CN113869605A - Method and device for predicting downstream water level of hydropower station and terminal equipment - Google Patents
Method and device for predicting downstream water level of hydropower station and terminal equipment Download PDFInfo
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Abstract
The invention provides a prediction method, a prediction device and terminal equipment for downstream water level of a hydropower station, wherein the method is applied to a server, the server is in communication connection with an unmanned aerial vehicle, and the method comprises the following steps: acquiring a dam downstream water level prediction model corresponding to a target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of the target dam; controlling the unmanned aerial vehicle to acquire current elevation information of a downstream water area of the target dam; and inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area. The invention can reduce the cost required by water level prediction and improve the efficiency and accuracy of water level prediction, thereby realizing unmanned full-automatic inspection and prediction.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle inspection, in particular to a method and a device for predicting downstream water level of a hydropower station and terminal equipment.
Background
In the operation and dispatching process of the hydropower station, the drainage flow after flood storage dispatching operation can affect the water level and flow amplitude of a downstream riverway of a dam, a large amount of observation data shows that the downstream water level of the hydropower station is affected by various factors for a long time, and particularly when the hydropower station undertakes the tasks of peak regulation and frequency regulation, the flow of the hydropower station leaving a reservoir can be changed violently, so that the non-constant water flow (namely the characteristic of the downstream non-constant flow of the hydropower station) with the water level and the flow rate changing sharply can be formed in the downstream riverway. The complex changes of the downstream water level caused by the delivery flow affect the normal operation of the hydropower station and bring uncertainty to the downstream safety, so that the delivery flow and the downstream water level rise need to be accurately predicted. At present, monitoring equipment such as various ground sensors are mainly utilized to collect information such as dam downstream water level, and the like, and the monitoring equipment is also combined with manual placement and the like, so that the workload is large, the labor cost is high, the sensor work is easily influenced by the collection environment and the working life, and the low-cost, high-efficiency and accurate downstream water level prediction is not facilitated.
Disclosure of Invention
In view of the above, the present invention provides a method, an apparatus, and a terminal device for predicting a downstream water level of a hydropower station, which can reduce the cost required by water level prediction and improve the efficiency and accuracy of water level prediction, thereby implementing unmanned full-automatic inspection and prediction.
In a first aspect, an embodiment of the present invention provides a method for predicting a downstream water level of a hydropower station, where the method is applied to a server, and the server is in communication connection with an unmanned aerial vehicle, and the method includes: acquiring a dam downstream water level prediction model corresponding to a target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of the target dam; controlling the unmanned aerial vehicle to acquire current elevation information of a downstream water area of the target dam; and inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area.
In one embodiment, the step downstream of the dam comprises: acquiring dam parameters of a target dam and a preset downstream water level formula; and constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula.
In one embodiment, the drone carries a laser point cloud pod; the step of controlling unmanned aerial vehicle to gather the current elevation information of the downstream waters of the target dam comprises: issuing a point cloud acquisition task to the unmanned aerial vehicle to acquire point cloud data of a downstream water area of the target dam through the laser point cloud pod of the unmanned aerial vehicle; wherein the point cloud data comprises a point cloud at a junction of a downstream target area of the target dam and the downstream water area; and receiving the point cloud data acquired by the unmanned aerial vehicle, and determining the current elevation information of the downstream water area based on the point cloud data.
In one embodiment, the step of inputting the current elevation information and the dam outbound flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area includes: and estimating an elevation difference value by using the water level prediction model based on the dam delivery flow of the target dam and the current elevation information, and calculating the water level information of the downstream water area based on the current elevation information and the elevation difference value.
In one embodiment, the method further comprises: and generating water level change information of the downstream water area according to the water level information of the downstream water area in the target time period.
In one embodiment, the method further comprises: controlling the unmanned aerial vehicle to acquire a dam image of the target dam and generating a dam three-dimensional live-action model based on the dam image; the dam three-dimensional live-action model is used for displaying live-action information of the target dam and the downstream water area; and displaying the water level information and/or the water level change information of the downstream water area based on the dam three-dimensional live-action model.
In a second aspect, an embodiment of the present invention further provides a device for predicting a downstream water level of a hydropower station, where the device is applied to a server, and the server is in communication connection with an unmanned aerial vehicle, and the device includes: the acquisition module is used for acquiring a dam downstream water level prediction model corresponding to the target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of the target dam; the acquisition module is used for controlling the unmanned aerial vehicle to acquire the current elevation information of the downstream water area of the target dam; and the prediction module is used for inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area.
In one embodiment, the obtaining module is further configured to: acquiring dam parameters of a target dam and a preset downstream water level formula; and constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula.
In a third aspect, an embodiment of the present invention further provides a terminal device, including a memory and a processor; the memory has stored therein a computer program operable on the processor, the processor implementing the steps of the method of any of the first and second aspects when executing the computer program.
In a fourth aspect, embodiments of the present invention also provide a computer-readable storage medium storing machine executable instructions that, when invoked and executed by a processor, cause the processor to perform the method of any one of the first and second aspects.
According to the method, the device and the terminal equipment for predicting the downstream water level of the hydropower station, a dam downstream water level prediction model corresponding to a target dam constructed based on dam parameters is obtained, then an unmanned aerial vehicle is controlled to collect current elevation information of a downstream water area of the target dam, and then the current elevation information and preset dam delivery flow are input into the dam downstream water level prediction model so as to obtain water level information corresponding to the downstream water area by using the dam downstream water level prediction model. According to the method, the current elevation information of the downstream water area is acquired through the unmanned aerial vehicle, the water level information is determined by utilizing the downstream water level prediction model of the dam based on the current elevation information and the flow of the dam leaving the reservoir, and full-automatic inspection and water level prediction of the hydropower station dam are achieved.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the aforementioned and other objects, features and advantages of the present invention comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic flow chart of a method for predicting a downstream water level of a hydropower station according to an embodiment of the invention;
FIG. 2 is a schematic flow chart illustrating another method for predicting a downstream water level of a hydropower station according to an embodiment of the invention;
fig. 3 is a schematic structural diagram of a device for predicting a downstream water level of a hydropower station according to an embodiment of the invention;
fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the embodiments, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In practical application, the change of the downstream water level of the dam is not only related to the delivery flow of the current time period, but also related to the previous working state, namely, has a certain 'aftereffect', and the unsteady flow characteristic of the downstream riverway can cause the actual downstream water levels of the same delivery flow at different moments to be different. Based on the method, the cost required by water level prediction can be reduced, and the efficiency and accuracy of water level prediction are improved, so that unmanned full-automatic inspection and prediction are realized.
To facilitate understanding of the present embodiment, first, a method for predicting a downstream water level of a hydropower station disclosed in the embodiment of the present invention is described in detail, specifically referring to a schematic flow chart of the method for predicting a downstream water level of a hydropower station shown in fig. 1, where the method is applied to a server, and the server is in communication connection with an unmanned aerial vehicle, and the method mainly includes the following steps S102 to S106:
step S102, a dam downstream water level prediction model corresponding to the target dam is obtained, wherein the dam downstream water level prediction model is constructed based on dam parameters of the target dam, the dam parameters can include historical ex-warehouse flow, ex-warehouse time, downstream section initial water level, water level expansion, flow velocity, water depth, water area, section water level difference, river channel geological characteristics, valley morphology (V, U type and the like), bedrock characteristics and other prototype data, the prototype data need to meet the requirements of complete and continuous data, full coverage and the like, and in addition, the dam parameters can also include observation and analysis results of non-constant characteristics and the like. In an embodiment, the downstream water level prediction model of the dam can be constructed according to dam parameters of the target dam and a downstream water level formula, and the downstream water level formula can be an empirical formula established according to historical water level information, so that the required downstream water level prediction model of the dam can be obtained.
And step S104, controlling the unmanned aerial vehicle to acquire the current elevation information of the downstream water area of the target dam. The downstream water area (i.e., the submerged area) can be understood as an area submerged by the water level of the river of the dam rising and returning, and the current elevation information refers to the distance from the horizontal plane to the upper end of the target dam. In one embodiment, the drone may penetrate into the submerged area of the target dam to collect corresponding image data or point cloud data, so as to calculate current elevation information of the downstream water area based on the data.
And S106, inputting the current elevation information and the dam outlet flow of the target dam into a dam downstream water level prediction model to obtain water level information of a downstream water area. In practical application, an uploading channel of the dam delivery flow can be provided for workers, related workers can set the dam delivery flow of the target dam according to the collected current elevation information in combination with practical work experience or other reference information, the dam delivery flow and the current elevation information are input into the dam downstream water level prediction model, the dam downstream water level prediction model is used for predicting the elevation difference value of a downstream water area, and then the water level information of the downstream water area is obtained based on the elevation difference value.
According to the method for predicting the downstream water level of the hydropower station, provided by the embodiment of the invention, the current elevation information of the downstream water area is acquired through the unmanned aerial vehicle, and the water level information is determined by utilizing the downstream water level prediction model of the dam based on the current elevation information and the flow of the dam leaving the reservoir, so that the full-automatic routing inspection and the water level prediction of the hydropower station dam are realized.
Based on the above discussion of step S102, the present invention further provides an implementation method for obtaining a dam downstream water level prediction model corresponding to a target dam, including:
(1) and acquiring dam parameters of the target dam and a preset downstream water level formula. The dam parameters may include historical ex-warehouse flow, ex-warehouse time, downstream section initial water level, water level fluctuation, flow velocity, water depth, water area, section water head, river channel geological characteristics, river valley morphology (V, U type, etc.), bedrock characteristics, observation and analysis results, and the like. The dam parameters have a crucial role in constructing a dam downstream water level prediction model, for example, in practical application, structural parameters such as river channel geological characteristics, valley morphology, bedrock characteristics and the like of the target dam can be collected, and parameters such as water level expansion amplitude, flow speed, water depth, water area, section water head and the like of the target dam can be obtained by combining the parameters, historical ex-warehouse flow, ex-warehouse time, downstream section initial water level and theoretical analysis. In one embodiment, the dam parameters can be stored in a designated storage area, so that the dam parameters are directly read from the designated storage area when a dam downstream water level prediction model is constructed.
(2) And constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula. In an optional implementation manner, a constant in the downstream water level formula may be fitted according to the dam parameters, so as to obtain a dam downstream water level prediction model, where variables of the dam downstream water level prediction model are current elevation information and dam outbound flow, and in a subsequent application process, the constant of the dam downstream water level prediction model may be adjusted according to the current elevation information and an elevation difference corresponding to the current elevation information, so as to further improve prediction accuracy of the dam downstream water level prediction model.
In order to accurately and clearly acquire the current elevation information of the submerged area, the embodiment of the invention provides a laser point cloud pod carried by an unmanned aerial vehicle, and on the basis of the step S104, the invention further provides an implementation mode for controlling the unmanned aerial vehicle to acquire the current elevation information of the downstream water area of the target dam, which comprises the following steps:
a) the method comprises the following steps And issuing the point cloud acquisition task to the unmanned aerial vehicle so as to acquire the point cloud data of the downstream water area of the target dam through a laser point cloud pod of the unmanned aerial vehicle. The point cloud data comprises a point cloud of a junction of a downstream target area of a target dam and a downstream water area, wherein the target area can comprise a downstream slope or a target point, the target point can select points with an included angle of 90 degrees with a water surface, such as a bridge pier, a rock mass and the like, and the point cloud collection task is used for indicating the unmanned aerial vehicle to go to a submerged area and collecting corresponding point cloud data. Specifically, the laser point cloud pod carried by the unmanned aerial vehicle can be used for collecting point cloud data of a downstream water area, and in practical application, in order to ensure the accuracy of the elevation information of the target dam, the point cloud data needs to be collected in a plurality of areas of the target dam.
b) The method comprises the following steps And receiving point cloud data acquired by the unmanned aerial vehicle, and determining the current elevation information of the downstream water area based on the point cloud data. In an alternative embodiment, the modeling may be performed based on point cloud data, such as establishing a model of the junction between the downstream slope and the downstream water area, or establishing a model of the junction between the target point and the downstream water area, where the size of the model is proportional to the actual size of the target dam, so that the current elevation information of the downstream water area may be determined based on the model.
Based on this, on the basis of the above discussion of step S106, the present invention further provides an embodiment of inputting the current elevation information and the dam outbound flow of the target dam into a dam downstream water level prediction model to obtain the water level information of the downstream water area, including: and estimating an elevation difference value based on the dam delivery flow of the target dam and the current elevation information by using a water level prediction model, and calculating the water level information of the downstream water area based on the current elevation information and the elevation difference value. In an optional implementation manner, since each constant parameter in the dam downstream water level model is determined, two variable parameters, namely current elevation information and dam downstream ex-warehouse flow, are input into the dam downstream water level prediction model, so that a corresponding elevation difference value can be calculated, and a sum of the elevation difference value (which may be a positive value or a negative value) and the current elevation information is the water level information of the downstream water area. For example, the flow rate of warehouse-out downstream of the dam is 100 cubic meters, the current elevation information is 30 meters, the elevation difference calculated by using the dam downstream water level prediction model is 2 meters, and the water level information is the sum of the current elevation information and the elevation difference, namely 30+ 2-32 (meters).
Furthermore, in order to facilitate the staff to know the water level change of the downstream water area, the embodiment of the present invention further provides an implementation manner for determining the water level change information, and the water level change information of the downstream water area can be generated according to the water level information of the downstream water area in the target time period. In practical application, the water level information of the target dam is in a dynamic change process, and the water level change condition in a certain time period (target time interval) can be determined according to the real-time water level information of the submerged area, for example, the corresponding water level daily variation can be obtained by continuously recording the water level information in one day, wherein the water level daily variation is the water level change information in one day.
Further, in order to visually display the water level information and/or the water level change information of the downstream water area, the embodiment of the invention further provides an implementation manner as shown below: and controlling the unmanned aerial vehicle to acquire a dam image of the target dam, generating a three-dimensional real-scene model of the target dam based on the dam image, and displaying water level information and/or water level change information of a downstream water area based on the three-dimensional real-scene model of the dam. The dam image comprises a target dam and a downstream drainage basin image, and the dam three-dimensional live-action model is used for displaying live-action information of the target dam and a downstream water area. In practical application, the unmanned aerial vehicle can also collect image information of a dam and a watershed of a target dam, and a three-dimensional real-scene model of the dam is established by utilizing the collected image information so as to display the actual situation of the target dam to a user in real time through the three-dimensional real-scene model of the dam, wherein parameters related to the three-dimensional real-scene model of the dam comprise a warehouse-out flow factor, a river channel erosion and deposition factor, a tail water level factor, a downstream water level factor, a water flow speed factor, a river channel area factor, a former warehouse-out flow and the like. Furthermore, a downstream water area can be simulated based on the water level information, the water level change information and the parameters, so that the water level information and/or the water level change information obtained through the prediction of the water level prediction model is displayed to a user through the dam three-dimensional real-scene model, and the user can be helped to timely and accurately master the water level information of the downstream of the dam.
To facilitate understanding of the water level prediction method provided in the foregoing embodiment, an application example of a method for predicting a downstream water level of a hydropower station is provided in an embodiment of the present invention, and specifically, referring to a flow diagram of another method for predicting a downstream water level of a hydropower station shown in fig. 2, the method includes the following steps S202 to S212:
step S202: and controlling a laser point cloud pod of the fully autonomous unmanned aerial vehicle to execute a fixed-point scanning task. In practical application, the unmanned aerial vehicle is provided with the laser point cloud pod, and point cloud data of a downstream water area of the target dam can be acquired by controlling the laser point cloud pod to designate a vertex scanning task.
Step S204: the real-time water level elevation (i.e., the current elevation information) of the downstream water area is calculated. In one embodiment, a model of a boundary between a slope and a downstream water area may be established through point cloud data, or a model of a boundary between a target point and a downstream water area may be established, so as to calculate an implementation water level elevation based on the model.
Step S206: and receiving the flow of the dam out of the warehouse. In one embodiment, the dam delivery flow rate can be determined by the staff according to the actual working conditions, and the dam delivery flow rate uploaded by the staff is obtained.
Step S208: and inputting the real-time water level elevation and the dam outlet flow into a pre-established dam downstream water level prediction model. In practical application, the real-time water level elevation and the dam delivery flow can be input into a dam downstream water level prediction model, the dam downstream water level prediction model outputs a corresponding elevation difference value, and water level information is obtained through calculation based on the elevation difference value and the real-time water level elevation. It should be noted that a water level prediction model can be pre-constructed according to dam parameters, in addition, the unmanned aerial vehicle can acquire images of the dam and the watershed of the target dam in real time to generate a dam three-dimensional real-scene model, and the dam three-dimensional real-scene model can display the water level conditions of the target dam and the downstream water area in real time.
Step S210: and outputting the water level information and the water level change information of the target dam.
Step S212: and simulating water level information and water level change information through the dam three-dimensional live-action model. Wherein, the water level variation information may include a water level daily variation.
In summary, the prediction method for the downstream water level of the hydropower station provided by the embodiment of the invention collects the current elevation information of the downstream of the target dam, determines the flow rate of the discharged reservoir according to the actual working condition, and inputs the current elevation information and the flow rate of the discharged reservoir into the prediction model for the downstream water level of the dam, so that the influence of the flow rate of the discharged reservoir on the downstream water level of the dam in a prediction period can be rapidly and accurately predicted.
Based on the prediction method of the downstream water level of the hydropower station provided by the foregoing embodiment, the implementation of the present invention provides a prediction apparatus of the downstream water level of the hydropower station, the apparatus is applied to a server, the server is in communication connection with an unmanned aerial vehicle, see a schematic structural diagram of the prediction apparatus of the downstream water level of the hydropower station shown in fig. 3, and the apparatus includes:
the obtaining module 302 is used for obtaining a dam downstream water level prediction model corresponding to a target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of a target dam;
the acquisition module 304 is used for controlling the unmanned aerial vehicle to acquire the current elevation information of the downstream water area of the target dam;
and the prediction module 306 is used for inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area.
According to the water level prediction device provided by the embodiment of the invention, the current elevation information of the downstream water area is acquired by the unmanned aerial vehicle, and the water level information is determined by utilizing the downstream water level prediction model of the dam based on the current elevation information and the flow of the dam leaving the reservoir, so that the full-automatic inspection and water level prediction of the hydropower station dam are realized.
In one embodiment, the obtaining module 302 is further configured to: acquiring dam parameters of a target dam and a preset downstream water level formula; and constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula.
In one embodiment, the drone carries a laser point cloud pod; an acquisition module 304, further configured to: the point cloud acquisition task is issued to the unmanned aerial vehicle, so that point cloud data of a downstream water area of the target dam are acquired through a laser point cloud pod of the unmanned aerial vehicle; the point cloud data comprises point cloud at the junction of a downstream target area of the target dam and a downstream water area; and receiving point cloud data acquired by the unmanned aerial vehicle, and determining the current elevation information of the downstream water area based on the point cloud data.
In one embodiment, the prediction module 306 is configured to: and estimating an elevation difference value based on the dam delivery flow of the target dam and the current elevation information by using a water level prediction model, and calculating the water level information of the downstream water area based on the current elevation information and the elevation difference value.
In one embodiment, the apparatus further comprises a water level change determination module for: and generating water level change information of the downstream water area according to the water level information of the downstream water area in the target time interval.
In one embodiment, the apparatus further comprises a display module for: controlling an unmanned aerial vehicle to acquire a dam image of a target dam and generating a dam three-dimensional live-action model based on the dam image; the dam three-dimensional live-action model is used for displaying live-action information of a target dam and a downstream water area; and displaying the water level information and/or water level change information of the downstream water area based on the dam three-dimensional live-action model.
The system provided by the embodiment has the same implementation principle and the same technical effect as the foregoing embodiment, and for the sake of brief description, reference may be made to the corresponding contents in the foregoing method embodiment for the part of the embodiment of the system that is not mentioned.
The embodiment of the invention provides terminal equipment, which particularly comprises a processor and a storage device; the storage means has stored thereon a computer program which, when executed by the processor, performs the method of any of the above described embodiments.
Fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present invention, where the terminal device 100 includes: a processor 40, a memory 41, a bus 42 and a communication interface 43, wherein the processor 40, the communication interface 43 and the memory 41 are connected through the bus 42; the processor 40 is arranged to execute executable modules, such as computer programs, stored in the memory 41.
The Memory 41 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 43 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, etc. may be used.
The bus 42 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
The memory 41 is used for storing a program, the processor 40 executes the program after receiving an execution instruction, and the method executed by the apparatus defined by the flow process disclosed in any of the foregoing embodiments of the present invention may be applied to the processor 40, or implemented by the processor 40.
The processor 40 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 40. The Processor 40 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory 41, and the processor 40 reads the information in the memory 41 and completes the steps of the method in combination with the hardware thereof.
The computer program product of the readable storage medium provided in the embodiment of the present invention includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to execute the method described in the foregoing method embodiment, and specific implementation may refer to the foregoing method embodiment, which is not described herein again.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present invention, which are used for illustrating the technical solutions of the present invention and not for limiting the same, and the protection scope of the present invention is not limited thereto, although the present invention is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the embodiments of the present invention, and they should be construed as being included therein. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A prediction method for a hydropower station downstream water level is applied to a server which is in communication connection with an unmanned aerial vehicle, and the method comprises the following steps:
acquiring a dam downstream water level prediction model corresponding to a target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of the target dam;
controlling the unmanned aerial vehicle to acquire current elevation information of a downstream water area of the target dam;
and inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area.
2. The method according to claim 1, wherein the step of obtaining a dam downstream water level prediction model corresponding to the target dam comprises:
acquiring dam parameters of a target dam and a preset downstream water level formula;
and constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula.
3. The method of claim 1, wherein the drone carries a laser point cloud pod;
the step of controlling unmanned aerial vehicle to gather the current elevation information of the downstream waters of the target dam comprises:
issuing a point cloud acquisition task to the unmanned aerial vehicle to acquire point cloud data of a downstream water area of the target dam through the laser point cloud pod of the unmanned aerial vehicle; wherein the point cloud data comprises a point cloud at a junction of a downstream target area of the target dam and the downstream water area;
and receiving the point cloud data acquired by the unmanned aerial vehicle, and determining the current elevation information of the downstream water area based on the point cloud data.
4. The method of claim 1, wherein the step of inputting the current elevation information and the dam outbound flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream body of water comprises:
and estimating an elevation difference value by using the water level prediction model based on the dam delivery flow of the target dam and the current elevation information, and calculating the water level information of the downstream water area based on the current elevation information and the elevation difference value.
5. The method of claim 4, wherein the method comprises:
and generating water level change information of the downstream water area according to the water level information of the downstream water area in the target time period.
6. The method of claim 5, further comprising:
controlling the unmanned aerial vehicle to acquire a dam image of the target dam and generating a dam three-dimensional live-action model based on the dam image; the dam three-dimensional live-action model is used for displaying live-action information of the target dam and the downstream water area;
and displaying the water level information and/or the water level change information of the downstream water area based on the dam three-dimensional live-action model.
7. The utility model provides a prediction device of power station downstream water level, its characterized in that, the device is applied to the server, server and unmanned aerial vehicle communication connection, the device includes:
the acquisition module is used for acquiring a dam downstream water level prediction model corresponding to the target dam; the dam downstream water level prediction model is constructed on the basis of dam parameters of the target dam;
the acquisition module is used for controlling the unmanned aerial vehicle to acquire the current elevation information of the downstream water area of the target dam;
and the prediction module is used for inputting the current elevation information and the dam outlet flow of the target dam into the dam downstream water level prediction model to obtain the water level information of the downstream water area.
8. The apparatus of claim 7, wherein the obtaining module is further configured to:
acquiring dam parameters of a target dam and a preset downstream water level formula;
and constructing a dam downstream water level prediction model of the target dam based on the dam parameters and the downstream water level formula.
9. A terminal device, comprising a memory and a processor; the memory has stored therein a computer program operable on the processor, the processor implementing the steps of the method of any of the preceding claims 1 to 6 when executing the computer program.
10. A computer readable storage medium having stored thereon machine executable instructions which, when invoked and executed by a processor, cause the processor to execute the method of any of claims 1 to 6.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114781682A (en) * | 2022-03-01 | 2022-07-22 | 中国长江电力股份有限公司 | Reservoir peak regulation and output increase dam front water level change prediction method based on variable reservoir capacity method |
| CN115018165A (en) * | 2022-06-10 | 2022-09-06 | 江西武大扬帆科技有限公司 | Flood forecast analysis system and method based on big data |
| CN115060343A (en) * | 2022-06-08 | 2022-09-16 | 山东智洋上水信息技术有限公司 | Point cloud-based river water level detection system, detection method and program product |
| CN115165466A (en) * | 2022-07-07 | 2022-10-11 | 北京奥达清环境检测有限公司 | Water taking system of automatic river channel monitoring water station |
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2021
- 2021-10-27 CN CN202111253507.4A patent/CN113869605A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114781682A (en) * | 2022-03-01 | 2022-07-22 | 中国长江电力股份有限公司 | Reservoir peak regulation and output increase dam front water level change prediction method based on variable reservoir capacity method |
| CN114781682B (en) * | 2022-03-01 | 2023-10-27 | 中国长江电力股份有限公司 | Reservoir peak regulation and output increase dam front water level change prediction method based on reservoir capacity changing method |
| CN115060343A (en) * | 2022-06-08 | 2022-09-16 | 山东智洋上水信息技术有限公司 | Point cloud-based river water level detection system, detection method and program product |
| CN115060343B (en) * | 2022-06-08 | 2023-03-14 | 山东智洋上水信息技术有限公司 | Point cloud-based river water level detection system and detection method |
| CN115018165A (en) * | 2022-06-10 | 2022-09-06 | 江西武大扬帆科技有限公司 | Flood forecast analysis system and method based on big data |
| CN115165466A (en) * | 2022-07-07 | 2022-10-11 | 北京奥达清环境检测有限公司 | Water taking system of automatic river channel monitoring water station |
| CN115165466B (en) * | 2022-07-07 | 2024-01-23 | 北京奥达清环境检测有限公司 | Water intake system of river course automatic monitoring water station |
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