds during the comparison process, the device confirms that the diffusion direction prediction is accurate and expands the directional vector extension range to a region 5 meters away, while lowering the warning threshold of the remote device.

[0055] In some embodiments, this application provides a terminal, including: Memory, used to store gas leak detection simulation programs; A processor is used to execute the steps of the gas leak detection method when the gas leak detection device is used.

[0056] In some embodiments, this application provides a computer-readable storage medium that stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the gas leak detection method.

[0057] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A gas leak detection device, characterized in that, The detection device includes a three-axis moving structure and a sensor array plate (9). The sensor array plate (9) is set on the end moving platform of the three-axis moving structure. Multiple gas sensors are arranged on the sensor array plate (9) to acquire gas concentration data at different locations. The three-axis moving structure is used to drive the sensor array to move in three-dimensional space to cover the area to be measured. The detection device also includes a data acquisition module, a control module, a data processing module, and an alarm feedback module; The data acquisition module is used to acquire real-time concentration data output from multiple gas sensors; The control module is used to control the three-axis moving structure to move the sensor array plate (9) according to the preset path or dynamic feedback information, and to trigger a local scan when abnormal concentration data is detected; The data processing module is used to perform consistency analysis and fusion processing on data collected by multiple gas sensors in order to determine whether a leak event exists; The alarm feedback module is used to output an alarm signal and send the analysis results to the remote monitoring platform when a leakage event is determined to be true.

2. The gas leak detection device according to claim 1, characterized in that, The three-axis moving mechanism includes a Z-axis lifting assembly and an XY slide assembly; The Z-axis lifting assembly includes a vertical guide rail (1) and a platform drive unit for driving the lifting. The platform drive unit includes a lifting motor (2), a lifting screw (3), and a lifting platform (4). The Z-axis lifting assembly is used to adjust the height position of the sensor array plate (9) in the vertical direction. The XY slide assembly is mounted on the lifting platform (4) of the Z-axis lifting assembly. The XY slide assembly includes a first drive unit and a second drive unit respectively arranged along the X-axis and Y-axis. The first drive unit includes a first drive motor (5) and a first lead screw (6) for driving movement along the X-axis. The second drive unit includes a second drive motor (7) and a second lead screw (8) for driving movement along the Y-axis. The XY slide assembly is used to drive the sensor array plate (9) to move in the horizontal plane.

3. The gas leak detection device according to claim 1, characterized in that, The sensor array board (9) has a matrix arrangement structure, with multiple gas sensors evenly arranged on the surface of the array board in an M×N matrix manner; Multiple gas sensors are connected via a bus, which includes power lines and signal lines, to transmit the detection signals from the multiple sensors to the data acquisition module.

4. A gas leak detection method, characterized in that, This method, based on the gas leak detection device according to any one of claims 1 to 3, includes the following steps: Step S1: Deploy detection devices at each leakage risk point and establish a three-dimensional environmental spatial model; Step S2: Control the three-axis moving structure in the detection device to move the sensor array plate (9) to the preset detection height and detection area; Step S3: Collect gas concentration data at multiple locations through the sensor array board (9), and transmit the data to the data processing module in real time via the data acquisition module; Step S4: The control module preprocesses the collected concentration data. When the concentration value output by a certain sensor exceeds the set threshold, a local scan is performed. The three-axis moving structure is controlled to drive the sensor array plate (9) to further detect in the abnormal area. Step S5: The data processing module performs consistency analysis and fusion processing on the multi-sensor data obtained from the local scan to determine whether it is a real leakage event. Step S6: If a leakage event is determined, the alarm feedback module outputs an alarm signal, synchronously updates the leakage event information in the three-dimensional spatial model, and uploads it to the remote monitoring platform.

5. The gas leak detection method according to claim 4, characterized in that, In step S4, when the concentration data of a certain sensor exceeds the set threshold, the control module controls the three-axis moving structure to make local fine adjustments with the location of the sensor as the center. During the local scanning process, the three-axis moving structure uses the XYZ three-axis linkage to control the sensor array board (9) to make joint adjustments to the vertical height and planar position in the area, and drives the sensor array board (9) to generate multiple detection points around the location, so that multiple different sensors can repeatedly detect the same leakage area.

6. The gas leak detection method according to claim 4, characterized in that, In step S5, when multiple gas sensors on the sensor array board (9) detect abnormal concentration data, the data processing module uses a combination of fitting analysis and reverse derivation based on the concentration time-series changes, response time differences and concentration spatial gradients of multiple sensors at different locations in three-dimensional space. The sensor region that responds earliest is identified, and the initial spatial location of the leak point is deduced by using the response time difference between it and the surrounding points. By combining the concentration growth rate and the spatial gradient direction, the diffusion direction and diffusion rate of the leaked gas are calculated. A leakage hazard level scoring model was constructed by using peak concentration, concentration change rate, gradient intensity, and response synchronization as multiple input factors. The hazard level is determined by a leakage hazard level scoring model, and the prediction results are updated synchronously with the hazard level in the three-dimensional spatial model.

7. The gas leak detection method according to claim 6, characterized in that, After the three-dimensional spatial model is synchronously labeled with the direction of leakage, the control module adjusts the alarm threshold of the sensors on the platform corresponding to the adjacent detection devices along the path pointed to by the leakage direction vector, based on the position distance weighting function and the risk reduction model. The alarm threshold adjustment includes a preset maximum reduction range, and the target threshold for each sensor in each adjacent detection platform is calculated based on a spatial weighting function.

8. The gas leak detection method according to claim 7, characterized in that, When the real-time concentration value of any sensor in an adjacent platform reaches the dynamically adjusted alarm threshold, the control module triggers the detection device of that platform to perform a local scanning process, record the sensor data, and match and compare it with the leakage diffusion direction recorded in the three-dimensional model. The comparison process uses a concentration response consistency calculation model, and based on the spatial direction error threshold and response time window, confirms that the direction is the actual diffusion direction of the current leak, and updates the state of the three-dimensional spatial model.

9. A terminal, characterized in that, include: Memory, used to store gas leak detection simulation programs; A processor is configured to implement the steps of the gas leak detection method as described in claim 4 when executing the gas leak detection device.

10. A computer-readable storage medium, characterized in that, The storage medium stores computer instructions. When the computer reads the computer instructions from the storage medium, the computer executes the gas leak detection method as described in claim 4.

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