CN117028866A - GIS-based heat supply main pipeline leakage detection system - Google Patents

Abstract

The application relates to the technical field of leakage detection of heating pipelines, in particular to a GIS-based heating main pipeline leakage detection system. Comprising the following steps: the central control unit establishes a pipe network simulation model according to the heat supply main pipeline, generates a plurality of monitoring areas according to the pipe network simulation model, and is internally provided with a plurality of monitoring nodes; the monitoring unit is connected with the central control unit through wireless signals and comprises a plurality of monitoring modules, the monitoring modules are arranged at monitoring nodes of the main heating pipeline, and the monitoring modules are used for collecting operation data of the monitoring nodes; and the inspection unit is connected with the central control unit through a wireless signal and is used for acquiring infrared image data of the monitoring area. By additionally arranging the GIS module, the node data of the main heating pipeline is utilized to establish a pipe network simulation model, so that the positions of all pipe sections are rapidly positioned, and meanwhile, the leakage state of the pipe sections is monitored and early-warned in time according to the real-time operation parameters of the nodes. The safe operation of the pipe network is ensured.

Description

GIS-based heat supply main pipeline leakage detection system

Technical Field

The application relates to the technical field of leakage detection of heating pipelines, in particular to a GIS-based heating main pipeline leakage detection system.

Background

With the rapid development of cities, heat supply pipelines are distributed almost throughout the city underground, and once leakage occurs, huge personnel and property losses are caused. The leakage condition of the steam heating pipe network is not easy to know, and the detection of leakage by using the inspection equipment is an important means for guaranteeing the safe operation of the pipe network.

At present, when the position information of the leakage point and the like is recorded, the description is often carried out by relying on a reference object, the manual search is relied on to be associated with the pipeline, and the accurate positioning of the position information of the leakage point and the like is lacking; the concentration information detected in the inspection process cannot be matched with the position information accurately, so that the detection precision is low.

Disclosure of Invention

The purpose of the application is that: in order to solve the technical problems, the application provides a heat supply main pipeline leakage detection system based on GIS.

In some embodiments of the application, a GIS module is additionally arranged, and a pipe network simulation model is built by utilizing node data of a main heating pipeline, so that the positions of all pipe sections are rapidly positioned, and meanwhile, the leakage state of the pipe sections is monitored and early-warned in time according to real-time operation parameters of the nodes. The safe operation of the pipe network is ensured.

In some embodiments of the application, the inspection unit is additionally arranged, the unmanned aerial vehicle is utilized to inspect the main heating pipeline, the thermal imaging is utilized to analyze leakage of the main heating pipeline, the primary inspection unmanned aerial vehicle is utilized to conduct conventional inspection, the leakage state of the pipe section is monitored, and early warning is timely carried out. Through setting up second grade inspection unmanned aerial vehicle, inspect revealing the pipeline section, the quick location reveals the dew point, improves inspection accuracy.

In some embodiments of the present application, there is provided a GIS-based heating main line leak detection system, comprising:

the central control unit establishes a pipe network simulation model according to a heat supply main pipeline, and generates a plurality of monitoring areas according to the pipe network simulation model, wherein a plurality of monitoring nodes are arranged in the monitoring areas;

the monitoring unit is connected with the central control unit through wireless signals and comprises a plurality of monitoring modules, the monitoring modules are arranged at monitoring nodes of the main heating pipeline, and the monitoring modules are used for collecting operation data of the monitoring nodes;

and the inspection unit is connected with the central control unit through a wireless signal and is used for collecting infrared image data of the monitoring area.

In some embodiments of the present application, the central control unit includes:

the first processing module is used for obtaining drain valves of the heating main pipeline and setting a plurality of monitoring nodes according to the drain valves;

the second processing module is used for setting the monitoring node quantity b of a single monitoring area according to the monitoring node total quantity a, and is also used for generating a plurality of monitoring areas according to the monitoring node quantity b and the position data of the monitoring nodes.

In some embodiments of the application, the first processing module is further configured to:

building a heat supply demand-node steam flow simulation model;

and generating the expected steam flow of each monitoring node according to the heat supply demand-node steam flow simulation model.

In some embodiments of the present application, the central control unit further includes:

the third processing module is used for acquiring real-time steam flow of each monitoring node and judging whether the current monitoring node is an abnormal node or not according to the real-time steam flow and the expected steam flow;

and if the real-time steam flow is smaller 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.

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 includes:

presetting a flow difference matrix C, and setting C (C1, C2 and C3), wherein C1 is a preset first flow difference, C2 is a preset second flow difference, C3 is a preset third flow difference, and C1 is less than C2 and less than C3;

acquiring a flow difference value c of a monitoring node;

if C1 is more than C and less than C2, the third processing module sets the current monitoring node as a first-level abnormal node;

if C2 is more than C and less than C3, the third processing module sets the current monitoring node as a second-level abnormal node;

if C is more than C3, the third processing module sets the current monitoring node as a three-level abnormal node.

In some embodiments of the application, the second processing module is further configured to:

presetting a total number matrix A of monitoring nodes, and setting A (A1, A2, A3 and A4), wherein A1 is the total number of preset first monitoring nodes, A2 is the total number of preset second monitoring nodes, A3 is the total number of preset third monitoring nodes, A4 is the total number of preset fourth monitoring nodes, and A1 is more than A2 and less than A3 and less than A4;

the second processing module is further configured to preset a number of monitoring nodes B, and set B (B1, B2, B3, B4), wherein B1 is a preset first number of monitoring nodes, B2 is a preset second number of monitoring nodes, B3 is a preset third number of monitoring nodes, B4 is a preset fourth number of monitoring nodes, and B1 is greater than B2 and less than B3 is greater than B4;

the second processing module is further used for acquiring the total number a of the monitoring nodes;

if A1 is less than a < A2, setting the number B of monitoring nodes in a single monitoring area as a preset first monitoring node number B1, namely b=b1;

if A2 is less than a < A3, setting the number B of monitoring nodes in the single monitoring area as a preset second monitoring node number B2, namely b=b2;

if A3 is less than a < A4, setting the number B of the monitoring nodes of the single monitoring area as a preset third monitoring node number B3, namely b=b3;

if a > A4, the number B of monitoring nodes in the single monitoring area is set to be the preset fourth number B4 of monitoring nodes, i.e. b=b4.

In some embodiments of the present application, the central control unit further includes:

the GIS module is used for establishing a pipe network simulation model according to the position data of the main heating pipeline;

the first control module generates a monitoring area evaluation value according to the monitoring area parameter and generates a conventional inspection parameter according to the monitoring area evaluation value;

the first control module is also used for;

generating the length of a main pipeline of the monitoring area according to the monitoring area parameters, and detecting the heat user grade and the historical leakage times of the area;

the first control module is further used for generating a main pipeline evaluation value d1 according to the main pipeline length of the monitoring area and generating a heat user rating value b2 according to the heat user grade of the monitoring area;

the first control module is further used for generating a compensation coefficient m according to the historical leakage times;

generating a monitoring area evaluation value d;

d=m (n1+n2+d2), where n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1+n2=1.

In some embodiments of the application, the inspection unit comprises:

the first control module sets the conventional inspection time nodes and single inspection time of each monitoring area according to the evaluation values of the monitoring areas and the number of the first inspection unmanned aerial vehicles;

and the correction module is used for setting the number of the secondary inspection unmanned aerial vehicles according to the number of the monitoring areas.

In some embodiments of the present application, the central control unit further includes:

the second control module is used for acquiring all abnormal nodes of the monitoring area and generating a patrol instruction;

the second control module is also used for setting working parameters of the secondary inspection unmanned aerial vehicle according to the inspection instruction.

In some embodiments of the present application, when generating the inspection instruction, the method includes:

judging whether a three-level abnormal node exists in the monitoring area;

when the monitoring area has three-level abnormal nodes, the second control module generates a first-level inspection instruction;

when the monitoring area does not have the three-level abnormal nodes, acquiring the number f1 of the two-level abnormal nodes of the monitoring area;

presetting a threshold f2 of the number of the second-level abnormal nodes;

if the number f1 of the second-level abnormal nodes is greater than the threshold f2 of the number of the second-level abnormal nodes, generating a second-level inspection instruction;

if the number f1 of the second-level abnormal nodes is smaller than the threshold f2 of the second-level abnormal nodes, obtaining the total number f3 of the abnormal nodes;

presetting an abnormal node total amount threshold f4;

if the total number f3 of the abnormal nodes is greater than the total number threshold f4 of the abnormal nodes, generating a three-level inspection instruction;

if the total number f3 of the abnormal nodes is smaller than the total number threshold f4 of the abnormal nodes, no patrol instruction is generated.

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

by additionally arranging the GIS module, the node data of the main heating pipeline is utilized to establish a pipe network simulation model, so that the positions of all pipe sections are rapidly positioned, and meanwhile, the leakage state of the pipe sections is monitored and early-warned in time according to the real-time operation parameters of the nodes. The safe operation of the pipe network is ensured.

Through addding the unit of patrolling and examining, utilize unmanned aerial vehicle to patrol and examine the heat supply main pipeline, utilize thermal imaging to reveal the analysis to the heat supply main pipeline, patrol and examine unmanned aerial vehicle through the one-level and carry out conventional inspection, monitor the state of revealing of pipeline section, in time early warning. Through setting up second grade inspection unmanned aerial vehicle, inspect revealing the pipeline section, the quick location reveals the dew point, improves inspection accuracy.

Drawings

Fig. 1 is a schematic structural diagram of a GIS-based main heating pipeline leakage detection system according to a preferred embodiment of the present application.

Detailed Description

The following describes in further detail the embodiments of the present application with reference to the drawings and examples. The following examples are illustrative of the application and are not intended to limit the scope of the application.

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 orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present application and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present application.

The terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. In the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.

In the description of the present application, it should be noted that, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be either fixedly connected, detachably connected, or integrally connected, for example; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present application will be understood in specific cases by those of ordinary skill in the art.

As shown in fig. 1, a GIS-based heating main pipeline leakage detection system according to a preferred embodiment of the present application includes:

the central control unit establishes a pipe network simulation model according to the heat supply main pipeline, generates a plurality of monitoring areas according to the pipe network simulation model, and is internally provided with a plurality of monitoring nodes;

the monitoring unit is connected with the central control unit through wireless signals and comprises a plurality of monitoring modules, the monitoring modules are arranged at monitoring nodes of the main heating pipeline, and the monitoring modules are used for collecting operation data of the monitoring nodes;

and the inspection unit is connected with the central control unit through a wireless signal and is used for acquiring infrared image data of the monitoring area.

Specifically, the central control unit includes:

the first processing module is used for obtaining drain valves of the main heating pipeline and setting a plurality of monitoring nodes according to the drain valves;

the second processing module is used for setting the monitoring node number b of the single monitoring area according to the monitoring node total number a, and generating a plurality of monitoring areas according to the monitoring node number b and the position data of the monitoring nodes.

Specifically, the inspection unit is preferably an unmanned aerial vehicle capable of acquiring infrared data, and the monitoring unit is used for acquiring steam flow data of the nodes.

It can be appreciated that in the above embodiment, by establishing a plurality of monitoring areas and using the node data of the main heating pipeline, a pipe network simulation model is established, so that the positions of each pipe section are rapidly positioned, and meanwhile, by establishing a plurality of monitoring areas, the main heating pipeline is monitored in a partitioning manner, so that the monitoring efficiency is improved, and early warning is timely performed. The safe operation of the pipe network is ensured.

In a preferred embodiment of the present application, the first processing module is further configured to:

building a heat supply demand-node steam flow simulation model;

and generating the expected steam flow of each monitoring node according to the heat supply demand-node steam flow simulation model.

Specifically, the central control unit further includes:

the third processing module is used for acquiring the real-time steam flow of each monitoring node and judging whether the current monitoring node is an abnormal node according to the real-time steam flow and the expected steam flow;

if the real-time steam flow is smaller than the expected steam flow, the third processing module generates a flow difference value and sets the abnormal grade of the current monitoring node according to the flow difference value.

Specifically, a heating demand-node steam flow simulation model is established according to historical operation data. Therefore, the steam flow of each node position is monitored, the leakage state of the pipe section is monitored, early warning is timely carried out, and the safe operation of the pipe network is ensured.

Specifically, when setting the abnormal level of the current monitoring node according to the flow difference value, the method includes:

presetting a flow difference matrix C, and setting C (C1, C2 and C3), wherein C1 is a preset first flow difference, C2 is a preset second flow difference, C3 is a preset third flow difference, and C1 is less than C2 and less than C3;

acquiring a flow difference value c of a monitoring node;

if C1 is more than C and less than C2, the third processing module sets the current monitoring node as a first-level abnormal node;

if C2 is more than C and less than C3, the third processing module sets the current monitoring node as a second-level abnormal node;

if C is more than C3, the third processing module sets the current monitoring node as a three-level abnormal node.

Specifically, the pipe segment risk between the three-level abnormal nodes is higher than the pipe segment between the two-level abnormal nodes than the pipe segment between the one-level abnormal nodes according to the leakage risk thereof.

Specifically, a risk pipe section is determined according to the abnormal node, and the risk pipe section is an abnormal node gas inlet pipe section.

Specifically, through establishing flow difference matrix, set up the unusual grade of node according to its flow difference to reveal the pipeline section according to unusual node location, in time fix a position the point of revealing through second grade inspection unmanned aerial vehicle, improve and patrol and examine efficiency, reduce and patrol and examine the cost, improve and patrol and examine the precision.

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

presetting a total number matrix A of monitoring nodes, and setting A (A1, A2, A3 and A4), wherein A1 is the total number of preset first monitoring nodes, A2 is the total number of preset second monitoring nodes, A3 is the total number of preset third monitoring nodes, A4 is the total number of preset fourth monitoring nodes, and A1 is more than A2 and less than A3 and less than A4;

the second processing module is further configured to preset a number of monitoring nodes B, and set B (B1, B2, B3, B4), wherein B1 is a preset first number of monitoring nodes, B2 is a preset second number of monitoring nodes, B3 is a preset third number of monitoring nodes, B4 is a preset fourth number of monitoring nodes, and B1 is greater than B2 and less than B3 is greater than B4;

the second processing module is also used for acquiring the total number a of the monitoring nodes;

if A1 is less than a < A2, setting the number B of monitoring nodes in a single monitoring area as a preset first monitoring node number B1, namely b=b1;

if A2 is less than a < A3, setting the number B of monitoring nodes in the single monitoring area as a preset second monitoring node number B2, namely b=b2;

if A3 is less than a < A4, setting the number B of the monitoring nodes of the single monitoring area as a preset third monitoring node number B3, namely b=b3;

if a > A4, the number B of monitoring nodes in the single monitoring area is set to be the preset fourth number B4 of monitoring nodes, i.e. b=b4.

It can be appreciated that in the above embodiment, by setting the total number matrix of the monitoring nodes and the number of the monitoring nodes, and dynamically adjusting the number of the monitoring nodes in a single monitoring area, a plurality of monitoring areas are set, so that the main heating pipeline is monitored in a partitioned manner, the monitoring efficiency is improved, and early warning is timely performed. The safe operation of the pipe network is ensured.

In a preferred embodiment of the present application, the central control unit further includes:

the GIS module is used for establishing a pipe network simulation model according to the position data of the main heating pipeline;

the first control module generates a monitoring area evaluation value according to the monitoring area parameter and generates a conventional inspection parameter according to the monitoring area evaluation value;

the first control module is also used for;

generating the length of a main pipeline of the monitoring area according to the parameters of the monitoring area, and detecting the heat user grade and the historical leakage times of the area;

the first control module is further used for generating a main pipeline evaluation value d1 according to the main pipeline length of the monitoring area and generating a heat user rating value b2 according to the heat user grade of the monitoring area;

the first control module is also used for generating a compensation coefficient m according to the historical leakage times;

generating a monitoring area evaluation value d;

d=m (n1+n2+d2), where n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1+n2=1.

Specifically, the inspection unit includes:

the first control module sets the conventional inspection time nodes and single inspection time of each monitoring area according to the evaluation values of the monitoring areas and the number of the first inspection unmanned aerial vehicles;

specifically, aiming at different monitoring areas, the unmanned aerial vehicle is utilized to collect infrared image data of a heating main pipeline of the monitoring area, and conventional inspection is carried out. The conventional inspection time nodes can be comprehensively set according to the number of the monitoring areas and the number of unmanned aerial vehicles.

And the correction module is used for setting the number of the secondary inspection unmanned aerial vehicles according to the number of the monitoring areas.

Specifically, the secondary inspection unmanned aerial vehicle is selected from the primary inspection unmanned aerial vehicles without conventional inspection tasks.

The second control module is used for acquiring all abnormal nodes of the monitoring area and generating a patrol instruction;

the second control module is also used for setting working parameters of the secondary inspection unmanned aerial vehicle according to the inspection instruction.

Specifically, when generating the inspection instruction, the method includes:

judging whether a three-level abnormal node exists in the monitoring area;

when the monitoring area has three-level abnormal nodes, the second control module generates a first-level inspection instruction;

when the monitoring area does not have the three-level abnormal nodes, acquiring the number f1 of the two-level abnormal nodes of the monitoring area;

presetting a threshold f2 of the number of the second-level abnormal nodes;

if the number f1 of the second-level abnormal nodes is greater than the threshold f2 of the number of the second-level abnormal nodes, generating a second-level inspection instruction;

if the number f1 of the second-level abnormal nodes is smaller than the threshold f2 of the second-level abnormal nodes, obtaining the total number f3 of the abnormal nodes;

presetting an abnormal node total amount threshold f4;

if the total number f3 of the abnormal nodes is greater than the total number threshold f4 of the abnormal nodes, generating a three-level inspection instruction;

if the total number f3 of the abnormal nodes is smaller than the total number threshold f4 of the abnormal nodes, no patrol instruction is generated.

Specifically, the first-level inspection instruction refers to selecting an abnormal area according to an abnormal node, immediately utilizing the second-level inspection unmanned aerial vehicle to carry out inspection, and timely determining a leakage point for overhauling. The second-level inspection instruction is to select an abnormal area according to the abnormal node, and after the corresponding first-level inspection unmanned aerial vehicle completes conventional inspection, the second-level inspection unmanned aerial vehicle performs inspection again, so that whether the leakage point exists or not is determined. The third-level inspection instruction refers to selecting an abnormal area according to an abnormal node, and performing orderly conventional inspection by the first-level inspection unmanned aerial vehicle, so as to judge whether a leakage point exists.

According to the first conception of the application, by adding the GIS module and utilizing the node data of the main heating pipeline, a pipe network simulation model is established, so that the positions of all pipe sections are rapidly positioned, and meanwhile, the leakage state of the pipe sections is monitored and early-warned in time according to the real-time operation parameters of the nodes. The safe operation of the pipe network is ensured.

According to the second conception of the application, the inspection unit is additionally arranged, the unmanned aerial vehicle is utilized to inspect the main heating pipeline, the thermal imaging is utilized to analyze leakage of the main heating pipeline, the primary inspection unmanned aerial vehicle is utilized to conduct conventional inspection, the leakage state of the pipe section is monitored, and early warning is timely carried out. Through setting up second grade inspection unmanned aerial vehicle, inspect revealing the pipeline section, the quick location reveals the dew point, improves inspection accuracy.

The foregoing is merely a preferred embodiment of the present application, and it should be noted that modifications and substitutions can be made by those skilled in the art without departing from the technical principles of the present application, and these modifications and substitutions should also be considered as being within the scope of the present application.

Claims (10)

1. GIS-based heating main pipeline leakage detection system, characterized by comprising:

the central control unit establishes a pipe network simulation model according to a heat supply main pipeline, and generates a plurality of monitoring areas according to the pipe network simulation model, wherein a plurality of monitoring nodes are arranged in the monitoring areas;

the monitoring unit is connected with the central control unit through wireless signals and comprises a plurality of monitoring modules, the monitoring modules are arranged at monitoring nodes of the main heating pipeline, and the monitoring modules are used for collecting operation data of the monitoring nodes;

and the inspection unit is connected with the central control unit through a wireless signal and is used for collecting infrared image data of the monitoring area.

2. The GIS-based heating main line leak detection system of claim 1, wherein the central control unit comprises:

the first processing module is used for obtaining drain valves of the heating main pipeline and setting a plurality of monitoring nodes according to the drain valves;

the second processing module is used for setting the monitoring node quantity b of a single monitoring area according to the monitoring node total quantity a, and is also used for generating a plurality of monitoring areas according to the monitoring node quantity b and the position data of the monitoring nodes.

3. The GIS-based heating main line leak detection system of claim 2, wherein the first processing module is further configured to:

building a heat supply demand-node steam flow simulation model;

and generating the expected steam flow of each monitoring node according to the heat supply demand-node steam flow simulation model.

4. A GIS-based heating main line leak detection system as defined in claim 3, wherein the central control unit further comprises:

the third processing module is used for acquiring real-time steam flow of each monitoring node and judging whether the current monitoring node is an abnormal node or not according to the real-time steam flow and the expected steam flow;

and if the real-time steam flow is smaller 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.

5. The GIS-based heating main line leak detection system as defined in claim 4, wherein when an abnormality level of a current monitoring node is set according to the flow difference value, comprising:

presetting a flow difference matrix C, and setting C (C1, C2 and C3), wherein C1 is a preset first flow difference, C2 is a preset second flow difference, C3 is a preset third flow difference, and C1 is less than C2 and less than C3;

acquiring a flow difference value c of a monitoring node;

if C1 is more than C and less than C2, the third processing module sets the current monitoring node as a first-level abnormal node;

if C2 is more than C and less than C3, the third processing module sets the current monitoring node as a second-level abnormal node;

if C is more than C3, the third processing module sets the current monitoring node as a three-level abnormal node.

6. The GIS-based heating main line leak detection system of claim 5, wherein the second processing module is further configured to:

presetting a total number matrix A of monitoring nodes, and setting A (A1, A2, A3 and A4), wherein A1 is the total number of preset first monitoring nodes, A2 is the total number of preset second monitoring nodes, A3 is the total number of preset third monitoring nodes, A4 is the total number of preset fourth monitoring nodes, and A1 is more than A2 and less than A3 and less than A4;

the second processing module is further configured to preset a number of monitoring nodes B, and set B (B1, B2, B3, B4), wherein B1 is a preset first number of monitoring nodes, B2 is a preset second number of monitoring nodes, B3 is a preset third number of monitoring nodes, B4 is a preset fourth number of monitoring nodes, and B1 is greater than B2 and less than B3 is greater than B4;

the second processing module is further used for acquiring the total number a of the monitoring nodes;

if A1 is less than a < A2, setting the number B of monitoring nodes in a single monitoring area as a preset first monitoring node number B1, namely b=b1;

if A2 is less than a < A3, setting the number B of monitoring nodes in the single monitoring area as a preset second monitoring node number B2, namely b=b2;

if A3 is less than a < A4, setting the number B of the monitoring nodes of the single monitoring area as a preset third monitoring node number B3, namely b=b3;

if a > A4, the number B of monitoring nodes in the single monitoring area is set to be the preset fourth number B4 of monitoring nodes, i.e. b=b4.

7. The GIS-based heating main line leak detection system of claim 6, wherein the central control unit further comprises:

the GIS module is used for establishing a pipe network simulation model according to the position data of the main heating pipeline;

the first control module generates a monitoring area evaluation value according to the monitoring area parameter and generates a conventional inspection parameter according to the monitoring area evaluation value;

the first control module is also used for;

generating the length of a main pipeline of the monitoring area according to the monitoring area parameters, and detecting the heat user grade and the historical leakage times of the area;

the first control module is further used for generating a main pipeline evaluation value d1 according to the main pipeline length of the monitoring area and generating a heat user rating value b2 according to the heat user grade of the monitoring area;

the first control module is further used for generating a compensation coefficient m according to the historical leakage times;

generating a monitoring area evaluation value d;

d=m (n1+n2+d2), where n1 is a preset first weight coefficient, n2 is a preset second weight coefficient, and n1+n2=1.

8. The GIS-based heating main line leak detection system of claim 7, wherein the patrol unit includes:

the first control module sets the conventional inspection time nodes and single inspection time of each monitoring area according to the evaluation values of the monitoring areas and the number of the first inspection unmanned aerial vehicles;

and the correction module is used for setting the number of the secondary inspection unmanned aerial vehicles according to the number of the monitoring areas.

9. The GIS-based heating main line leak detection system of claim 7, wherein the central control unit further comprises:

the second control module is used for acquiring all abnormal nodes of the monitoring area and generating a patrol instruction;

the second control module is also used for setting working parameters of the secondary inspection unmanned aerial vehicle according to the inspection instruction.

10. The GIS-based heating main line leak detection system of claim 9, wherein generating the patrol command comprises:

judging whether a three-level abnormal node exists in the monitoring area;

when the monitoring area has three-level abnormal nodes, the second control module generates a first-level inspection instruction;

when the monitoring area does not have the three-level abnormal nodes, acquiring the number f1 of the two-level abnormal nodes of the monitoring area;

presetting a threshold f2 of the number of the second-level abnormal nodes;

if the number f1 of the second-level abnormal nodes is greater than the threshold f2 of the number of the second-level abnormal nodes, generating a second-level inspection instruction;

if the number f1 of the second-level abnormal nodes is smaller than the threshold f2 of the second-level abnormal nodes, obtaining the total number f3 of the abnormal nodes;

presetting an abnormal node total amount threshold f4;

if the total number f3 of the abnormal nodes is greater than the total number threshold f4 of the abnormal nodes, generating a three-level inspection instruction;

if the total number f3 of the abnormal nodes is smaller than the total number threshold f4 of the abnormal nodes, no patrol instruction is generated.