Heating station meter inspection method and system based on unmanned aerial vehicle

Abstract

The invention provides a thermal station meter inspection method and system based on an unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicles, and the method specifically comprises the steps: determining an inspection target time period and an inspection processing strategy of an in-situ surface meter in an inspection processing time period based on the analysis result of the image definition of each in-situ surface meter in the inspection processing time period, and performing the on-earth-surface inspection processing in the inspection target time period by using the inspection processing strategy, and determining the on-earth-surface inspection processing method in the future on-earth-surface inspection target time period by using the on-earth-surface inspection processing result and the matching condition of the inspection processing result and the heat supply demand. And the reliability of the thermal station meter inspection processing based on the unmanned aerial vehicle is improved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of unmanned aerial vehicles, and particularly relates to a heat station meter inspection method and system based on unmanned aerial vehicles. BACKGROUND

[0002] In the prior art, the on-site meter of a heat station often lacks effective inspection means, and since it is not connected to an online monitoring platform, manual inspection is often used for inspection and processing, which not only has a large inspection delay, but also makes it difficult to accurately and timely find abnormalities in the on-site meter.

[0003] To solve the above technical problems, the unmanned aerial vehicle inspection method can be used to read and process the monitoring data of the unmanned meter, but since the unmanned aerial vehicle is used to read and process the meter monitoring data in the form of a monitoring image, the reading accuracy of the monitoring image is greatly affected by light, and the difference in the distribution position may affect the reading accuracy to some extent, so it is urgent to solve the technical problem of how to combine light data to perform meter inspection of a heat station.

[0004] To solve the above technical problems, the present application provides a heat station meter inspection method and system based on unmanned aerial vehicles. SUMMARY

[0005] To achieve the purpose of the present application, the present application adopts the following technical solutions: Specifically, the present application provides a heat station meter inspection method based on unmanned aerial vehicles, which specifically comprises: S1, determining the distribution data of the on-site meter in the heat station based on the constituent data of the monitoring meter of the heat station, and when it is determined that the on-site meter does not need to be inspected by using a preset scheme, proceeding to the next step; S2, performing inspection processing of the on-site meter of the heat station to obtain the image definition of the meter image of the on-site meter in different time periods, and determining the inspection processing time period in the time period based on the analysis result of the image definition of the meter image of the on-site meter in each time period; S3, determining the inspection target time period and the inspection processing strategy of the on-site meter in the inspection processing time period based on the analysis result of the image definition of each on-site meter in the inspection processing time period; S4, performing inspection processing of the on-site meter in the inspection target time period by using the inspection processing strategy, determining the inspection processing method of the on-site meter in the inspection target time period of the on-site meter in the future by using the inspection processing result of the on-site meter and the matching condition of the inspection processing result and the heat supply demand, and performing verification processing between different meters by using the inspection result.

[0006] The beneficial effects of the present application are: With the analysis result of the image definition of the meter image of the on-site meter in each period, the inspection processing period in the period is determined, which realizes the selection of the inspection processing period with more on-site meters with image definition meeting the requirements from the perspective of image definition of the meter image, and further combines the number of on-site meters with image definition meeting the requirements in the period with image definition meeting the requirements, thereby realizing the selection of the period with greater inspection processing demand, and improving the reliability of the inspection processing.

[0007] With the inspection processing result of the on-site meter and the matching condition of the inspection processing result and the heat supply demand, the inspection processing method of the on-site meter in the future inspection target period of the on-site meter is determined, which not only considers the influence of the reliability of the inspection processing due to the difference in image definition in the inspection processing process of the on-site inspection meter, but also further combines the matching condition of the inspection processing result and the heat supply demand, realizes the determination of the inspection processing demand of the on-site meter from the perspective of the heat supply demand, and improves the pertinence and reliability of the inspection processing.

[0008] Further, the constituent data of the monitoring meter includes the number of on-site meters and online meters.

[0009] Specifically, the on-site meter is a meter that does not perform upload processing of monitoring data.

[0010] Further, it is determined that the preset scheme is not needed for inspection processing, specifically including: With the constituent data of the on-site meter, the number of on-site meters in the heat station is determined; With the constituent data of the on-site meter in different pipes, the number of pipes with on-site meters is determined; Based on the number of pipes with on-site meters and the constituent data of the on-site meter in the pipe with on-site meters, it is determined whether the preset scheme is needed for inspection processing.

[0011] Further, the method for determining the inspection processing method of the on-site meter in the future inspection target period of the on-site meter is: With the inspection processing result of the on-site meter, the proportion of the number of inspection target periods with image definition not meeting the requirements in the historical inspection processing process of different on-site meters in the current date is determined, and it is used as the proportion of the number of on-site meters with poor image definition; Based on the matching condition of the inspection result and the heat supply demand, the on-site meter not matching the heat supply demand in the recent inspection processing process is determined, and it is used as the on-site meter with poor matching; The image poor quantity proportion of the on-site meter and the poor matching meter are used to determine the on-site meter inspection processing method of the future on-site meter inspection target period.

[0012] In a second aspect, the present application provides a computer system, comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to perform the above-mentioned unmanned aerial vehicle-based heat station meter inspection method.

[0013] Other features and advantages will be set forth in the accompanying description, and in part will be apparent from the description and the drawings, or can be learned by practice of the application as claimed herein.

[0014] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the following preferred embodiments are specifically described in detail below, and the accompanying drawings are described as follows. BRIEF DESCRIPTION OF DRAWINGS

[0015] The above-mentioned and other features and advantages of the present application will become more apparent by describing in detail example embodiments thereof with reference to the attached drawings.

[0016] Figure 1 is a flowchart of an unmanned aerial vehicle-based heat station meter inspection method; Figure 2 is a flowchart of determining that the preset scheme does not need to be used for inspection processing; Figure 3 is a flowchart of a method for determining the inspection processing period in the period. DETAILED DESCRIPTION

[0017] In order to make the technical personnel in the art better understand the technical solutions in the present application, the technical solutions in the present application will be described in detail below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor should belong to the protection scope of the present application.

[0018] Embodiment 1 As Figure 1 shown, the present application provides an unmanned aerial vehicle-based heat station meter inspection method, which specifically comprises: S1 determines the distribution data of the on-site meter in the heat station based on the constituent data of the monitored meter of the heat station, and when it is determined that the preset scheme does not need to be used for inspection processing based on the distribution data of the on-site meter, the next step is entered; S2 performs the on-site metering inspection processing of the heat station to obtain the image definition of the metering image of the on-site meter in different time periods, determines the inspection processing time period in the time period according to the analysis result of the image definition of the metering image of the on-site meter in each time period; S3 determines the inspection target time period and the inspection processing strategy of the on-site meter in the inspection processing time period according to the analysis result of the image definition of each on-site meter in the inspection processing time period; S4 performs the inspection processing of the on-site meter in the inspection target time period by using the inspection processing strategy, determines the inspection processing method of the on-site meter in the inspection target time period of the on-site meter in the future by using the inspection processing result of the on-site meter and the matching condition of the inspection processing result and the heat supply demand, and performs the verification processing between different meters by using the inspection result.

[0019] Further, the constituent data of the monitored meter includes the number of on-site meters and online meters.

[0020] Specifically, the on-site meter is a meter that does not perform uploading processing of monitoring data.

[0021] Specifically, as shown in the method for determining whether the preset scheme needs to be used for the inspection processing, the method comprises the steps of: Figure 2 determining the number of on-site meters in the heat station according to the constituent data of the on-site meter; determining the number of pipes with on-site meters according to the constituent data of the on-site meter in different pipes; determining whether the preset scheme needs to be used for the inspection processing according to the number of pipes with on-site meters and the constituent data of the on-site meter in the pipe with on-site meters. It can be understood that when the number of pipes with on-site meters is greater than the preset pipe number threshold and the number of pipes with on-site meters whose number of on-site meters is greater than the preset on-site meter number threshold does not meet the requirement, that is, the number of pipes with on-site meters whose number of on-site meters is greater than the preset on-site meter number threshold is greater than the second pipe number threshold, at this time, in order to ensure the reliable procedure of the monitoring processing of the on-site meter of the heat station, the preset scheme needs to be used for the inspection processing.

[0022] In another possible embodiment, the method for determining whether the preset scheme needs to be used for the inspection processing comprises the steps of:

[0023] determining the number of on-site meters in the heat station according to the constituent data of the on-site meter; determining the number of pipes with on-site meters according to the constituent data of the on-site meter in different pipes; determining whether the preset scheme needs to be used for the inspection processing according to the number of pipes with on-site meters and the constituent data of the on-site meter in the pipe with on-site meters. Based on the number of pipelines with on-site meters and the number of on-site meters, it is determined whether a preset scheme needs to be used for inspection processing.

[0024] It should be noted that when the number of pipelines with on-site meters is greater than the preset pipeline number threshold and the proportion of on-site meters in the heat station in all monitored meters is greater than the preset proportion threshold, it is determined that the preset scheme needs to be used for inspection processing.

[0025] Further, the on-site meter inspection processing of the heat station is performed, specifically including: All on-site meters in the heat station are inspected in different time periods, specifically, all on-site meters in the heat station are inspected every hour.

[0026] Further, the image clarity of the meter image of the on-site meter is determined according to the signal-to-noise ratio of the meter image.

[0027] Specifically, as shown in Figure 3 The method for determining the inspection processing period in the time period is: Based on the analysis result of the image clarity of the meter image of the on-site meter in each time period, the time period in which the image clarity of the meter image of the on-site meter meets the requirement is determined as the matching inspection time period of the on-site meter; According to the on-site meter belonging to the matching inspection time period in the time period, the matching inspection meter in the time period is determined. Using the number of matching inspection meters in the time period and the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to different matching inspection meters, it is determined whether the time period is an inspection processing period.

[0028] It can be understood that using the number of matching inspection meters in the time period and the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to different matching inspection meters, it is determined whether the time period is an inspection processing period, specifically including: Based on the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to the matching inspection meter, the sorting result of the time period in the matching inspection time period corresponding to the matching inspection meter is determined. Based on the sorting result in the matching inspection time period corresponding to different matching inspection meters, it is determined whether the time period is an inspection processing period.

[0029] It should be noted that the sorting result is obtained by sorting from large to small based on the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to the matching inspection meter in the time period.

[0030] It can be understood that when the number of the matching metering meters in the corresponding matching metering period meeting the requirement of the sorting result meets the requirement, the period is determined as a metering processing period. Specifically, in one possible embodiment, the top 50% of the matching metering meters in the sorting result in the corresponding matching metering period are taken as the matching metering meters in the corresponding matching metering period meeting the requirement of the sorting result, and when the number of the matching metering meters in the corresponding matching metering period meeting the requirement of the sorting result is more than 8, the period is determined as the metering processing period.

[0031] Further, the method for determining the metering processing period in the period is as follows: The period in which the image definition of the metering image of the on-site meter meets the requirement is determined according to the analysis result of the image definition of the metering image of the on-site meter in each period, and the period is taken as the matching metering period of the on-site meter. The matching metering meters in the period are determined according to the on-site meter belonging to the matching metering period in the period. The adaptation value of the matching metering meter in the period is determined according to the number of the on-site meters in which the image definition of the metering image of the different matching metering meters meets the requirement. Whether the period is a metering processing period is determined by using the number of the matching metering meters in the period and the adaptation value of the different matching metering meters in the period.

[0032] It should be noted that the adaptation value of the matching metering meter in the period is determined according to the ratio of the number of the on-site meters in which the image definition of the metering image of the matching metering meter meets the requirement in the period to the maximum value of the number of the on-site meters in which the image definition of the metering image of the matching metering meter meets the requirement in all matching metering periods.

[0033] Further, the period in which the image definition of the metering image meets the requirement is determined according to the minimum signal-to-noise ratio at which the metering image can be accurately read by the unmanned aerial vehicle. When the signal-to-noise ratio is greater than the minimum signal-to-noise ratio, it is determined that the image definition of the metering image meets the requirement.

[0034] It can be understood that whether the period is a metering processing period is determined by using the number of the matching metering meters in the period and the adaptation value of the different matching metering meters in the period, and specifically includes: The comprehensive adaptation value is determined by summing the adaptation values of the different matching metering meters in the period in the period, and the period in which the comprehensive adaptation value is greater than a preset adaptation threshold is taken as the metering processing period.

[0035] Further, the method for determining the metering target period of the on-site meter in the metering processing period is as follows: determine the image clarity of the on-site meter in the image clarity required inspection processing period of the on-site meter based on the analysis result of the image clarity of the on-site meter in the image clarity required inspection processing period determine the image clarity of the on-site meter in the image clarity required inspection processing period of the on-site meter based on the analysis result of the image clarity of the on-site meter in the image clarity required inspection processing period determine the image clarity of the on-site meter in the image clarity required inspection processing period of the on-site meter based on the analysis result of the image clarity of the on-site meter in the image clarity required inspection processing period

[0036] It should be noted that when the number of the image clarity required inspection processing periods of the on-site meter is less than the preset period number threshold, all the image clarity required inspection processing periods of the on-site meter are determined as the inspection target periods of the on-site meter.

[0037] In addition, it can be understood that when the number of the image clarity required inspection processing periods of the on-site meter is not less than the preset period number threshold, the period with the maximum number of the on-site meters with the image clarity in the image clarity required inspection processing periods of the on-site meter is taken as the inspection target period of the on-site meter, and in a possible embodiment, the preset period number threshold is about 4.

[0038] Further, the method for determining the inspection processing strategy of the on-site meter is as follows: In the actual inspection processing process of the current date, when the number of the image clarity required inspection processing periods of the on-site meter is less than the preset period number threshold, the inspection processing of the on-site meter is performed in different inspection target periods; In the actual inspection processing process of the current date, when the number of inspection processing periods in which the image definition of the on-site meter meets the requirements is not less than the preset period number threshold, the determination of the inspection target period in which the on-site meter is inspected according to the number of on-site meters in different inspection target periods in which the image definition meets the requirements is performed. Specifically, first, the on-site meter inspection processing is performed in the preset number of inspection target periods in which the number of on-site meters in which the image definition meets the requirements is the most. In one possible embodiment, the on-site meter inspection processing is performed in the first three inspection target periods in which the number of on-site meters in which the image definition meets the requirements is the most. When there is an inspection target period in which the image definition does not meet the requirements in the above-mentioned preset number of inspection target periods, the on-site meter inspection processing is performed in the remaining inspection target periods in the current date. Otherwise, no further inspection processing is required.

[0039] Further, the determination method of the on-site meter inspection processing method of the on-site meter in the future inspection target period is as follows: Based on the on-site meter inspection processing result, the proportion of the number of on-site meters in which the image definition does not meet the requirements in the historical inspection processing of different on-site meters in the current date is determined and used as the poor image proportion of the on-site meter. Based on the matching of the inspection result and the heat supply demand, the on-site meter that does not match the heat supply demand in the latest inspection processing is determined and used as the poor matching meter. The poor image proportion of the on-site meter and the poor matching meter are used to determine the on-site meter inspection processing method of the on-site meter in the future inspection target period.

[0040] It can be understood that the poor matching meter is determined based on the meter monitoring result of the on-site meter when the heat supply demand is met. Specifically, the meter monitoring result of the on-site meter when the heat supply demand is met can be determined based on the monitoring result of the meter when the minimum heat supply amount of the heat supply station can meet the heat supply demand of the heat supply user.

[0041] It should be noted that when the number of poor matching meters in the current date does not meet the requirements, that is, the number of pipelines in which there is a poor matching meter is greater than the preset pipeline number, at this time, the demand degree of the heat supply scheduling processing of the heat station is higher, and therefore, on this basis, it is determined that all on-site meters in all inspection target periods of on-site meters in the current date are inspected.

[0042] Further, if the number of pipes with poor matching meters is not greater than the preset number of pipes, it is determined whether the number of meters with the image poor number proportion greater than the preset proportion threshold and greater than the preset meter number threshold meets the requirement, and if the number of meters with the image poor number proportion greater than the preset proportion threshold and greater than the preset meter number threshold is greater than the preset meter number threshold, it is determined that the reliability of the monitoring processing of the in-situ meter is poor, and thus it is determined that all the in-situ meters in the future in the current date are subjected to the inspection processing.

[0043] If the number of meters with the image poor number proportion greater than the preset proportion threshold and greater than the preset meter number threshold is not greater than the preset meter number threshold, if there is a meter with the image poor number proportion greater than the preset proportion threshold, the in-situ meter subjected to the inspection processing in the future in the current date is subjected to the inspection processing of the in-situ meter with the image clarity meeting the requirement, i.e., the in-situ meter is subjected to the inspection processing in the inspection target period with the image clarity meeting the requirement.

[0044] In addition, it should be noted that if there is no meter with the image poor number proportion greater than the preset proportion threshold, it is further determined whether the number of pipes with poor matching meters is in the preset pipe number interval, and if the number of pipes with poor matching meters is in the preset pipe number interval, the in-situ meter subjected to the inspection processing in the future in the current date is subjected to the inspection processing of the in-situ meter with the image clarity meeting the requirement, i.e., the in-situ meter is subjected to the inspection processing in the inspection target period with the image clarity meeting the requirement.

[0045] In addition, it should be noted that if the number of pipes with poor matching meters is not in the preset pipe number interval, the in-situ meter subjected to the inspection processing in the future in the current date is subjected to the inspection processing of the in-situ meter in the inspection target period of the in-situ meter.

[0046] Optionally, the method for determining the inspection processing of the in-situ meter in the future in the inspection target period comprises the following steps: The inspection processing result of the in-situ meter in the current date is used to determine the number proportion of the inspection target period with the image clarity not meeting the requirement in the historical inspection processing of different in-situ meters, and the number proportion is taken as the image poor number proportion of the in-situ meter, and the image poor number proportion of different in-situ meters is used to determine the inspection deviation value of the in-situ meter. Optionally, in the above step, it is determined whether the number of the in-situ meters that do not meet the requirement in terms of the proportion of the number of the poor images meeting the requirement meets the requirement, where the number of the in-situ meters with the proportion of the number of the poor images greater than the preset proportion threshold is greater than the preset meter number threshold, and at this time, it is determined that the reliability of the monitoring process of the in-situ meters is poor, and therefore, on this basis, it is determined that all the in-situ meters are subjected to the inspection process in the inspection target period of all the in-situ meters in the future on the current date.

[0047] If the number of the in-situ meters with the proportion of the number of the poor images greater than the preset proportion threshold is not greater than the preset meter number threshold, at this time, the inspection deviation value of the in-situ meters is determined according to the proportion of the number of the poor images of different in-situ meters, and when the inspection deviation value does not meet the requirement, it is determined that the reliability of the monitoring process of the in-situ meters is poor, and therefore, on this basis, it is determined that all the in-situ meters are subjected to the inspection process in the inspection target period of all the in-situ meters in the future on the current date, and otherwise, the next step is entered.

[0048] Based on the matching of the inspection result and the heat supply demand, the in-situ meters that do not match the heat supply demand in the latest inspection process are determined as the poor matching meters, and based on the number of the poor matching meters in the pipeline where the poor matching meters exist, the heat supply demand matching deviation value of the in-situ meters is determined. The poor matching meter is determined according to the meter monitoring result of the in-situ meter when the heat supply demand is met, and specifically, the meter monitoring result of the in-situ meter when the heat supply demand is met can be determined according to the meter monitoring result of the in-situ meter when the lowest heat supply amount of the heat supply station can meet the heat supply demand of the heat supply user.

[0049] It should be noted that when the number of the poor matching meters does not meet the requirement, i.e., the number of the pipelines where the poor matching meters exist is greater than the preset pipeline number value, at this time, the demand degree of the heat supply scheduling process of the heat supply station is higher, and therefore, on this basis, it is determined that all the in-situ meters are subjected to the inspection process in the inspection target period of all the in-situ meters in the future on the current date.

[0050] Further, if the number of the pipelines where the poor matching meters exist is not greater than the preset pipeline number value, at this time, it is further determined whether the number of the poor matching meters meets the requirement, and when the number of the poor matching meters is greater than the preset poor matching meter number threshold, at this time, it is determined that all the in-situ meters are subjected to the inspection process in the inspection target period of all the in-situ meters in the future on the current date.

[0051] It can be understood that even if the number of the matched poor meters meets the requirement, it is also necessary to determine whether the heat supply demand matching deviation value of the on-site meter meets the requirement, and when the heat supply demand matching deviation value of the on-site meter is greater than the preset matching deviation threshold value, it is determined that all the on-site meters are inspected in the future inspection target period of the on-site meter in the current date.

[0052] The heat supply demand matching deviation value and the inspection deviation value of the on-site meter are used to determine the inspection method of the on-site meter in the future inspection target period of the on-site meter.

[0053] It should be noted that the comprehensive deviation value is determined based on the average of the heat supply demand matching deviation value and the inspection deviation value of the on-site meter, and when the comprehensive deviation value is greater than the preset deviation threshold value, the inspection method of the on-site meter in the future inspection target period of the on-site meter is determined to be that all the on-site meters are inspected in the future inspection target period of the on-site meter, and when the comprehensive deviation value is not greater than the preset deviation threshold value, only the on-site meter in the on-site meter inspection target period needs to be inspected in the future inspection target period of the on-site meter in the current date.

[0054] Specifically, the inspection results are used for verification processing between different meters, specifically including: The meters installed on the same pipeline are combined as a meter combination, and the verification processing of the meters is performed according to the inspection results of the meters in the meter combination under similar heat supply data of the pipeline. Specifically, when the heat supply temperature and the heat supply flow rate are within a certain interval, the inspection results of different meters are often maintained within a preset range, and if there is an inspection result that is not within the preset range, it is determined that the verification processing result of the meter is abnormal.

[0055] Specifically, if the deviation amounts of the heat supply flow rates of the meters in the pipeline all meet the requirements, that is, the absolute values of the deviation rates between the heat supply flow rates of the other meters except for a certain meter are all less than 2%, and if the absolute value of the deviation rate between the heat supply flow rate of the meter and the heat supply flow rates of the other meters is greater than 10%, it is determined that the verification processing result of the meter is abnormal.

[0056] Embodiment 2 In a second aspect, the present application provides a computer system, comprising a memory and a processor connected in communication, and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to perform the above-mentioned heat station meter inspection method based on the unmanned aerial vehicle.

[0057] The various embodiments in this specification describe the application in progressive stages. Identical or similar parts from one embodiment to another embodiment can be mutually referred to. Each embodiment focuses on the difference from other embodiments. In particular, the device, apparatus, and non-transitory computer storage medium embodiments are described more simply because they are substantially similar to the method embodiments. The relevant parts can be referred to the method embodiment description.

[0058] The above describes specific embodiments of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the acts or steps recited in the claims can be performed in a different order than the order in which they are recited and still achieve desirable results. In addition, the processes depicted in the figures do not necessarily require the particular order shown or sequential order in order to achieve the desired results. In some implementations, multitasking and parallel processing can be advantageous or necessary.

[0059] The above only describes one or more embodiments of the present specification and is not intended to limit the present specification. One or more embodiments of the present specification can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principles of one or more embodiments of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A method for inspecting meters in a thermal power station based on unmanned aerial vehicles (UAVs), characterized in that, Specifically comprising: With the composition data of the monitoring meter, the distribution data of the on-site meter in the heat station is determined, and when it is determined that the preset scheme is not needed for the inspection processing, the next step is entered; The inspection processing of the on-site meter of the heat station is performed, and the image definition of the meter image of the on-site meter in different time periods is obtained. With the analysis result of the image definition of the meter image of the on-site meter in each time period, the inspection processing time period in the time period is determined; With the analysis result of the image definition of each on-site meter in the inspection processing time period, the inspection target time period and the inspection processing strategy of the on-site meter in the inspection processing time period are determined; With the inspection processing strategy, the inspection processing of the on-site meter in the inspection target time period is performed. With the inspection processing result of the on-site meter and the matching condition of the inspection processing result and the heat supply demand, the inspection processing method of the on-site meter in the inspection target time period in the future is determined, and the calibration processing between different meters is performed with the inspection result.

2. The unmanned aerial vehicle based heat station meter patrol method of claim 1, wherein, The composition data of the monitoring meter includes the number of on-site meters and online meters.

3. The unmanned aerial vehicle based heat station meter patrol method of claim 1, wherein, The on-site meter is a meter whose monitoring data does not perform uploading processing.

4. The unmanned aerial vehicle-based thermal station meter reading method of claim 1, wherein, When it is determined that the preset scheme is not needed for the inspection processing, specifically comprising: With the composition data of the on-site meter, the number of on-site meters in the heat station is determined; With the composition data of the on-site meter in different pipelines, the number of pipelines with on-site meters is determined; With the number of pipelines with on-site meters and the composition data of the on-site meter in the pipeline with on-site meters, it is determined whether the preset scheme is needed for the inspection processing.

5. The unmanned aerial vehicle-based thermal station meter reading method of claim 1, wherein, The inspection processing of the on-site meter of the heat station specifically comprises: The inspection processing of all on-site meters in the heat station is performed in different time periods. Specifically, the inspection processing of all on-site meters in the heat station is performed every hour.

6. The unmanned aerial vehicle-based thermal station meter reading method of claim 1, wherein, The image definition of the meter image of the on-site meter is determined according to the signal-to-noise ratio of the meter image.

7. The unmanned aerial vehicle-based thermal station meter reading method of claim 1, wherein, The method for determining the inspection processing time period in the time period is: With the analysis result of the image definition of the meter image of the on-site meter in each time period, the time period in which the image definition of the meter image of the on-site meter meets the requirements is determined as the matching inspection time period of the on-site meter; According to the on-site meter belonging to the matching inspection time period in the time period, the matching inspection meter in the time period is determined; With the number of matching inspection meters in the time period and the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to different matching inspection meters, it is determined whether the time period is an inspection processing time period.

8. The unmanned aerial vehicle-based thermal station meter reading method of claim 7, wherein With the number of matching inspection meters in the time period and the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to different matching inspection meters, it is determined whether the time period is an inspection processing time period, specifically comprising: With the number of on-site meters belonging to the matching inspection time period in the matching inspection time period corresponding to the matching inspection meter in the time period, the sorting result of the time period in the matching inspection time period corresponding to the matching inspection meter is determined; Based on the sorting results in the corresponding matching inspection time periods of different matching inspection tables, it is determined whether the time period is an inspection processing time period.

9. The unmanned aerial vehicle-based thermal station meter reading method of claim 1, wherein, The determined method of the on-site meter inspection processing method of the on-site meter in the future inspection target time period is: Based on the on-site meter inspection processing result, the number ratio of the inspection target time period in which the image definition does not meet the requirement in the historical inspection processing process of different on-site meters in the current date is determined as the image poor number ratio of the on-site meter; Based on the matching condition of the inspection result and the heat supply demand, the on-site meter which does not match the heat supply demand in the latest inspection processing process is determined as a poor matching meter; The on-site meter inspection processing method of the on-site meter in the future inspection target time period is determined by using the image poor number ratio of the on-site meter and the poor matching meter.

10. A computer system comprising: The memory and the processor connected by communication, and the computer program stored on the memory and capable of running on the processor, characterized in that the processor executes the computer program to perform the unmanned aerial vehicle-based heat station meter inspection method of any one of claims 1-9.

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