Underway vehicle-mounted laser gas leakage detection equipment and method

Abstract

The invention belongs to the field of fuel gas leakage cruise detection, and discloses underway type vehicle-mounted laser fuel gas leakage detection equipment and method, and the equipment comprises a pumping type laser methane ethane detector, an overhead telemetering laser methane detector, and an unmanned vehicle. A pumping type laser methane ethane detector and an overhead telemetering laser methane detector are integrated with an unmanned vehicle, and all-directional dead-corner-free gas concentration detection of fuel gas from a near field to a far field is realized through an active sample extraction or remote laser telemetering technology. More importantly, through a data false alarm filtering algorithm and a gas leakage tracing algorithm, the methane leakage source can be accurately judged, the equipment false alarm rate can be reduced, the leakage source point can be positioned, and a high-efficiency and high-precision solution is provided for safety monitoring and management of an urban gas pipe network.

Description

Technical Field

[0001] The present invention belongs to the field of cruise detection of gas leaks, and in particular relates to combining unmanned vehicle gas leak detection technology to realize unmanned driving, gas leak detection and methods, and specifically relates to a cruise-type vehicle-mounted laser gas leak detection equipment and method. Background Art

[0002] In the context of rapid urbanization, gas safety issues are receiving increasing attention. Traditional gas leak detection technologies mainly include fixed monitoring stations and manual inspections. Fixed monitoring stations monitor the gas concentration in a specific area by installing highly sensitive gas alarms, but they have disadvantages such as difficulty in selecting the equipment installation location, inaccurate positioning of the leak point, and limited detection range. Although manual inspections are mobile and flexible and can overcome the shortcomings of fixed monitoring stations, they are inefficient and have obvious limitations due to the location of the leak point and the direction of gas injection. In order to improve the accuracy and efficiency of detection, some technologies have begun to use drones equipped with laser methane telemeters for gas leak detection. They have the advantages of flexibility and remote operation, but are limited by endurance and operational technical requirements and are not suitable for large-scale urban gas inspections. There are also IoT devices that continuously monitor the temperature and pressure of gas pipelines to detect gas leaks. However, this method is highly dependent on the accuracy of the algorithm, and there are challenges in parameter acquisition. It is also susceptible to environmental interference and equipment failure. In addition, in urban inspections, faced with the diversity and complexity of gas composition, especially the source of methane, which includes not only natural gas leaks, but also biogas, automobile exhaust and a variety of uncertain gases, accurately distinguishing emission sources and reducing the false alarm rate of gas leaks are key tasks to improve the efficiency of gas safety management.

[0003] In view of this, the present invention proposes a cruise-type vehicle-mounted laser gas leak detection equipment and method. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a cruise-type vehicle-mounted laser gas leak detection equipment and method to improve the foresight and initiative of gas safety management in smart city construction. The equipment integrates overhead telemetry laser methane detection technology and pump-suctioned methane and ethane detection technology, as well as Beidou precise positioning and L4 level automatic driving technology to achieve all-round, efficient and precise monitoring and management of urban gas pipeline networks. Through data false alarm filtering and gas leak tracing algorithm based on composite shape method, gas leakage events can be quickly and accurately identified, the influence of other methane emission sources can be eliminated, and the leakage source can be accurately located. Finally, a spatial distribution map of methane and ethane concentration is generated, and the concentration abnormal areas are marked to provide city managers with an intuitive leakage risk view. The present invention provides scientific decision-making support for municipal managers by improving detection accuracy, optimizing data presentation, and enhancing automation level, effectively improving the management efficiency and accuracy of urban gas pipeline networks.

[0005] To achieve the above object, the present invention provides the following solutions:

[0006] A cruise-type vehicle-mounted laser gas leak detection equipment, the equipment comprising: a pump-suction laser methane and ethane detector, a top-mounted telemetry laser methane detector, and an unmanned vehicle;

[0007] The pump-suction laser methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with the unmanned vehicle. Through active sampling or long-distance laser telemetry technology, the gas concentration of the gas is detected in all directions from near field to far field without blind spots.

[0008] Preferably, a pump-suction laser methane and ethane detector is installed at the front of the unmanned vehicle and close to the ground to facilitate direct extraction of ambient air samples, and a top-mounted telemetry laser methane detector is installed directly above the unmanned vehicle for long-distance detection.

[0009] Preferably, the equipment uses the Beidou satellite navigation system for positioning, combined with geographic information system (GIS) technology, to achieve real-time recording and analysis of detected gas concentration data.

[0010] Preferably, the unmanned vehicle integrates a set of meteorological monitoring equipment that can provide key meteorological parameters including wind speed, wind direction, temperature and air pressure.

[0011] The present invention also provides a cruise-type vehicle-mounted laser gas leak detection method, which is implemented by using any of the cruise-type vehicle-mounted laser gas leak detection equipment described above, and the method comprises:

[0012] After the pump-suction laser methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with the unmanned vehicle, the inspection is started by the preset or manually input initial concentration threshold. At the same time, the back-end system administrator can view the real-time monitoring and analysis of methane and ethane concentration data through the web terminal, as well as the detection of environmental parameters and unmanned vehicle status information;

[0013] When abnormal gas concentration is detected, the data false alarm filtering algorithm is used to determine the source of the leak. If it is confirmed to be a gas leak, the unmanned vehicle will automatically adjust the inspection route and conduct a full range of key inspections on the warning area;

[0014] Record key indicators, generate gas concentration early warning inspection reports, extract features from detection data, and use gas leak tracing algorithms to deduce the source of the leak;

[0015] Generates detailed inspection record reports and methane and ethane concentration distribution maps. In addition, the system performs in-depth analysis on areas with abnormal concentrations and clearly marks them on the map to facilitate the identification of potential risk areas. At the same time, it marks possible leakage sources calculated by the gas tracing algorithm to achieve global monitoring of gas concentration distribution and leakage conditions, thereby improving the efficiency and responsiveness of gas safety management.

[0016] Preferably, using a data false positive filtering algorithm to determine the source of the leak includes:

[0017]

[0018] Where R is the abnormal enhancement ratio of methane and ethane concentration; X0 is the initial methane concentration; Y0 is the initial ethane background; X and Y are the methane and ethane concentration values ​​corresponding to the data points of the abnormal classification data set, respectively;

[0019] If R<0, check if the concentration changes of methane and ethane are inconsistent, and judge the source of methane to be biogas or other gases; if R>0, and the concentrations of methane and ethane are analyzed by Spearman rank correlation coefficient, P<0.05, then methane and ethane show significant correlation and are judged to be natural gas, otherwise it is biogas or other gases.

[0020] Preferably, the calculation of the initial concentration of methane and ethane includes:

[0021] According to the real-time monitoring data, a sliding time series data set {x1,x2,x3,…,x n}, the window size is N, and each time node is taken as the center to calculate the average value of the data points in the window:

[0022]

[0023] The calculation is updated as new data points are added and old data points are removed;

[0024] For the same time window, calculate the standard deviation:

[0025]

[0026] According to experience, the judgment threshold is selected as V t +nS t , where n is selected as 1, 2, 3, ...; if a new data point exceeds the threshold, indicating a leakage event or an abnormal situation, the data point will be excluded from the moving average calculation.

[0027] Preferably, calculating the leak source using a gas leak source tracing algorithm includes:

[0028] A coordinate system is established in the gas diffusion space where the methane concentration exceeds the standard, with the wind direction defined as the X-axis, the direction parallel to the ground and perpendicular to the wind direction defined as the Y-axis, and the direction perpendicular to the ground as the Z-axis, i.e., the height; when continuous gas leakage is detected, the leaked methane concentration at each point in the space is obtained based on the cruise-type vehicle-mounted laser gas leak detection equipment;

[0029] If the gas leakage source is on the ground or below the ground and overflows from the ground, the leakage type is a continuous leakage from a ground point source. Then the leakage rate of the leakage point in the diffusion space is calculated based on the leakage gas concentration at each point:

[0030]

[0031] If the leakage source is at a predetermined height above the ground, the leakage type is an elevated point source continuous leakage. Considering the reflection of the leaking gas by the ground, the leakage rate calculation formula of the leakage point is:

[0032]

[0033] Where Q0 is the leakage rate of the leakage point, that is, the source strength; C(x, y, z) is the methane gas concentration detected at the monitoring point at (x, y, z) in space under the condition of continuous gas leakage; x, y, z are the spatial coordinates of the detection point; x0, y0, z0 are the spatial coordinates of the leakage source; σ y , σ z are the diffusion coefficients in the Z direction and the X direction, respectively, which are related to meteorological conditions and are determined according to atmospheric stability; u is the ambient wind speed;

[0034] The data collected at the monitoring point is called the measured concentration. The gas diffusion model is used to obtain the gas concentration formed by the hypothetical leakage source at the monitoring point, which becomes the calculated concentration. The relationship between the measured concentration and the calculated concentration is established to form the objective function, which is the traceability model:

[0035]

[0036] The source tracing model formula applicable to continuous leakage of ground point sources is:

[0037]

[0038] The continuous gas leakage tracing is to find a set of (x0, y0) or (x0, y0, Q0) so that the objective function F(x) gets the minimum value;

[0039] The gas diffusion process is simulated and compared with the actual data to obtain the simulation results with the smallest error, and finally the spatial location and source strength of the gas leakage source are determined.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention integrates overhead telemetry laser methane detection technology and pump-suctioned methane and ethane detection technology, as well as Beidou precise positioning and L4 level automatic driving technology, to provide a cruise-type laser gas leak detection equipment and system that can perform all-round, efficient and precise detection of urban gas pipelines. After the technology is implemented, the system detects trace gas leaks with ppb-level sensitivity through laser spectroscopy technology, ensuring high sensitivity and accuracy of detection. The combination of Beidou precise positioning technology and L4 level automatic driving technology improves the spatial distribution accuracy and inspection efficiency of methane and ethane gas concentration detection. In addition, the system can also use multi-type data integration and analysis technology, and a gas leak tracing algorithm based on the composite form method. Through the above technologies, the present invention can not only improve detection accuracy, optimize data presentation, and enhance the level of automation, but also provide scientific decision-making support for municipal managers, effectively improving the management efficiency and accuracy of urban gas pipelines. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solution of the present invention, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1 This is a schematic diagram of a flow chart of a vehicle-mounted laser gas leak detection method according to an embodiment of the present invention;

[0044] Figure 2 The present invention is a flowchart of the composite method for finding the optimal solution. DETAILED DESCRIPTION

[0045] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] Embodiment 1

[0048] The present invention provides a cruise-type vehicle-mounted laser gas leak detection equipment, the equipment comprising: a pump-suction laser methane and ethane detector, an overhead telemetry laser methane detector, and an unmanned vehicle;

[0049] The pump-suction laser methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with the unmanned vehicle. Through active sampling or long-distance laser telemetry technology, the gas concentration of the gas is detected in all directions from near field to far field without blind spots.

[0050] In this embodiment, the pump-suction laser methane and ethane gas detector adopts active sampling technology, introduces ambient air into the instrument through the pump-suction method, and uses the built-in laser to emit a laser beam of a specific wavelength, which is only absorbed by methane and ethane, thereby achieving high-precision measurement of the concentrations of these two gases. The system consists of a laser gas detector, a high-precision positioning module, a pump-suction device, and a data processing unit. The secondary sampling technology of the gas sampling unit in the pump-suction device not only improves the gas update rate, but also reduces the filtration requirements. This detector can detect low-concentration gases at a long distance, has strong adaptability, is suitable for areas with poor air circulation, and can provide strong technical guarantees for environmental safety.

[0051] In this embodiment, the overhead telemetry laser methane detector detects methane concentration from a distance by emitting lasers of a specific wavelength through the instrument and analyzing the absorption of methane gas. The advantages of this device are its high-precision monitoring capability, long-distance telemetry capability, strong anti-interference, durability in a variety of harsh environments, real-time monitoring and rapid alarm response, as well as low maintenance costs and long service life. In addition, Beidou / GPS dual-mode positioning and data transmission are added, making it particularly suitable for remote and large-area monitoring occasions.

[0052] In this embodiment, the pump-suction methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with an unmanned vehicle with L4 full-stack autonomous driving technology to construct a cruise-type vehicle-mounted laser gas leak detection equipment. The equipment can perform all-round gas concentration detection of methane from near field to far field without blind spots by actively extracting samples or using long-distance laser telemetry technology.

[0053] The pump-suction laser methane and ethane detector is now installed at the front of the vehicle, close to the ground, to facilitate direct extraction of ambient air samples, and the overhead telemetry laser methane detector is installed directly above the vehicle to provide a better perspective for long-distance detection. To ensure the accuracy and reliability of the detection data, this equipment uses the Beidou satellite navigation system for high-precision positioning, combined with geographic information system (GIS) technology to achieve real-time recording and analysis of the detected gas concentration data. In addition, the unmanned vehicle is equipped with integrated meteorological monitoring equipment that can provide accurate key meteorological parameters including wind speed, wind direction, temperature and air pressure. These meteorological parameters are the key environmental background for data filtering algorithms and leak source tracing analysis, ensuring the accuracy of detection data and the accuracy of leak source location. At the same time, these parameters are also used to optimize the cruising path of the unmanned vehicle and improve inspection efficiency.

[0054] Embodiment 2

[0055] like Figure 1 As shown, the present invention also provides a cruise-type vehicle-mounted laser gas leak detection method, which is implemented by using any of the cruise-type vehicle-mounted laser gas leak detection equipment described above, and the method includes:

[0056] System startup and threshold setting. Integrate the pump-suction laser methane and ethane detector, the top-mounted telemetry laser methane detector and the meteorological environment monitoring equipment into the unmanned vehicle, and start the inspection program through the preset or manually input initial concentration threshold. The back-end system administrator can view the real-time monitoring and analysis of methane and ethane concentration data through the web terminal, and monitor environmental parameters and unmanned vehicle status information at the same time;

[0057] Abnormal detection and route adjustment. When abnormal gas concentration is detected, the system uses a data false alarm filtering algorithm to determine the source of the leak. Once a gas leak is confirmed, the unmanned vehicle will automatically adjust the inspection route and conduct a full-scale inspection of the warning area to collect more detailed data;

[0058] Early warning and traceability analysis. Analyze and process the detection data, extract key characteristic indicators, and generate gas concentration early warning prompts. Then use the gas leak traceability algorithm to deduce the source of the leak, provide a gas leak concentration risk distribution map, and provide technical reference for emergency response;

[0059] Result recording and report generation. After the inspection, the system generates an inspection record report and a methane and ethane concentration distribution map, as well as a key analysis report on areas where gas concentration exceeds the standard, to achieve global monitoring of gas concentration distribution and leakage, thereby improving the efficiency and responsiveness of gas safety management.

[0060] In this embodiment, through the above-mentioned integrated cruise vehicle-mounted laser gas monitoring equipment, the operator can manually or default the gas concentration threshold through the device user interface, automatically plan the optimal inspection route according to the preset route or real-time task requirements, and ensure coverage of key areas. During the inspection process, real-time gas concentration change data will be generated and compared with historical data to facilitate the analysis of gas concentration trends and anomalies; when the gas concentration is detected to exceed the preset threshold, the equipment will automatically mark the abnormal point, and determine the methane emission source through the data false alarm filtering algorithm, and record detailed gas detection data and emission source type, and will separately save the current meteorological parameters and detection environment pictures for subsequent data analysis and leakage source location. In multiple warning areas, the unmanned vehicle will automatically adjust the driving mode, conduct multi-directional and multi-angle key detection, and increase the density and breadth of data collection.

[0061] In this embodiment, the data false alarm filtering and early warning algorithm based on the big data model:

[0062] Considering that the sources of methane emissions include not only gas leaks, but may also involve biogas, automobile exhaust and other uncertain gas sources, further analysis is needed to determine the specific emission sources of the gas for the detected gas concentration exceeding the standard. There are differences in the content standards of methane and ethane in different gases. For example, methane in natural gas usually contains a certain proportion of hydrocarbon gases such as ethane and propane, while biogas may contain more carbon dioxide and hydrogen. By analyzing the ratio of methane to its associated gas, it is possible to assist in determining the source of methane. When the equipment detects excessive gas concentration for the first time, the unmanned vehicle automatically adjusts its driving to obtain multi-directional and multi-angle detection data. Based on these data, the methane and ethane concentration data at the location where the warning is issued continuously are classified as abnormal, taking the initial background concentration of methane and ethane (X0, Y0) as the benchmark. The data false alarm filtering algorithm can automatically identify and classify a large amount of data and calculate the abnormal enhancement ratio of methane and ethane concentrations:

[0063]

[0064] X0 is the initial concentration of methane; Y0 is the initial concentration of ethane; X and Y are the methane and ethane concentration values ​​corresponding to the data points of the anomaly classification data set.

[0065] If R<0, the concentration changes of methane and ethane are inconsistent, and the source of methane is judged to be biogas or other gases; if R>0, and the concentrations of methane and ethane are analyzed by Spearman rank correlation coefficient, P<0.05, then methane and ethane show a significant correlation and are judged to be natural gas, otherwise it is biogas or other gases.

[0066] Calculation of initial methane and ethane concentrations:

[0067] In urban environments, gas compositions are complex and varied, and the initial background concentrations of methane and ethane fluctuate over time. This variation is mainly due to the shift in inspection locations, such as from residential to commercial areas, to industrial areas, or to areas with heavy traffic. In residential areas, methane and ethane emissions may increase due to household cooking and heating activities, while in commercial areas, the catering industry and commercial activities may produce different gas emission characteristics. In addition, industrial emissions in industrial areas and vehicle exhaust emissions in areas with heavy traffic also affect the concentrations of methane and ethane. Therefore, the initial background concentrations of methane and ethane in these different areas may vary due to differences in human activities and energy consumption patterns. During the inspection process, by monitoring the concentrations of methane and ethane in real time, we can estimate and track the central trend (such as the mean or median) and dispersion (such as the standard deviation or coefficient of variation) of the data set where the concentrations of these gases change over time.

[0068] According to the real-time monitoring data, a sliding time series data set {x1,x2,x3,…,x n}, the window size is N. Taking each time node as the center, calculate the average value of the data points in the window:

[0069]

[0070] The calculation is updated as new data points are added and old data points are removed.

[0071] For the same time window, calculate the standard deviation:

[0072]

[0073] In order to avoid the influence of abnormal data in the selected window on the moving average, the judgment threshold is selected based on experience = V t +nS t , where n can be selected as 1, 2, 3, ... If a new data point exceeds the threshold, it may indicate a leak event or an abnormal situation, and the data point will be excluded from the moving average calculation to avoid affecting the estimation of the background concentration.

[0074] Through the above filtering algorithm, real gas leakage events can be effectively identified from a large amount of data, reducing false alarms of methane concentration, thereby achieving accurate gas leakage warning.

[0075] In this embodiment, the gas leak source tracing algorithm based on vehicle-mounted cruising data is as follows:

[0076] The core principle of the algorithm is to extract the peak concentration characteristics near the leakage point by analyzing the changing trend and characteristics of the concentration data. Then, a gas diffusion model is established by combining the movement trajectory of the vehicle-mounted monitoring equipment and environmental parameters such as wind speed and wind direction. By simulating the diffusion process of gas within a preset distance range and performing error analysis with the actual monitoring data, the algorithm can find the most matching simulation data. Finally, the prediction algorithm and the vehicle driving path are used to determine the approximate location and traceability range of the leakage source, so as to achieve accurate positioning of the leakage source.

[0077] Algorithm implementation steps:

[0078] First, a coordinate system is established based on the gas diffusion space where the methane concentration exceeds the standard. The wind direction is defined as the X-axis, the direction parallel to the ground and perpendicular to the wind direction is defined as the Y-axis, and the direction perpendicular to the ground is the Z-axis, i.e., the height. When a possible continuous gas leak is detected, the concentration of methane leaked at each point in the space can be known based on the cruise gas leak detection equipment. If the gas leak source is on the ground or below the ground and overflows from the ground, the leak type is a continuous ground point source leak.

[0079] Then the leakage rate of the leakage point in the diffusion space can be calculated according to the leakage gas concentration at each point by the following formula (Gaussian plume diffusion model):

[0080]

[0081] If the leak source is at a certain height above the ground, the leak type is an elevated point source continuous leak. Considering the reflection of the leaking gas from the ground, the leakage rate calculation formula of the leak point is:

[0082]

[0083] Where Q0 is the leakage rate of the leakage point, that is, the source strength, mg / s;

[0084] C(x,y,z) is the methane gas concentration detected at the monitoring point (x,y,z) in the space under the condition of continuous gas leakage, mg / m 3 ;

[0085] x, y, z are the spatial coordinates of the detection point, m

[0086] x0, y0, z0 are the spatial coordinates of the leakage source, m;

[0087] σ y , σ zare the diffusion coefficients in the Y and Z directions, respectively, which are related to meteorological conditions and their values ​​are determined according to atmospheric stability;

[0088] u is the ambient wind speed, m / s;

[0089] The Gaussian gas diffusion model is used as the pre-model, and the leakage source information is used as the solution to build a traceability model. The data collected at the monitoring point is called the measured concentration. The gas concentration formed by the hypothetical leakage source at these monitoring points is obtained by using the gas diffusion model to become the calculated concentration The relationship between the measured concentration and the calculated concentration is established to form the objective function, which is the traceability model.

[0090]

[0091] Therefore, the tracing model formula applicable to continuous leakage of ground point sources is:

[0092]

[0093] The construction of the traceability model transforms the gas leakage traceability problem into a multi-parameter optimization problem. Continuous gas leakage traceability is to find a set of (x0, y0) or (x0, y0, Q0) to minimize the objective function F(x). In this calculation process, the values ​​and combinations of (x0, y0) or (x0, y0, Q0) need to be adjusted continuously. This time, the traceability model is combined with the composite method to solve the gas leakage source location and leakage source strength through multiple parameters.

[0094] The composite method is a direct search method for solving optimization problems. It does not require gradient information and is suitable for linear and nonlinear programming problems. The following is the operation principle and steps of the composite method. Figure 2 :

[0095] (1) Initialization: Determine the number of parameters D of the optimization problem and the value range of each parameter;

[0096] Generate an initial composite shape, usually composed of D+1 vertices;

[0097] (2) Calculate the vertex function value, for each vertex X i , calculate the corresponding objective function value F(X i );

[0098] (3) Vertex classification: among the selected vertices, find the best and worst vertices, which are X best , X worst ;

[0099] (4) Centroid calculation: calculate the centroid Xcent of all vertices except the worst point.

[0100]

[0101] (5) Reflection and extension, at the worst point X worst Based on this, a new reflection point X is generated along the centroid direction. ref , where α is the reflection coefficient, usually greater than 1;

[0102] X ref =X ref +α(X ref -X ref )

[0103] If the reflection point is better than Xbest, an extension point Xexp is further generated, where β is the expansion coefficient, which is usually greater than α;

[0104] X exp =X cent +β(X ref -X cent )

[0105] (6) Replacement and contraction: if the reflection point or expansion point is better than the best point, then the worst point is replaced; if the reflection point is worse than the best point but better than the worst point, then the worst point is replaced with the reflection point;

[0106] If the reflection point is worse than the worst point, the transition is extended and contraction needs to be performed to regenerate the contraction point Xcont, where γ is the contraction system, which is usually less than 1;

[0107] X cont =X cent +γ(X worst -X cent )

[0108] (7) Iterative update: According to the above steps, update the vertex set of the composite shape and repeat steps 2-6 until the convergence condition is met. At this time, the vertex X with the minimum objective function best is the optimal solution of the algorithm.

[0109] Diffusion simulation and error analysis: Simulate the gas diffusion process, compare with the actual data, and find the simulation result with the smallest error.

[0110] We now take a gas pipeline leak in a residential building as an example, as a continuous point source leak scenario, and take the location where the leak detection equipment first detected the concentration exceeding the standard as the origin, the leak source spatial coordinates (8, 15, 2), source strength Q0 = 8500mg / s. After the detection equipment detects that the gas concentration exceeds the threshold, it adjusts the inspection path according to the wind speed and direction to collect methane and ethane gas concentration detection data at more spatial locations. We conduct source tracing analysis on this leak incident and inversely calculate the spatial coordinates of the leak source (x0, y 0，z0) and source strength Q0; initially set the composite positioning D = 6, the convergence condition is eps = 0.001, the compression coefficient is 0.5, and the expansion coefficient (expansion coefficient and reflection coefficient) is 2, and iterates 1000 times. According to the above composite method analysis process, the gas leakage source is traced and analyzed, and the coordinates of the leakage source point are obtained as (8.4256, 14.2725, 2.127), the source strength Q = 8064.8mg / s, and the absolute value of the relative error of the leakage source coordinates is within 10%.

[0111] Table 1 Error analysis of traceability results

[0112]

[0113] The present invention helps to improve the sensitivity and selectivity of detection by integrating the overhead telemetry laser detection system with the pump-suction methane and ethane detection system. Combined with the application of unmanned vehicles, it can not only expand the coverage of the inspection, but also effectively improve the inspection efficiency, and realize comprehensive and large-scale gas safety monitoring. Compared with drones, this solution does not need to consider the problem of short-term endurance, and can continuously perform long-term and large-scale inspection tasks. Through the application of intelligent data filtering algorithms, the interference of non-target methane release sources such as automobile exhaust and biogas is effectively eliminated, and the accuracy of gas leak detection is significantly improved. In addition, the present invention proposes a gas leak tracing algorithm based on the composite method, which can track and locate the gas leak source, and evaluate the potential impact of the gas leak based on the tracing results. Through the application of the above innovative technologies, the present invention not only significantly improves the efficiency and accuracy of gas leak detection, but also provides more comprehensive and scientific technical support for urban gas safety management, ensuring the sustainable development of public safety and the environment.

[0114] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A cruise-type vehicle-mounted laser gas leak detection equipment, characterized in that: The equipment includes: a pump-suction laser methane and ethane detector, an overhead telemetry laser methane detector, and an unmanned vehicle; The pump-suction laser methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with the unmanned vehicle. Through active sampling or long-distance laser telemetry technology, the gas concentration of the gas is detected in all directions from near field to far field without blind spots.

2. The device according to claim 1, characterized in that: The pump-suction laser methane and ethane detector is installed at the front of the unmanned vehicle and close to the ground to facilitate the direct extraction of ambient air samples. The top-mounted telemetry laser methane detector is installed directly above the unmanned vehicle for long-distance detection.

3. The device according to claim 1, characterized in that: The equipment adopts the Beidou satellite navigation system for positioning and combines the geographic information system (GIS) technology to achieve real-time recording and analysis of the detected gas concentration data.

4. The device according to claim 1, characterized in that: The unmanned vehicle integrates a set of meteorological monitoring equipment that can provide key meteorological parameters including wind speed, wind direction, temperature and air pressure.

5. A cruise-type vehicle-mounted laser gas leak detection method, implemented by using a cruise-type vehicle-mounted laser gas leak detection equipment according to any one of claims 1 to 4, characterized in that: The method comprises: After the pump-suction laser methane and ethane detector and the top-mounted telemetry laser methane detector are integrated with the unmanned vehicle, the inspection is started by the preset or manually input initial concentration threshold. At the same time, the back-end system administrator can view the real-time monitoring and analysis of methane and ethane concentration data through the web terminal, as well as the detection of environmental parameters and unmanned vehicle status information; When abnormal gas concentration is detected, the data false alarm filtering algorithm is used to determine the source of the leak. If it is confirmed to be a gas leak, the unmanned vehicle will automatically adjust the inspection route and conduct a full range of key inspections on the warning area; Record key indicators, generate gas concentration early warning inspection reports, extract features from detection data, and use gas leak tracing algorithms to deduce the source of the leak; Generates detailed inspection record reports and methane and ethane concentration distribution maps. In addition, the system performs in-depth analysis on areas with abnormal concentrations and clearly marks them on the map to facilitate the identification of potential risk areas. At the same time, it marks possible leakage sources calculated by the gas tracing algorithm to achieve global monitoring of gas concentration distribution and leakage conditions, thereby improving the efficiency and responsiveness of gas safety management.

6. The method according to claim 5, characterized in that The sources of leaks determined by using the data false positive filtering algorithm include: Where R is the abnormal enhancement ratio of methane and ethane concentration; X0 is the initial methane concentration; Y0 is the initial ethane background; X and Y are the methane and ethane concentration values ​​corresponding to the data points of the abnormal classification data set, respectively; If R<0, check if the concentration changes of methane and ethane are inconsistent, and judge the source of methane to be biogas or other gases; if R>0, and the concentrations of methane and ethane are analyzed by Spearman rank correlation coefficient, P<0.05, then methane and ethane show significant correlation and are judged to be natural gas, otherwise it is biogas or other gases.

7. The method according to claim 6, characterized in that The calculation of the initial methane and ethane concentrations includes: According to the real-time monitoring data, a sliding time series data set {x1,x2,x3,…,x n }, the window size is N, and each time node is taken as the center to calculate the average value of the data points in the window: The calculation is updated as new data points are added and old data points are removed; For the same time window, calculate the standard deviation: According to experience, the judgment threshold is selected as V t +nS t , where n is selected as 1, 2, 3, ...; if a new data point exceeds the threshold, indicating a leakage event or an abnormal situation, the data point will be excluded from the moving average calculation.

8. The method according to claim 5, characterized in that The gas leak source tracing algorithm is used to deduce the leak sources, including: A coordinate system is established in the gas diffusion space where the methane concentration exceeds the standard, with the wind direction defined as the X-axis, the direction parallel to the ground and perpendicular to the wind direction defined as the Y-axis, and the direction perpendicular to the ground as the Z-axis, i.e., the height; when continuous gas leakage is detected, the leaked methane concentration at each point in the space is obtained based on the cruise-type vehicle-mounted laser gas leak detection equipment; If the gas leakage source is on the ground or below the ground and overflows from the ground, the leakage type is a continuous leakage from a ground point source. Then the leakage rate of the leakage point in the diffusion space is calculated based on the leakage gas concentration at each point: If the leakage source is at a predetermined height above the ground, the leakage type is an elevated point source continuous leakage. Considering the reflection of the leaking gas by the ground, the leakage rate calculation formula of the leakage point is: Where Q0 is the leakage rate of the leakage point, that is, the source strength; C(x, y, z) is the methane gas concentration detected at the monitoring point at (x, y, z) in space under the condition of continuous gas leakage; x, y, z are the spatial coordinates of the detection point; x0, y0, z0 are the spatial coordinates of the leakage source; σ y , σ z are the diffusion coefficients in the Z direction and the X direction, respectively, which are related to meteorological conditions and are determined according to atmospheric stability; u is the ambient wind speed; The data collected at the monitoring point is called the measured concentration. The gas diffusion model is used to obtain the gas concentration formed by the hypothetical leakage source at the monitoring point, which becomes the calculated concentration. The relationship between the measured concentration and the calculated concentration is established to form the objective function, which is the traceability model: The source tracing model formula applicable to continuous leakage of ground point sources is: The continuous gas leakage tracing is to find a set of (x0, y0) or (x0, y0, Q0) so that the objective function F(x) gets the minimum value; The gas diffusion process is simulated and compared with the actual data to obtain the simulation results with the smallest error, and finally the spatial location and source strength of the gas leakage source are determined.

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