An intelligent control method and system for pipeline power supply system based on artificial intelligence

Abstract

The present invention belongs to the technical field of water flow power generation management. Provided is an intelligent control method and system for a pipeline power supply system based on artificial intelligence. The method includes: a controller receives a first water flow information monitoring task sent by a management platform, the first water flow information monitoring task includes a first monitoring task for a number of critical monitoring periods and a second monitoring task for a non-critical monitoring period; the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and determines the upload frequency of the water flow information based on this, and predicts the power demand based on the upload frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods based on the remaining power and the power demand, and controls the combination of the embedded turbine and the externally connected micro-generator in each power generation period to realize the power generation of the externally connected micro-generator. The scheme of the present invention can effectively extend the service life of the generator.

Description

Technical Field

[0001] The present invention relates to the technical field of water flow power generation management, and in particular to an intelligent control method and system for a pipeline power supply system based on artificial intelligence. Background Art

[0002] Water supply pipelines are an important part of urban infrastructure, which are used to provide citizens, institutions, enterprises, etc. with stable water supply that meets relevant indicators. In order to achieve real-time monitoring of the flow rate, water level, water pressure, etc. of the water flow in each water supply pipeline, it is necessary to set up corresponding sensors in the water supply pipeline and send them to the management platform wirelessly. At the same time, a self-generating system is also set up in the water supply pipeline to power sensors, wireless communicators and other components. The self-generating system is driven by the water flow in the water supply pipeline to generate electricity and store it in capacitors, for example.

[0003] However, existing self-generating systems all adopt a normally open setting, that is, the self-generating system continuously generates electricity under the drive of water flow, which causes excessive wear of the generator, thereby reducing its service life. Therefore, it is necessary to reasonably manage the power generation time of the self-generating system, but the existing technology has not yet effectively solved this technical problem. Summary of the invention

[0004] In this regard, the present invention provides an artificial intelligence-based pipeline power supply system intelligent control method, system, electronic device, computer storage medium and computer program product to solve the above-mentioned technical problems.

[0005] The present invention discloses an intelligent control method for a pipeline power supply system based on artificial intelligence. The pipeline power supply system includes a controller, an embedded turbine, an external micro-generator, and a battery. The controller is used to control the combination state of the embedded turbine and the external micro-generator; the battery is used to store the electric energy generated by the external micro-generator and supply it to a wireless communicator and a sensor; the sensor is used to detect water flow information in a water supply pipeline, and the wireless communicator is used to transmit the water flow information to a management platform.

[0006] The method includes the following steps: a controller receives a first water flow information monitoring task sent by a management platform, the first water flow information monitoring task includes a first monitoring task for a number of critical monitoring periods and a second monitoring task for a non-critical monitoring period; the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and thereby determines the upload frequency of the water flow information, and predicts the power demand according to the upload frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the power demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

[0007] In some embodiments, the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and determines the upload frequency of the water flow information accordingly, including: the controller compares the current moment with the set time period of each monitoring task in the first water flow information monitoring task, and determines the monitoring task corresponding to the set time period that is successfully matched, that is, the first monitoring task or the second monitoring task; if the successfully matched monitoring task is the second monitoring task, the second configured upload frequency of the second monitoring task is determined as the upload frequency; if the successfully matched monitoring task is the first monitoring task, the second water flow information monitoring tasks of other pipeline power supply systems within the surrounding preset range are obtained, and a correction coefficient is determined according to each of the second water flow information monitoring tasks, and the upload frequency is calculated according to the correction coefficient and the first configured upload frequency of the first monitoring task.

[0008] In some embodiments, the obtaining of the second water flow information monitoring tasks of other pipeline power supply systems within a surrounding preset range, and determining a correction coefficient based on each of the second water flow information monitoring tasks, includes: determining the preset range based on the first configuration upload frequency and water supply network data, and obtaining the second water flow information monitoring tasks of other pipeline power supply systems within the preset range; calculating the first proportion of the first monitoring tasks belonging to the key monitoring period in each of the second water flow information monitoring tasks, and calculating a second proportion based on each of the first proportions; wherein the second proportion includes the average, median, and mode value of each of the first proportions; and calculating the correction coefficient based on the second proportion.

[0009] In some embodiments, calculating the correction coefficient according to the second ratio includes: ; In the formula, is the correction factor, is the average value in the second ratio, is the median value of the second ratio, is the mode value in the second ratio; , , is the weight coefficient, and , .

[0010] In some embodiments, the power demand is predicted based on the upload frequency, including: obtaining a single upload duration and a static power consumption of a single upload based on a statistical analysis of the upload history of the water flow information, and calculating the dynamic power consumption based on the single upload duration; the power demand is predicted by calculating the static power consumption and the dynamic power consumption of a single upload, the upload frequency, and the duration of a set time period corresponding to the first monitoring task or the second monitoring task.

[0011] In some embodiments, the determining of a plurality of power generation time periods based on the remaining power and the power demand comprises: calculating a power difference based on the power demand and the remaining power, and calculating a plurality of power generation time periods based on the power generation efficiency of the externally connected micro-generator and the rated capacity of the battery.

[0012] The present invention also discloses an intelligent control system for a pipeline power supply system based on artificial intelligence. The intelligent control system is applied to a controller of the pipeline power supply system. The pipeline power supply system includes a controller, an embedded turbine, an external micro-generator, and a battery. The controller is used to control the combination state of the embedded turbine and the external micro-generator; the battery is used to store the electric energy generated by the external micro-generator and supply it to a wireless communicator and a sensor; the sensor is used to detect water flow information in a water supply pipeline, and the wireless communicator is used to transmit the water flow information to a management platform; the intelligent control system includes a processor and a memory, and the processor calls the computer program code stored in the memory to implement The method steps are as follows: a controller receives a first water flow information monitoring task sent by a management platform, wherein the first water flow information monitoring task includes a first monitoring task for a number of critical monitoring periods and a second monitoring task for a non-critical monitoring period; the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and thereby determines the upload frequency of the water flow information, and predicts the electric energy demand according to the upload frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the electric energy demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

[0013] The present invention also discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in any of the preceding items.

[0014] The present invention also discloses a computer storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement any of the above methods.

[0015] The present invention also discloses a computer program product. When the computer program product is run on a terminal, the terminal implements any of the above methods when executing the computer program product.

[0016] The beneficial effect of the present invention is that compared with the working mode of the generator in a continuous power generation state mentioned in the background technology part, the present invention uses a controller to dynamically decide the combination state of the embedded turbine and the external micro-generator according to the first water flow information monitoring task, and then regulates the power generation time of the external micro-generator, thereby reducing the ineffective power generation operation time of the external micro-generator, reducing the wear of the generator, and thus increasing its service life. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a schematic diagram of the basic structure of the pipeline power supply system disclosed in an embodiment of the present invention.

[0019] Figure 2 It is a flow chart of an intelligent control method for a pipeline power supply system based on artificial intelligence disclosed in an embodiment of the present invention.

[0020] Figure 3 It is a structural schematic diagram of an intelligent control system for a pipeline power supply system based on artificial intelligence disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0021] The following is a description of the implementation of the present application by specific specific embodiments. People familiar with the technology can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0022] In addition, the technical features involved in the different embodiments of the present application described below can be combined with each other as long as they do not conflict with each other.

[0023] like Figure 1 As shown, an embodiment of the present invention discloses an intelligent control method for a pipeline power supply system based on artificial intelligence, wherein the pipeline power supply system includes a controller, an embedded turbine, an externally connected micro-generator, and a battery, wherein the controller is used to control the combination state of the embedded turbine and the externally connected micro-generator; the battery is used to store the electric energy generated by the externally connected micro-generator and supply it to a wireless communicator and a sensor; the sensor is used to detect water flow information in a water supply pipeline, and the wireless communicator is used to transmit the water flow information to a management platform.

[0024] like Figure 2 As shown, the method includes the following steps: a controller receives a first water flow information monitoring task sent by a management platform, wherein the first water flow information monitoring task includes a first monitoring task for a number of critical monitoring periods and a second monitoring task for a non-critical monitoring period; the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and thereby determines the upload frequency of the water flow information, and predicts the power demand according to the upload frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the power demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

[0025] Compared to the working mode of the generator in a continuous power generation state mentioned in the background technology part, the controller of the present invention dynamically decides the combination state of the embedded turbine and the external micro-generator according to the first water flow information monitoring task, and then regulates the power generation time of the external micro-generator, thereby reducing the ineffective power generation operation time of the external micro-generator, reducing the wear of the generator, and thus increasing its service life.

[0026] Specifically, the management platform formulates a first water flow information monitoring task, which includes a first monitoring task for several key monitoring periods and a second monitoring task for non-key monitoring periods, and sends it to the controller. The controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and determines the upload frequency of the water flow information suitable for the first monitoring task or the second monitoring task. Different upload frequencies require different electrical energy, and the corresponding electrical energy demand can be predicted accordingly. At the same time, the controller also extracts the remaining power in the battery in real time, determines several power generation periods based on the remaining power and the electrical energy demand, and controls the embedded turbine to combine with the external micro-generator when these power generation periods are reached. The embedded turbine rotates under the drive of the water flow and drives the external micro-generator to rotate, thereby realizing the power generation operation of the external micro-generator, and the generated power is stored in the battery to power the sensor and the wireless communicator.

[0027] It should be noted that the storage battery can be a conventional lithium battery, lead-acid battery, etc., or a capacitor. There are many types of sensors, which are used to detect the flow rate, water level, water pressure, etc. of the water flow in the water supply pipe. In addition, the present invention arranges an AI-based decision module in the controller, and the decision module performs the functions of the controller of the present invention.

[0028] In some embodiments, the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and determines the upload frequency of the water flow information accordingly, including: the controller compares the current moment with the set time period of each monitoring task in the first water flow information monitoring task, and determines the monitoring task corresponding to the set time period that is successfully matched, that is, the first monitoring task or the second monitoring task; if the successfully matched monitoring task is the second monitoring task, the second configured upload frequency of the second monitoring task is determined as the upload frequency; if the successfully matched monitoring task is the first monitoring task, the second water flow information monitoring tasks of other pipeline power supply systems within the surrounding preset range are obtained, and a correction coefficient is determined according to each of the second water flow information monitoring tasks, and the upload frequency is calculated according to the correction coefficient and the first configured upload frequency of the first monitoring task.

[0029] In the embodiment of the present invention, the management platform formulates the water flow information monitoring tasks of each pipeline power supply system in the water supply pipeline network according to the management needs, and sends them to the corresponding water supply pipeline networks respectively. In addition to the first monitoring tasks of the above-mentioned several key monitoring time periods and the second monitoring tasks of the non-key monitoring time periods, the water flow information monitoring tasks also include the set time periods and configured upload frequencies corresponding to each type of second monitoring tasks. The pipeline power supply system performs the corresponding monitoring tasks in the corresponding set time periods and uploads the water flow information according to the corresponding configured upload frequencies.

[0030] Therefore, the controller determines the set time period at the current moment, and then determines the monitoring task that should be performed at present, thereby determining the configuration upload frequency of the water flow information corresponding to the corresponding monitoring task. When the monitoring task is the second monitoring task in the non-critical monitoring period, it means that the monitoring task is a routine monitoring task, and there is no need to increase the upload frequency. At this time, the wireless communicator is controlled to directly upload the detected water flow information to the management platform according to the configuration upload frequency corresponding to the second monitoring task. When the monitoring task is the first monitoring task in the critical monitoring period, it means that the monitoring task is an unconventional monitoring task, such as an emergency monitoring task, a temporary monitoring task, etc. Since the wireless communicator adopts a wireless transmission method, and the signal in the outdoor area where the water supply pipeline is located is generally poor or easily affected by various interferences, there is a certain probability of failure to upload the water flow information. At this time, it is necessary to appropriately increase the upload frequency to ensure the successful upload of the water flow information to avoid adverse effects on key monitoring needs.

[0031] Among them, when the monitoring task is the first monitoring task, the specific processing is as follows: this pipeline power supply system sends an interconnection signal to other pipeline power supply systems within a preset range around it through a wireless communication device, requesting these pipeline power supply systems to share their second water flow information monitoring tasks. The control of this pipeline power supply system can determine the corresponding correction coefficient according to each second water flow information monitoring task, and then calculate the upload frequency in this case according to the correction coefficient and the first configured upload frequency of the first monitoring task.

[0032] In some embodiments, the obtaining of the second water flow information monitoring tasks of other pipeline power supply systems within a surrounding preset range, and determining a correction coefficient based on each of the second water flow information monitoring tasks, includes: determining the preset range based on the first configuration upload frequency and water supply network data, and obtaining the second water flow information monitoring tasks of other pipeline power supply systems within the preset range; calculating the first proportion of the first monitoring tasks belonging to the key monitoring period in each of the second water flow information monitoring tasks, and calculating a second proportion based on each of the first proportions; wherein the second proportion includes the average, median, and mode value of each of the first proportions; and calculating the correction coefficient based on the second proportion.

[0033] In an embodiment of the present invention, a water supply network of a region is stored in the pipeline power supply system, and the water supply network includes multiple sections of water supply pipelines that are interconnected. The controller determines a preset range in the above water supply network according to the first configuration upload frequency corresponding to the first monitoring task. The preset range includes multiple sections of pipelines that are directly or indirectly connected to the pipelines in the region where the pipeline power supply system is located, and other pipeline power supply systems are also arranged in these pipelines. Then, the second water flow information monitoring task of other pipeline power supply systems within the preset range is obtained by sending a request information. The second water flow information monitoring task can be the latest water flow information monitoring task received by the corresponding pipeline power supply system from the management platform. Finally, the first proportion of the first monitoring task belonging to the key monitoring period in each second water flow information monitoring task is calculated, and the average, median, and mode values ​​of each first proportion corresponding to all pipeline power supply systems within the preset range are calculated. These values ​​constitute the second proportion, and the correction coefficient is calculated according to the second proportion. The correction coefficient is then used to correct the first configuration upload frequency corresponding to the first monitoring task to the upload frequency of the water flow information that the wireless communication device of the pipeline power supply system should execute.

[0034] It should be noted that the above-mentioned correction coefficient of the present invention should be a value greater than 1. Using this correction coefficient, the first configuration upload frequency configured by the management platform can be increased to a certain extent to cope with the above-mentioned upload failure problem caused by poor signal or interference, and ensure the timely and successful upload of key water flow information during key monitoring periods.

[0035] In some embodiments, calculating the correction coefficient according to the second ratio includes: ; In the formula, is the correction factor, is the average value in the second ratio, is the median value of the second ratio, is the mode value in the second ratio; , , is the weight coefficient, and , .

[0036] In an embodiment of the present invention, in order to improve the judgment of the correction coefficient on the monitoring task characteristics of other pipeline power supply systems within the surrounding preset range, the present invention comprehensively analyzes and obtains the above correction coefficient based on the average value, median value, and mode value of each first ratio. The correction coefficient obtained by analysis can more accurately reflect the overall criticality of the monitoring tasks of other pipeline power supply systems within the surrounding preset range, and then be used to guide the appropriate upload frequency that this pipeline power supply system should adopt.

[0037] It should be noted that the mode value is more suitable for characterizing the overall criticality of the monitoring tasks of other pipeline power supply systems within the preset range than the mean and median values, so its weight is set to the largest, while the median value is more suitable for characterizing the overall criticality than the mean, so its weight is set to the second largest.

[0038] In some embodiments, the power demand is predicted based on the upload frequency, including: obtaining a single upload duration and a static power consumption of a single upload based on a statistical analysis of the upload history of the water flow information, and calculating the dynamic power consumption based on the single upload duration; the power demand is predicted by calculating the static power consumption and the dynamic power consumption of a single upload, the upload frequency, and the duration of a set time period corresponding to the first monitoring task or the second monitoring task.

[0039] In the embodiment of the present invention, the content of the water flow information uploaded by the wireless communicator each time is the same, and the corresponding data volume is also substantially the same. Therefore, by statistically analyzing the upload history of the water flow information, the single upload duration of the water flow information and the static power consumption required for a single upload can be determined. The dynamic power consumption required for a single upload can be calculated based on the single upload duration. Among them, static power consumption = (wake-up time × wake-up current) + (connection time × connection current) + (sleep time × sleep current), dynamic power consumption = communication time × communication current. Then, based on the static power consumption and dynamic power consumption of a single upload, the upload frequency, and the duration of the set time period corresponding to the monitoring task, the predicted power demand can be calculated.

[0040] In some embodiments, the determining of a plurality of power generation time periods based on the remaining power and the power demand comprises: calculating a power difference based on the power demand and the remaining power, and calculating a plurality of power generation time periods based on the power generation efficiency of the externally connected micro-generator and the rated capacity of the battery.

[0041] In the embodiment of the present invention, the power difference can be calculated based on the power demand obtained by the above prediction and the remaining power in the battery, that is, the external micro-generator needs to generate the power difference to meet the power demand of the wireless communicator in the set period. At the same time, considering the power generation efficiency of the external micro-generator and the rated power capacity of the battery, multiple power generation periods can be determined. For example, [t1, t2], [t4, t5], [t7, t8], that is, during the period t1-t2, the external micro-generator generates power, and the power generated just reaches the rated power capacity of the battery, that is, the battery is fully charged. At this time, the internal turbine and the external micro-generator are disconnected to stop power generation, and the wireless communicator sends water flow information to the management platform according to the upload frequency. The power in the battery is gradually consumed. Before time t4, the internal turbine and the external micro-generator are controlled to be combined again so that the external micro-generator continues to generate power. This cycle is repeated to ensure that there is always power in the battery to supply the wireless communicator.

[0042] It should be noted that the above-determined power generation period has taken into account the power demand of sensors, controllers, etc.

[0043] like Figure 3 As shown, an embodiment of the present invention further discloses an intelligent control system for a pipeline power supply system based on artificial intelligence, wherein the intelligent control system is applied to a controller of the pipeline power supply system, wherein the pipeline power supply system comprises a controller, an embedded turbine, an externally connected micro-generator, and a storage battery, wherein the controller is used to control the combination state of the embedded turbine and the externally connected micro-generator; the storage battery is used to store the electric energy generated by the externally connected micro-generator and supply the wireless communicator and the sensor for use; the sensor is used to detect the water flow information in the water supply pipeline, and the wireless communicator is used to transmit the water flow information to the management platform; the intelligent control system comprises a processor and a memory, wherein the processor calls the computer program code stored in the memory , to implement the following method steps: the controller receives a first water flow information monitoring task sent by a management platform, the first water flow information monitoring task includes a first monitoring task for a number of key monitoring periods and a second monitoring task for a non-key monitoring period; the controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and thereby determines the upload frequency of the water flow information, and predicts the power demand according to the upload frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the power demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

[0044] An embodiment of the present invention further discloses an electronic device, comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method described in the above embodiment.

[0045] An embodiment of the present invention further discloses a computer storage medium, wherein the computer storage medium stores a computer program, and the computer program is executed by a processor to implement the method described in the above embodiment.

[0046] The embodiment of the present invention further discloses a computer program product. When the computer program product is run on a terminal, the terminal implements the method described in the above embodiment.

[0047] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0048] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0049] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0050] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention.

Claims

1. An intelligent control method for pipeline power supply system based on artificial intelligence, characterized in that , the method comprises the following steps: the pipeline power supply system comprises a controller, an embedded turbine, an external micro-generator, and a storage battery, the controller is used to control the combination state of the embedded turbine and the external micro-generator; the storage battery is used to store the electric energy generated by the external micro-generator and supply the wireless communicator and the sensor; the sensor is used to detect the water flow information in the water supply pipeline, and the wireless communicator is used to transmit the water flow information to the management platform; the method comprises the following steps: the controller receives the first water flow information monitoring task sent by the management platform, the first water flow information monitoring task includes a first monitoring task of several key monitoring periods and a second monitoring task of non-key monitoring periods; The controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and accordingly determines the uploading frequency of the water flow information, and predicts the power demand according to the uploading frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the power demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

2. According to claim 1, the intelligent control method of pipeline power supply system based on artificial intelligence is characterized by: The controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and determines the upload frequency of the water flow information accordingly, including: the controller compares the current moment with the set time period of each monitoring task in the first water flow information monitoring task, and determines the monitoring task corresponding to the set time period that successfully matches, that is, the first monitoring task or the second monitoring task; if the successfully matched monitoring task is the second monitoring task, the second configured upload frequency of the second monitoring task is determined as the upload frequency; if the successfully matched monitoring task is the first monitoring task, the second water flow information monitoring tasks of other pipeline power supply systems within the surrounding preset range are obtained, and a correction coefficient is determined according to each of the second water flow information monitoring tasks, and the upload frequency is calculated according to the correction coefficient and the first configured upload frequency of the first monitoring task.

3. According to claim 2, the intelligent control method of pipeline power supply system based on artificial intelligence is characterized by: The second water flow information monitoring tasks of other pipeline power supply systems within a preset range are obtained, and a correction coefficient is determined according to each of the second water flow information monitoring tasks, including: determining the preset range according to the first configuration upload frequency and water supply network data, and obtaining the second water flow information monitoring tasks of other pipeline power supply systems within the preset range; calculating the first proportion of the first monitoring tasks belonging to the key monitoring period in each of the second water flow information monitoring tasks, and calculating the second proportion according to each of the first proportions; wherein the second proportion includes the average value, median value, and mode value of each of the first proportions; and calculating the correction coefficient according to the second proportion.

4. According to claim 3, the intelligent control method of pipeline power supply system based on artificial intelligence is characterized by: Calculating the correction coefficient according to the second ratio includes: ; In the formula, is the correction factor, is the average value in the second ratio, is the median value of the second ratio, is the mode value in the second ratio; , , is the weight coefficient, and , .

5. According to claim 4, the intelligent control method of pipeline power supply system based on artificial intelligence is characterized by: The power demand is predicted based on the upload frequency, including: obtaining a single upload duration and a single upload static power consumption based on a statistical analysis of the upload history of the water flow information, and calculating the dynamic power consumption based on the single upload duration; the power demand is predicted based on the static power consumption and the dynamic power consumption of a single upload, the upload frequency, and the duration of a set time period corresponding to the first monitoring task or the second monitoring task.

6. According to claim 5, the method for intelligent control of pipeline power supply system based on artificial intelligence is characterized in that: Determining a plurality of power generation time periods according to the remaining power and the power demand includes: calculating a power difference according to the power demand and the remaining power, and calculating a plurality of power generation time periods according to the power generation efficiency of the externally connected micro-generator and the rated capacity of the battery.

7. An intelligent control system for a pipeline power supply system based on artificial intelligence, the intelligent control system is applied to the controller of the pipeline power supply system, the pipeline power supply system includes a controller, an embedded turbine, an external micro-generator, and a battery, the controller is used to control the combination state of the embedded turbine and the external micro-generator; the battery is used to store the electric energy generated by the external micro-generator and supply it to the wireless communicator and sensor; the sensor is used to detect the water flow information in the water supply pipeline, and the wireless communicator is used to transmit the water flow information to the management platform; the intelligent control system includes a processor and a memory, characterized in that: The processor calls the computer program code stored in the memory to implement the following method steps: the controller receives a first water flow information monitoring task sent by the management platform, the first water flow information monitoring task including a first monitoring task for a plurality of critical monitoring periods and a second monitoring task for a non-critical monitoring period; The controller determines whether the current moment belongs to the first monitoring task or the second monitoring task based on time comparison, and accordingly determines the uploading frequency of the water flow information, and predicts the power demand according to the uploading frequency; the controller obtains the remaining power of the battery, determines a number of power generation time periods according to the remaining power and the power demand, and controls the embedded turbine to be combined with the externally connected micro-generator in each power generation time period to realize power generation by the externally connected micro-generator.

8. An electronic device, comprising: At least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the method according to any one of claims 1 to 6.

9. A computer storage medium storing a computer program, characterized in that: The computer program is executed by a processor to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program stored on a non-transitory computer readable medium, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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