A GIS-based heat supply main pipeline leakage detection system

Abstract

The application relates to the technical field of heat supply pipeline leakage detection, in particular to a GIS-based heat supply main pipeline leakage detection system. The system comprises a central control unit, a pipe network simulation model is established according to a heat supply main pipeline, a plurality of monitoring areas are generated according to the pipe network simulation model, and a plurality of monitoring nodes are arranged in the monitoring areas; a monitoring unit is connected with the central control unit through wireless signals, the monitoring unit comprises a plurality of monitoring modules, the monitoring modules are arranged at the monitoring nodes of the heat supply main pipeline, and the monitoring modules are used for collecting operation data of the monitoring nodes; and a patrol unit is connected with the central control unit through wireless signals, and the patrol unit is used for collecting infrared image data of the monitoring areas. By additionally arranging a GIS module, the node data of the heat supply main pipeline is utilized to establish a pipe network simulation model, so that the positions of various pipe sections can be quickly located, the leakage states of the pipe sections are monitored according to real-time operation parameters of the nodes, and timely early warning is realized. The safety operation of the pipe network is guaranteed.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of heat supply pipeline leakage detection, in particular to a GIS-based heat supply main pipeline leakage detection system. BACKGROUND

[0002] With the rapid development of cities, heat supply pipelines are almost distributed in the entire city underground. Once leakage occurs, great personnel and property losses will be caused. The leakage of steam heat supply pipeline network is not easy to know, and the leakage detection along the pipeline by using inspection equipment is an important means to ensure the safe operation of the pipeline network.

[0003] At present, when recording position information of a leakage point and the like, the position information is often described by relying on a reference object and associated with the pipeline by relying on human searching, and accurate positioning of the position information of the leakage point and the like is lacked; the position information of the concentration information detected in the inspection process cannot be accurately matched, so that the detection accuracy is low. SUMMARY

[0004] The application aims to solve the above technical problems, and provides a GIS-based heat supply main pipeline leakage detection system.

[0005] In some embodiments of the application, a GIS module is additionally arranged, a pipeline network simulation model is established by using node data of the heat supply main pipeline, the positions of various pipe sections are quickly located, the leakage state of the pipe sections is monitored according to real-time operation parameters of the nodes, and timely early warning is performed, so as to ensure the safe operation of the pipeline network.

[0006] In some embodiments of the application, an inspection unit is additionally arranged, an unmanned aerial vehicle is used to inspect the heat supply main pipeline, thermal imaging is used to analyze the leakage of the heat supply main pipeline, a primary inspection unmanned aerial vehicle is used to perform routine inspection, the leakage state of the pipe sections is monitored, and timely early warning is performed. A secondary inspection unmanned aerial vehicle is arranged to inspect the leaked pipe sections, the leakage points are quickly located, and the inspection accuracy is improved.

[0007] In some embodiments of the application, a GIS-based heat supply main pipeline leakage detection system is provided, which comprises:

[0008] A central control unit, which establishes a pipeline network simulation model according to a heat supply main pipeline, generates a plurality of monitoring areas according to the pipeline network simulation model, and is provided with a plurality of monitoring nodes in the monitoring areas;

[0009] A monitoring unit, which is connected with the central control unit through a wireless signal, comprises a plurality of monitoring modules, the monitoring modules are arranged at the monitoring nodes of the heat supply main pipeline, and the monitoring modules are used to collect operation data of the monitoring nodes;

[0010] The patrol unit is connected with the central control unit through wireless signals, and is configured to collect infrared image data of the monitoring area.

[0011] In some embodiments of the present application, the central control unit comprises:

[0012] The first processing module is configured to set a plurality of monitoring nodes according to a steam trap of the heat supply main pipeline.

[0013] The second processing module is configured to set the number of monitoring nodes b of a single monitoring area according to the total number a of monitoring nodes, and is further configured to generate a plurality of monitoring areas according to the number b of monitoring nodes and the position data of the monitoring nodes.

[0014] In some embodiments of the present application, the first processing module is further configured to:

[0015] establish a heat supply demand-node steam flow simulation model;

[0016] generate the expected steam flow of each monitoring node according to the heat supply demand-node steam flow simulation model.

[0017] In some embodiments of the present application, the central control unit further comprises:

[0018] The third processing module is configured to acquire the real-time steam flow of each monitoring node, and determine whether the current monitoring node is an abnormal node according to the real-time steam flow and the expected steam flow.

[0019] If the real-time steam flow is less than the expected steam flow, the third processing module generates a flow difference value and sets the abnormal level of the current monitoring node according to the flow difference value.

[0020] In some embodiments of the present application, when setting the abnormal level of the current monitoring node according to the flow difference value, the method comprises:

[0021] a preset flow difference value matrix C is set, C(C1, C2, C3), wherein C1 is a preset first flow difference value, C2 is a preset second flow difference value, and C3 is a preset third flow difference value, and C1

[0022] acquire the flow difference value c of the monitoring node;

[0023] If C1

[0024] If C2

[0025] If c>C3, the third processing module sets the current monitoring node as a third-level abnormal node.

[0026] In some embodiments of the present application, the second processing module is further configured to:

[0027] a preset total number of monitoring nodes matrix A is set as A (A1, A2, A3, A4), wherein A1 is a preset first total number of monitoring nodes, A2 is a preset second total number of monitoring nodes, A3 is a preset third total number of monitoring nodes, and A4 is a preset fourth total number of monitoring nodes, and A1

[0028] The second processing module is further configured to preset a monitoring node number B, and set B (B1, B2, B3, B4), wherein B1 is a preset first monitoring node number, B2 is a preset second monitoring node number, B3 is a preset third monitoring node number, and B4 is a preset fourth monitoring node number, and B1

[0029] The second processing module is further configured to obtain a total number of monitoring nodes a;

[0030] If A1

[0031] If A2

[0032] If A3

[0033] If a

[0034] In some embodiments of the present application, the central control unit further comprises:

[0035] a GIS module configured to establish a pipe network simulation model according to position data of the heat supply main pipeline;

[0036] a first control module configured to generate a monitoring area evaluation value according to the monitoring area parameters, and generate a regular inspection parameter according to the monitoring area evaluation value;

[0037] The first control module is further configured to:

[0038] generate a monitoring area main pipeline length, a monitoring area heat user level, and a historical leakage number according to the monitoring area parameters;

[0039] The first control module is further configured to generate a main pipeline evaluation value d1 according to the monitoring area main pipeline length, and generate a heat user evaluation value b2 according to the monitoring area heat user level.

[0040] The first control module is further configured to generate a compensation coefficient m according to the historical number of leaks;

[0041] generate a monitoring area evaluation value d;

[0042] d = m (n1 * d1 + n2 * d2), wherein n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1 + n2 = 1.

[0043] In some embodiments of the present application, the inspection unit comprises:

[0044] The first control module sets a regular inspection time node and a single inspection time for each monitoring area according to the monitoring area evaluation value and the number of first-level inspection unmanned aerial vehicles.

[0045] The correction module sets the number of second-level inspection unmanned aerial vehicles according to the number of monitoring areas.

[0046] In some embodiments of the present application, the central control unit further comprises:

[0047] The second control module is configured to obtain all abnormal nodes of the monitoring area and generate an inspection instruction.

[0048] The second control module is further configured to set the working parameters of the second-level inspection unmanned aerial vehicles according to the inspection instruction.

[0049] In some embodiments of the present application, when generating the inspection instruction, the following steps are included:

[0050] determine whether there is a third-level abnormal node in the monitoring area;

[0051] When there is a third-level abnormal node in the monitoring area, the second control module generates a first-level inspection instruction;

[0052] When there is no third-level abnormal node in the monitoring area, obtain the number f1 of second-level abnormal nodes of the monitoring area;

[0053] preset a second-level abnormal node number threshold f2;

[0054] If the number f1 of second-level abnormal nodes is greater than the second-level abnormal node number threshold f2, generate a second-level inspection instruction;

[0055] If the number f1 of second-level abnormal nodes is less than the second-level abnormal node number threshold f2, obtain the total number f3 of abnormal nodes;

[0056] preset a total abnormal node threshold f4;

[0057] If the total number of abnormal nodes f3 is greater than the total number of abnormal node threshold f4, a third-level inspection instruction is generated.

[0058] If the total number of abnormal nodes f3 is less than the total number of abnormal node threshold f4, no inspection instruction is generated.

[0059] Compared with the prior art, the GIS-based heat supply main pipeline leakage detection system has the beneficial effects that:

[0060] By adding a GIS module, a pipe network simulation model is established by using node data of the heat supply main pipeline, so as to quickly locate the positions of each pipe section, and the leakage state of the pipe section is monitored according to real-time operation parameters of the node, and timely early warning is performed, thereby ensuring safe operation of the pipe network.

[0061] By adding an inspection unit, the heat supply main pipeline is inspected by using a UAV, the heat supply main pipeline is analyzed for leakage by using thermal imaging, the leakage state of the pipe section is monitored by using a first-level inspection UAV for routine inspection, and timely early warning is performed. A second-level inspection UAV is arranged to inspect the leaked pipe section, the leakage point is quickly located, and the inspection accuracy is improved. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 is a structure schematic diagram of a GIS-based heat supply main pipeline leakage detection system in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0063] The specific embodiments of the present application will be further described in detail below in combination with the drawings and embodiments. The following embodiments are used to illustrate the present application, but not to limit the scope of the present application.

[0064] In the description of the present application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements indicated must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0065] The terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, the meaning of "a plurality of" is two or more.

[0066] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0067] like Figure 1 As shown in the preferred embodiment of this application, a GIS-based main heating pipeline leakage detection system includes:

[0068] The central control unit establishes a pipeline simulation model based on the main heating pipeline, generates multiple monitoring areas based on the pipeline simulation model, and sets multiple monitoring nodes within each monitoring area;

[0069] The monitoring unit is connected to the central control unit via wireless signal. The monitoring unit includes multiple monitoring modules, which are set at the monitoring nodes of the main heating pipeline. The monitoring modules are used to collect the operating data of the monitoring nodes.

[0070] The inspection unit is connected to the central control unit via wireless signal and is used to collect infrared image data of the monitored area.

[0071] Specifically, the central control unit includes:

[0072] The first processing module acquires the drain valves of the main heating pipeline and sets multiple monitoring nodes based on the drain valves.

[0073] The second processing module sets the number of monitoring nodes b in a single monitoring area based on the total number of monitoring nodes a. The second processing module is also used to generate multiple monitoring areas based on the number of monitoring nodes b and the location data of the monitoring nodes.

[0074] Specifically, the inspection unit is preferably a drone capable of collecting infrared data, and the monitoring unit is used to collect steam flow data of the nodes.

[0075] It is understandable that in the above embodiments, by establishing multiple monitoring areas and utilizing the node data of the main heating pipeline, a pipeline simulation model is built to quickly locate the position of each pipe segment. Simultaneously, by establishing multiple monitoring areas, the main heating pipeline is monitored in zones, thereby improving monitoring efficiency and providing timely early warnings, ensuring the safe operation of the pipeline network.

[0076] In a preferred embodiment of this application, the first processing module is further configured to:

[0077] Establish a simulation model of heating demand-node steam flow;

[0078] generate the expected steam flow of each monitoring node according to the heat demand-node steam flow simulation model.

[0079] Specifically, the central control unit further comprises:

[0080] The third processing module is configured to acquire real-time steam flow of each monitoring node, and determine whether the current monitoring node is an abnormal node according to the real-time steam flow and the expected steam flow.

[0081] If the real-time steam flow is less than the expected steam flow, the third processing module generates a flow difference value and sets an abnormal level of the current monitoring node according to the flow difference value.

[0082] Specifically, the heat demand-node steam flow simulation model is established according to historical operation data. Thus, the steam flow of each node position is monitored, the leakage state of the pipe section is monitored, early warning is made in time, and the safe operation of the pipe network is ensured.

[0083] Specifically, when the abnormal level of the current monitoring node is set according to the flow difference value, the following steps are included:

[0084] A preset flow difference value matrix C is set, and C (C1, C2, C3) is set, wherein C1 is a preset first flow difference value, C2 is a preset second flow difference value, and C3 is a preset third flow difference value, and C1 < C2 < C3.

[0085] The flow difference value c of the monitoring node is acquired.

[0086] If C1 < c < C2, the third processing module sets the current monitoring node as a first abnormal node.

[0087] If C2 < c < C3, the third processing module sets the current monitoring node as a second abnormal node.

[0088] If c > C3, the third processing module sets the current monitoring node as a third abnormal node.

[0089] Specifically, according to the leakage risk, the risk of the pipe section between the third abnormal nodes is higher than that between the second abnormal nodes and that between the first abnormal nodes.

[0090] Specifically, the risk pipe section is determined according to the abnormal node, and the risk pipe section of the abnormal node is the gas inlet pipe section of the abnormal node.

[0091] Specifically, by establishing the flow difference value matrix, the node abnormal level is set according to the flow difference value, the leakage pipe section is located according to the abnormal node, the leakage point is located in time by the second inspection unmanned aerial vehicle, the inspection efficiency is improved, the inspection cost is reduced, and the inspection accuracy is improved.

[0092] In the preferred embodiment of the present application, the second processing module is further configured to:

[0093] A matrix A is set to the total number of monitoring nodes, and A(A1, A2, A3, A4) is defined, where A1 is the total number of the first monitoring nodes, A2 is the total number of the second monitoring nodes, A3 is the total number of the third monitoring nodes, and A4 is the total number of the fourth monitoring nodes, and A1 < A2 < A3 < A4.

[0094] The second processing module is also used to preset the number of monitoring nodes B, and set B(B1, B2, B3, B4), where B1 is the preset first number of monitoring nodes, B2 is the preset second number of monitoring nodes, B3 is the preset third number of monitoring nodes, B4 is the preset fourth number of monitoring nodes, and B1 < B2 < B3 < B4.

[0095] The second processing module is also used to obtain the total number of monitoring nodes, a.

[0096] If A1 < a < A2, set the number of monitoring nodes b in a single monitoring area to the preset first number of monitoring nodes B1, that is, b = B1;

[0097] If A2 < a < A3, set the number of monitoring nodes b in a single monitoring area to the preset number of second monitoring nodes B2, that is, b = B2;

[0098] If A3 < a < A4, set the number of monitoring nodes b in a single monitoring area to the preset number of third monitoring nodes B3, that is, b = B3;

[0099] If a > A4, the number of monitoring nodes b in a single monitoring area is set to the preset number of fourth monitoring nodes B4, i.e., b = B4.

[0100] It is understood that in the above embodiments, by setting a matrix of the total number of monitoring nodes and the number of monitoring nodes, and by dynamically adjusting the number of monitoring nodes in a single monitoring area, multiple monitoring areas are set up to perform zoned monitoring of the main heating pipeline, thereby improving monitoring efficiency and providing timely early warnings. This ensures the safe operation of the pipeline network.

[0101] In a preferred embodiment of this application, the central control unit further includes:

[0102] The GIS module establishes a pipeline simulation model based on the location data of the main heating pipeline.

[0103] The first control module generates a monitoring area evaluation value based on the monitoring area parameters, and generates routine inspection parameters based on the monitoring area evaluation value.

[0104] The first control module is also used for;

[0105] Generate the main pipeline length of the monitoring area, the heat user level of the detection area, and the number of historical leaks based on the parameters of the monitoring area;

[0106] The first control module is further configured to generate a main pipe evaluation value d1 according to a length of a main pipe in the monitoring area, and generate a heat user evaluation value b2 according to a heat user level in the monitoring area;

[0107] The first control module is further configured to generate a compensation coefficient m according to a historical leakage frequency;

[0108] The monitoring area evaluation value d is generated.

[0109] d = m (n1 * d1 + n2 * d2), wherein n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1 + n2 = 1.

[0110] Specifically, the inspection unit comprises:

[0111] The first control module sets a regular inspection time node and a single inspection time of each monitoring area according to the monitoring area evaluation value and the number of the first-level inspection unmanned aerial vehicles.

[0112] Specifically, for different monitoring areas, infrared image data of a heating main pipe in the monitoring area is collected by using an unmanned aerial vehicle to perform regular inspection. The regular inspection time node can be comprehensively set according to the number of the monitoring areas and the number of the unmanned aerial vehicles.

[0113] The correction module sets the number of the second-level inspection unmanned aerial vehicles according to the number of the monitoring areas.

[0114] Specifically, the second-level inspection unmanned aerial vehicle is selected from the first-level inspection unmanned aerial vehicles without a regular inspection task.

[0115] The second control module is configured to obtain all abnormal nodes of the monitoring area and generate an inspection instruction.

[0116] The second control module is further configured to set working parameters of the second-level inspection unmanned aerial vehicle according to the inspection instruction.

[0117] Specifically, when the inspection instruction is generated, the following steps are included:

[0118] It is determined whether there is a third-level abnormal node in the monitoring area.

[0119] When there is a third-level abnormal node in the monitoring area, the second control module generates a first-level inspection instruction.

[0120] When there is no third-level abnormal node in the monitoring area, the number f1 of second-level abnormal nodes of the monitoring area is obtained.

[0121] A preset second-level abnormal node threshold f2 is set.

[0122] If the number of secondary abnormal nodes f1 is greater than the threshold f2, a secondary inspection instruction is generated.

[0123] If the number of secondary abnormal nodes f1 is less than the threshold f2, the total number of abnormal nodes f3 is obtained.

[0124] A preset total number of abnormal nodes threshold f4 is set.

[0125] If the total number of abnormal nodes f3 is greater than the threshold f4, a tertiary inspection instruction is generated.

[0126] If the total number of abnormal nodes f3 is less than the threshold f4, no inspection instruction is generated.

[0127] Specifically, the primary inspection instruction refers to selecting an abnormal area according to an abnormal node and immediately performing inspection by a secondary inspection unmanned aerial vehicle to determine a leakage point in time for repair. The secondary inspection instruction refers to selecting an abnormal area according to an abnormal node and performing secondary inspection by a secondary inspection unmanned aerial vehicle after a primary inspection unmanned aerial vehicle completes regular inspection to determine whether there is a leakage point. The tertiary inspection instruction refers to selecting an abnormal area according to an abnormal node and performing regular inspection by a primary inspection unmanned aerial vehicle in turn to determine whether there is a leakage point.

[0128] According to the first concept of the present application, by adding a GIS module, a pipe network simulation model is established by using node data of a heat supply main pipeline to quickly locate the positions of each pipe section, and the leakage state of the pipe section is monitored according to real-time operating parameters of the node to timely warn and ensure safe operation of the pipe network.

[0129] According to the second concept of the present application, by adding an inspection unit, a heat supply main pipeline is inspected by an unmanned aerial vehicle, and the heat supply main pipeline is analyzed for leakage by thermal imaging. Regular inspection is performed by a primary inspection unmanned aerial vehicle to monitor the leakage state of the pipe section and timely warn. A secondary inspection unmanned aerial vehicle is set to inspect the leakage pipe section to quickly locate the leakage point and improve the inspection accuracy.

[0130] The above only describes the preferred embodiments of the present application. It should be noted that for those skilled in the art, without departing from the technical principles of the present application, a number of improvements and replacements can be made, which should also be considered as the protection scope of the present application.

Claims

1. A GIS-based heat supply main line leak detection system, characterized in that, The application relates to a heat supply monitoring system, which comprises the following parts: a central control unit, which establishes a pipe network simulation model according to a heat supply main pipeline, generates a plurality of monitoring areas according to the pipe network simulation model, and sets a plurality of monitoring nodes in the monitoring areas; a monitoring unit, which is connected with the central control unit through wireless signals, comprises a plurality of monitoring modules, and is arranged at the monitoring nodes of the heat supply main pipeline, wherein the monitoring modules are used for collecting operation data of the monitoring nodes; an inspection unit, which is connected with the central control unit through wireless signals, and is used for collecting infrared image data of the monitoring areas; the central control unit comprises the following parts: a first processing module, which acquires drain valve data of the heat supply main pipeline, sets a plurality of monitoring nodes according to the drain valve data; a second processing module, which sets the number of monitoring nodes b of a single monitoring area according to the total number a of monitoring nodes, and is further used for generating a plurality of monitoring areas according to the number b of monitoring nodes and position data of the monitoring nodes; a GIS module, which establishes a pipe network simulation model according to position data of the heat supply main pipeline; a first control module, which generates a monitoring area evaluation value according to monitoring area parameters, and generates a regular inspection parameter according to the monitoring area evaluation value; and a third processing module, which is used for acquiring real-time steam flow of each monitoring node, judging whether the current monitoring node is an abnormal node according to the real-time steam flow and expected steam flow, generating a flow difference value and setting an abnormal level of the current monitoring node according to the flow difference value if the real-time steam flow is smaller than the expected steam flow; the inspection unit comprises a plurality of first-level inspection unmanned aerial vehicles, the first control module sets a regular inspection time node and a single inspection time of each monitoring area according to the monitoring area evaluation value and the number of the first-level inspection unmanned aerial vehicles, and a correction module sets the number of second-level inspection unmanned aerial vehicles according to the number of the monitoring areas; the central control unit further comprises a second control module, which is used for acquiring all abnormal nodes of the monitoring areas and generating an inspection instruction, and is further used for setting working parameters of the second-level inspection unmanned aerial vehicles according to the inspection instruction; the first processing module is further used for establishing a heat supply demand-node steam flow simulation model, and generating expected steam flow of each monitoring node according to the heat supply demand-node steam flow simulation model.

2. The GIS-based heat supply main line leak detection system as claimed in claim 1, characterized in that, When the abnormal level of the current monitoring node is set according to the flow difference value, the following steps are included: a preset flow difference matrix C is set as C (C1, C2, C3), wherein C1 is a preset first flow difference value, C2 is a preset second flow difference value, and C3 is a preset third flow difference value, and C1 < C2 < C3; a flow difference value c of the monitoring node is acquired; if C1 < c < C2, the third processing module sets the current monitoring node as a first-level abnormal node; if C2 < c < C3, the third processing module sets the current monitoring node as a second-level abnormal node; if c > C3, the third processing module sets the current monitoring node as a third-level abnormal node.

3. The GIS-based heat supply main line leak detection system as claimed in claim 2, characterized in that, the second processing module is further used for: A total number of preset monitoring nodes is set as a matrix A, and A (A1, A2, A3, A4) is set, wherein A1 is a preset first total number of monitoring nodes, A2 is a preset second total number of monitoring nodes, A3 is a preset third total number of monitoring nodes, and A4 is a preset fourth total number of monitoring nodes, and A1 < A2 < A3 < A4; The second processing module is further configured to preset a total number of monitoring nodes B, and B (B1, B2, B3, B4) is set, wherein B1 is a preset first total number of monitoring nodes, B2 is a preset second total number of monitoring nodes, B3 is a preset third total number of monitoring nodes, and B4 is a preset fourth total number of monitoring nodes, and B1 < B2 < B3 < B4; The second processing module is further configured to acquire a total number of monitoring nodes a; If A1 < a < A2, the number of monitoring nodes b of a single monitoring area is set as the preset first number of monitoring nodes B1, that is, b = B1; If A2 < a < A3, the number of monitoring nodes b of a single monitoring area is set as the preset second number of monitoring nodes B2, that is, b = B2; If A3 < a < A4, the number of monitoring nodes b of a single monitoring area is set as the preset third number of monitoring nodes B3, that is, b = B3; If a > A4, the number of monitoring nodes b of a single monitoring area is set as the preset fourth number of monitoring nodes B4, that is, b = B4.

4. The GIS-based heat supply main line leak detection system as claimed in claim 3, characterized in that, The first control module is further configured to: generate a monitoring area main pipeline length, a monitoring area heat user level, and a historical leakage number according to the monitoring area parameters; The first control module is further configured to generate a main pipeline evaluation value d1 according to the monitoring area main pipeline length and generate a heat user evaluation value b2 according to the monitoring area heat user level; The first control module is further configured to generate a compensation coefficient m according to the historical leakage number; generate a monitoring area evaluation value d; d = m (n1*d1 + n2*d2), wherein n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1 + n2 = 1.

5. The GIS-based heat supply main line leak detection system as claimed in claim 4, characterized in that, When generating an inspection instruction, the following steps are included: determine whether the monitoring area has a third-level abnormal node; when the monitoring area has a third-level abnormal node, the second control module generates a first-level inspection instruction; when the monitoring area does not have a third-level abnormal node, acquire a second-level abnormal node number f1 of the monitoring area; preset a second-level abnormal node number threshold f2; if the second-level abnormal node number f1 > the second-level abnormal node number threshold f2, generate a second-level inspection instruction; if the second-level abnormal node number f1 < the second-level abnormal node number threshold f2, acquire a total number of abnormal nodes f3; preset an abnormal node total quantity threshold f4; if the total number of abnormal nodes f3 > the abnormal node total quantity threshold f4, generate a third-level inspection instruction; if the total number of abnormal nodes f3 < the abnormal node total quantity threshold f4, do not generate an inspection instruction.

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