Water and electricity safety monitoring method and system based on Internet of Things

Abstract

The invention discloses a water and electricity safety monitoring method and system based on the Internet of Things, and relates to the technical field of water and electricity safety, the system comprises a three-dimensional map unit and an evaluation and detection unit, and a plurality of high-risk zones are sequentially checked by using an unmanned aerial vehicle system based on an evaluation result; the installation unit is used for determining an electricity stealing area based on an inspection result of the unmanned aerial vehicle inspection unit, and setting an electronic fence system and a video monitoring system in the area; the confirmation unit is used for determining an area where an electricity stealing behavior possibly exists or already exists, and if the electricity stealing behavior exists, communication to the outside is carried out after confirmation; and the early warning unit is used for setting a safety monitoring system to monitor an electricity stealing position when an electricity stealing behavior is inconvenient to immediately clear in an electricity stealing area, and giving an alarm to the outside and carrying out emergency power failure when a danger is generated. According to accurate estimation of the potential safety hazard of the position, when the potential safety hazard is generated or is about to be generated, corresponding processing is carried out in time, so that the potential safety hazard is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of hydropower safety, and specifically to a hydropower safety monitoring method and system based on the Internet of Things. Background Technique

[0002] In the remote rural areas and mountainous regions in the southwest of China, the hydropower resources are very rich, and the exploitable amount reaches 87 million kW. However, the terrain in these areas is complex, the population is sparse, the load is scattered, and the demand is low. Moreover, due to geographical environment and financial capacity limitations, it is very difficult to monitor the transmission lines around hydropower stations, which has led to a large number of electricity theft users around these small hydropower stations.

[0003] Some electricity theft personnel directly connect wires illegally along non-high-voltage transmission lines to illegally steal electric power resources. The operating conditions of the small hydropower stations whose electricity has been stolen are already worrying. In the absence of comprehensive and accurate operating data, it is very difficult for the power grid to achieve safe dispatching and orderly supervision of small hydropower stations. Even some wire connections by electricity thieves cannot be detected, resulting in the waste of electricity that cannot be recovered.

[0004] However, the harm of illegal wire connection for electricity theft is not limited to this. The areas where electricity is stolen are usually high-risk areas because the illegal wire connections at the electricity theft locations are often very unprofessional and the lines are too dense, which easily leads to electric leakage or fire, posing a great safety hazard.

[0005] Therefore, a hydropower safety monitoring method and system based on the Internet of Things are provided. Summary of the Invention

[0006] (I) Technical Problems to be Solved Aiming at the deficiencies of the prior art, the present invention provides a hydropower safety monitoring method and system based on the Internet of Things. By setting a three-dimensional map unit, an evaluation and detection unit, and using a drone system to sequentially check several high-risk areas based on the evaluation results; an installation unit, based on the inspection results of the drone inspection unit, determines the areas where electricity theft exists, and sets up an electronic fence system and a video monitoring system in these areas; a confirmation unit, determines the areas where electricity theft may exist or already exists. If electricity theft exists, after confirmation, it communicates with the outside; an early warning unit, when it is not convenient to immediately clean up the electricity theft behavior in the area where electricity theft exists, sets up a safety monitoring system to monitor the electricity theft location, and when danger occurs, alarms to the outside and cuts off the power emergently. According to the accurate estimation of the safety hazards at this location, corresponding measures are taken in a timely manner when safety hazards occur or are about to occur, thereby reducing safety hazards and solving the problems in the background technique.

[0007] (II) Technical Solutions To achieve the above objectives, the present invention is realized through the following technical solutions: A method for hydropower safety monitoring based on the Internet of Things, including: Step 1: Determine the monitoring area and create an electronic three-dimensional map, determine high-risk areas from the monitoring area, and mark them on the electronic three-dimensional map; The first step includes: Step 101: Determine the location of power generation or power supply, obtain the power supply area associated with the location, and establish an electronic three-dimensional map based on existing map data; Step 102: Determine the locations that are easily illegally wired according to whether the distance between the power supply line and the ground exceeds the threshold, and mark these locations that are easily illegally wired on the three-dimensional map. Step 2: Evaluate several high-risk areas in sequence, and use the drone system to inspect several high-risk areas in sequence based on the evaluation results. After the inspection is completed, randomly inspect other areas. The second step includes: Step 201: Image the high-risk areas through imaging equipment, obtain the terrain features of several high-risk areas, and establish a feature library; Step 202: Establish and train a terrain walking difficulty scoring model based on the deep learning algorithm, score the terrain features of each high-risk area, and output the score; Step 203: Obtain the height of the power transmission line in the high-risk area and output height data. Step 3: Based on the inspection results of the drone inspection unit, determine the areas where electricity theft exists, and set up an electronic fence system and a video monitoring system in this area. Step 4: Determine the areas where electricity theft may exist or already exists, mark them on the three-dimensional map, and detect this area. If electricity theft exists, confirm and communicate externally. Step 5: When it is not convenient to immediately clean up the electricity theft behavior in the area where electricity theft exists, set up a safety monitoring system to monitor the electricity theft location, and when danger occurs or may occur, alarm externally and cut off the power emergently.

[0008] Further, after step 203, it includes: Step 204: Obtain the height data H and the score data F, and determine the electricity theft difficulty scoring strategy, score the high-risk areas, and determine the electricity theft risk value Qf; Step 205: Obtain several electricity theft risk values Qf, sort several high-risk areas, so as to determine the areas that are most easily stolen; Step 206: Through the path planning algorithm, establish and train a path planning model, and the path planning model combines the electricity theft risk value ranking to plan the inspection order of the high-risk areas; Output the inspection order and execute it by the drone inspection unit.

[0009] Further, the electricity theft difficulty scoring strategy is; obtain the height data H and the score data F, perform normalization processing, and synthesize them to form the electricity theft risk value Qf. The confirmation logic of the electricity theft risk value Qf is as follows:

[0010] Among them, and are variable constant parameters. Among them, and , users can adjust according to the actual situation. The C and E constant correction coefficients can be corrected according to the actual pollution determination situation.

[0011] Furthermore, the third step includes the following contents: Step 301, obtain the inspection results of the high-risk area by the drone inspection unit and establish an inspection image library; Step 302, determine whether there is any illegal wiring behavior in the high-risk area involved through image recognition from the inspection images. If so, mark this area and determine it as a suspected electricity theft area; Step 303, use the drone inspection unit to verify the suspected electricity theft area, determine the electricity theft area therein, and mark it on the electronic three-dimensional map; Step 304, obtain several high-risk areas with electricity theft risk values higher than the threshold, determine them as electricity theft risk areas, and set up an electronic fence system and a video monitoring system in the electricity theft risk areas and the electricity theft areas respectively.

[0012] Furthermore, the fourth step includes the following contents: Step 401, set up a power supply data monitoring device on the transformer adjacent to the electricity theft area to detect nearby electricity theft users. If there are electricity theft users, send an alarm to the outside; Among them, the method for detecting electricity theft is: collect the high-voltage side current through the power consumption management monitoring terminal and upload it to the power consumption management main station. The power management main station collects the low-voltage side load current collected by the user collection system, compares the high-voltage side and low-voltage side load current curves, calculates the load current difference, and determines that there is an electricity theft behavior when it reaches the preset threshold; locate the users with electricity theft behavior and send the location information to the outside.

[0013] Furthermore, after Step 401, there are also: Step 402, set up a monitoring system in the electricity theft area to monitor each area with an electricity theft risk value higher than the threshold, so as to judge whether there will still be electricity theft behavior; enter the information of all electricity theft personnel with electricity theft behavior in the electricity theft area into the database, determine them as high-risk personnel, and conduct verification in turn according to the risk level when electricity theft behavior occurs again.

[0014] Further, the fifth step includes the following: Step 501, determine the location of illegal wiring in the electricity theft area. In case of possible leakage, establish a safe area and set up an electronic fence system along the outer edge of the safe area; Step 502, set up smoke sensors and heat sensors outside the electronic fence system to monitor the energized lines inside the electronic fence system respectively, and output the smoke concentration and temperature data in real time; Step 503, obtain the temperature data and smoke concentration data, compare them with the warning thresholds respectively. If at least one of them exceeds the threshold, an alarm will be sent to the outside.

[0015] Further, after step 503, there is also: Step 504, obtain the temperature T and the smoke concentration Yw. When both of them do not exceed the threshold, generate a hidden danger assessment value Yp according to the hidden danger assessment strategy; among them, the hidden danger assessment strategy is as follows: obtain the temperature T and the smoke concentration Yw, perform normalization processing, and synthesize them to form the hidden danger assessment value Yp. The confirmation logic of the pollution assessment value Yp is as follows:

[0016] Among them, 、 are variable constant parameters. Among them, and , which can be adjusted by users according to the actual situation. The A and B constant correction coefficients can be corrected according to the actual pollution determination situation.

[0017] Further, after step 504, it includes: Step 505, obtain several groups of hidden danger assessment values. When the current hidden danger assessment value exceeds the corresponding threshold, or when two of the three consecutive predicted values generated based on the quadratic smoothing index exceed the threshold, an alarm will be sent to the outside; Step 506, in steps 503 and 505, if the alarm sent to the outside is not responded within the preset time, the electricity theft area will be cut off power emergently.

[0018] The hydropower safety monitoring system based on the Internet of Things includes: a three-dimensional map unit, determine the monitoring area and make an electronic three-dimensional map, determine the high-risk areas from the monitoring area, and mark them on the electronic three-dimensional map; An evaluation and detection unit, evaluate several high-risk areas in turn, and use the drone system to check several high-risk areas in turn based on the evaluation results. After the inspection is completed, randomly check other areas; An installation unit, based on the inspection results of the drone inspection unit, determine the area where electricity theft exists, and set up an electronic fence system and a video monitoring system in this area; The confirmation unit determines the area where power theft may exist or already exists, marks it on a 3D map, and detects this area. If power theft is found, it will communicate externally after confirmation. The warning unit, when it is not convenient to immediately clean up power theft in the area where power theft occurs, sets up a security monitoring system to monitor the power theft location, and when danger occurs or may occur, it will alarm externally and cut off the power emergently.

[0019] (III) Beneficial effects The present invention provides a hydropower security monitoring system based on the Internet of Things, which has the following beneficial effects: When monitoring the hydropower transmission line, the area to be monitored is visualized, and the area where power theft may exist inside can be quickly determined for targeted monitoring, thereby reducing the risk of power theft.

[0020] According to the location and risk of the power theft area, several high-risk areas are inspected, reducing the economic cost and time cost of inspecting each area with a transmission line, saving manpower and material resources, and improving the detection efficiency; since the planned inspection path combines the power theft risk, it can also quickly find the area where power theft has already occurred when using drones for inspection.

[0021] Quickly determine the power theft risk area and power theft area from the monitoring area, and set up protection facilities, which can improve the high safety of the transmission line with illegal wiring already existing, and reduce the potential safety hazards that the power theft risk area and power theft area may bring.

[0022] When it is determined that power theft exists but cannot be processed immediately, the user can accurately estimate the potential safety hazards at this location, and make corresponding treatments in time when safety hazards occur or are about to occur, thereby reducing safety hazards and reducing the probability of fire. Brief description of the drawings

[0023] Figure 1 It is a schematic flow chart of the hydropower security monitoring method of the present invention; Figure 2 It is a schematic structural diagram of the hydropower security monitoring system of the present invention; Figure 3 It is a schematic diagram of the composition of the hidden danger evaluation value and power theft risk value of the present invention.

[0024] In the figure: 10, 3D map unit; 20, evaluation and detection unit; 30, installation unit; 40, confirmation unit; 50, warning unit. Detailed implementation manners

[0025] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0026] Embodiment 1:

[0027] Please refer to Figures 1-3 , the present invention provides a hydropower safety monitoring method based on the Internet of Things, including the following steps: Step 1: Determine the monitoring area and create an electronic three-dimensional map, determine the high-risk areas from the monitoring area, and mark them on the electronic three-dimensional map; it should be noted that the so-called high-risk areas refer to areas where electricity theft is likely to occur. Since the illegal wiring at the electricity theft locations is often very unprofessional and the lines are too dense, it is very easy to cause electric leakage or fire, posing a great safety hazard. The first step includes the following contents: Step 101: Determine the power generation or supply location, obtain the power supply area associated with the location, and establish an electronic three-dimensional map based on the existing map data; thereby visualizing the area.

[0028] Step 102: Determine the locations that are likely to be illegally wired based on whether the distance between the power supply line and the ground exceeds the threshold; among them, the height of the locations that are easily illegally wired can be retrieved from public information channels, such as news reports. Take 80% of the highest height made public as the threshold, that is, the locations below 80% of the highest height are the locations that are easily illegally wired; and mark these locations that are easily illegally wired on the three-dimensional map.

[0029] During use, combining the contents of steps 101 and 102, when monitoring the hydropower transmission, the area to be monitored can be visualized, and the areas where electricity theft is likely to occur inside can be determined for targeted monitoring, thereby reducing the risk of electricity theft and also reducing the safety hazard.

[0030] Step 2: Evaluate several high-risk areas in sequence, and use the drone system to inspect several high-risk areas in sequence based on the evaluation results. After the inspection is completed, randomly inspect other areas; the second step includes the following contents: Step 201: Image the high-risk areas through an imaging device, obtain the terrain features of several high-risk areas, and establish a feature library; when imaging, due to the inconsistent terrain conditions in different places and to save costs, drones can be used to image in sequence.

[0031] Step 202: Based on the deep learning algorithm, establish and train a terrain walking difficulty scoring model to score the terrain features of each high-risk area and output the scores. In actual use, the more difficult the terrain is to access and the more difficult it is to walk normally, the lower the possibility of electricity theft behavior.

[0032] Step 203: Obtain the height of the transmission line in the high-risk area and output the height data. Step 204: Obtain the height data H and the scoring data F, determine the electricity theft difficulty scoring strategy, score the high-risk area, and determine the electricity theft risk value Qf. Among them, the electricity theft difficulty scoring strategy is as follows: Obtain the height data H and the scoring data F, perform normalization processing, and synthesize them to form the electricity theft risk value Qf. The confirmation logic of the electricity theft risk value Qf is as follows:

[0033] Among them, 、 are variable constant parameters. Among them, and , which can be adjusted by users according to the actual situation. The C and E constant correction coefficients can be corrected according to the actual pollution determination situation.

[0034] In use, by generating the electricity theft risk value Qf, it is possible to evaluate the difficulty of illegal external connection cables and electricity theft of the transmission lines in the high-risk area. According to the magnitude of the electricity theft risk value Qf, it is possible to evaluate the electricity theft risk in the high-risk area. After receiving the electricity risk value Qf, users can also adjust the electricity theft difficulty scoring strategy according to the actual electricity theft situation, so that it better conforms to the actual use scenario.

[0035] Considering that there may be more than one high-risk area, but in actual processing, it may be difficult to handle them simultaneously. Therefore, there is also step 205 after step 204: Step 205: Obtain several electricity theft risk values Qf, sort several high-risk areas, and thus determine the area most vulnerable to electricity theft. Step 206: Through the path planning algorithm, establish and train a path planning model. The path planning model combines the electricity theft risk value sorting to plan the inspection order for the high-risk areas; output the inspection order and execute it by the unmanned aerial vehicle inspection unit.

[0036] In use, by planning the path, it is possible to combine the location of the high-risk area with the corresponding location to determine the unmanned aerial vehicle inspection order, so as to give priority to checking the area most likely to be stolen while shortening the inspection duration.

[0037] During use, combine the content in Steps 201 to 206: After determining the high-risk areas, evaluate the electricity theft risk values of several high-risk areas, and finally determine the inspection path. The drones with Internet of Things communication functions will check several high-risk areas in sequence, and finally output the inspection results, so as to minimize the economic cost and time cost of inspecting each area with transmission lines. Moreover, since the planned inspection path combines the electricity theft risk, it can also quickly detect the areas where electricity theft has occurred when using drones for inspection.

[0038] Step 3. Based on the inspection results of the drone inspection unit, determine the areas where electricity theft exists, and set up an electronic fence system and a video surveillance system in these areas; the said Step 3 includes the following content: Step 301, obtain the inspection results of the drone inspection unit for the high-risk areas and establish an inspection image library; it should be noted that when using the drone inspection unit to inspect the high-risk areas, the inspection results obtained are in the form of images and videos, and the drone inspection unit has a communication function and uploads or sends data based on the Internet of Things. Step 302. Through image recognition in the inspection images, judge whether there is any illegal wiring behavior in the involved high-risk areas. If so, mark this area and determine it as a suspected electricity theft area. Step 303. Use the drone inspection unit to verify the suspected electricity theft areas, determine the electricity theft areas among them, and mark them on the electronic 3D map. During use, through the initial inspection and re-inspection of the drone inspection unit and with the help of image recognition, quickly confirm the areas with illegal wiring.

[0039] Step 304. Obtain several high-risk areas with electricity theft risk values higher than the threshold, determine them as electricity theft risk areas, and set up an electronic fence system and a video surveillance system in the electricity theft risk areas and the electricity theft areas respectively.

[0040] During use, by setting up an electronic fence for the electricity theft risk areas, it can play a protective role for this area to avoid the risk of electricity theft in this area. If someone breaks through the electronic fence system, it can also be recognized through the video surveillance system, and finally it is convenient to determine the identity of the electricity theft personnel through the surveillance content.

[0041] During use, combine the content in Steps 301 to 304. With the help of the drone inspection unit, it is possible to determine the electricity theft risk areas and the electricity theft areas from the monitored areas. After setting up the protection devices, the safety can be improved and the potential safety hazards that may be brought by the electricity theft risk areas and the electricity theft areas can be reduced.

[0042] Step 4: Determine the area where electricity theft may exist or already exists, mark it on the 3D map, and detect this area. If electricity theft is found, confirm it and communicate externally; thus facilitating the timely investigation and punishment of illegal acts. The content of Step 4 is as follows: Step 401: Set up a power supply data monitoring device on the transformer adjacent to the electricity theft area to detect nearby electricity theft users. If there are electricity theft users, send an alarm externally; Among them, the method for detecting electricity theft is: Collect the high-voltage side current through the power consumption management monitoring terminal and upload it to the power consumption management master station. The power management master station collects the low-voltage side load current collected by the user collection system, compares the high-voltage side and low-voltage side load current curves, calculates the load current difference, and determines that there is electricity theft behavior when it reaches the preset threshold; Locate the users with electricity theft behavior and send the location information externally.

[0043] During use, by setting up a power supply data monitoring device on the transformer adjacent to the electricity theft area, it is possible to determine the electricity theft users and their specific locations within the area, thus facilitating targeted handling. Further, it is also possible to obtain the facial features of the electricity theft users and store them in the electricity theft user database to facilitate key attention when electricity theft occurs again in this electricity theft area.

[0044] After Step 401, there is also: Step 402: Set up a monitoring system within the electricity theft area to monitor areas where each electricity theft risk value is higher than the threshold, so as to determine whether there will still be electricity theft behavior; Enter the information of all electricity theft personnel with electricity theft behavior in the electricity theft area into the database, determine them as high-risk personnel, and conduct verification in sequence according to the risk level when electricity theft occurs again.

[0045] During use, in Step 402, by entering the identity information of former electricity theft personnel, it is possible to reduce the time cost of re-verification and also have a warning effect.

[0046] Step 5: When it is not convenient to immediately clean up the electricity theft behavior in the area where electricity theft exists, set up a safety monitoring system to monitor the electricity theft location, and when danger occurs or may occur, alarm externally and cut off the power emergently; thus enabling users to be aware immediately when a safety hazard occurs or is about to occur.

[0047] The content of Step 5 includes the following: Step 501: Determine the location of illegal wiring within the electricity theft area. In case of possible leakage, establish a safety area and set up an electronic fence system along the outer edge of the safety area, thereby preventing unauthorized access to this area. Step 502: Set up smoke sensors and heat sensors outside the electronic fence system to monitor the energized circuits inside the electronic fence system respectively, and output the smoke concentration and temperature data in real time. Step 503: Obtain the temperature data and smoke concentration data, compare them with the warning thresholds respectively. If at least one of them exceeds the threshold, an alarm will be sent to the outside.

[0048] Combining the content in Step 501 and Step 503, by setting up smoke sensors and heat sensors, real-time monitoring of the location of illegal wiring can be achieved.

[0049] After Step 503, there is also: Step 504: Obtain the temperature T and the smoke concentration Yw. When both of them do not exceed the threshold, generate a hidden danger assessment value Yp according to the hidden danger assessment strategy. Among them, the hidden danger assessment strategy is as follows: Obtain the temperature T and the smoke concentration Yw, perform normalization processing, and synthesize them to form the hidden danger assessment value Yp. The confirmation logic of the pollution assessment value Yp is as follows:

[0050] Among them, 、 are changeable constant parameters. Among them, and , which can be adjusted by users according to the actual situation. The constant correction coefficients A and B can be corrected according to the actual pollution determination situation.

[0051] Step 505: Obtain several groups of hidden danger assessment values. When the current hidden danger assessment value exceeds the corresponding threshold, or when two of the three consecutive predicted values generated based on the quadratic smoothing index exceed the threshold, an alarm will be sent to the outside. Step 506: In Step 503 and Step 505, if the alarm sent to the outside is not responded within the preset time, the electricity in this electricity theft area will be cut off emergently.

[0052] During use, in combination with the content in Steps 501 to 506, when it is determined that there is electricity theft behavior but it cannot be dealt with immediately, the location of electricity theft with illegal wiring is monitored, and the safety of the power transmission lines in the electricity theft area is risk-assessed based on the monitoring results. Therefore, users can accurately estimate the potential safety hazards at this location and make corresponding treatments in a timely manner when safety hazards occur or are about to occur, thereby reducing safety hazards to the greatest extent and decreasing the probability of fire.

[0053] In this application, in combination with the content in Steps 1 to 5, there are at least the following effects: When monitoring the water and electricity transmission lines, the area to be monitored is visualized to quickly determine the possible electricity theft areas inside and conduct targeted monitoring, thereby reducing the risk of electricity theft.

[0054] Based on the location and risk of the electricity theft area, several high-risk areas are inspected, reducing the economic cost and time cost of inspecting each area with power transmission lines, saving manpower and material resources, and improving the detection efficiency; since the planned inspection path incorporates the electricity theft risk, it is also possible to quickly discover the areas where electricity theft has already occurred when using drones for inspection.

[0055] Quickly determine the electricity theft risk areas and electricity theft areas from the monitoring area and set up protection facilities, which can improve the high safety of the power transmission lines with illegal wiring behavior and reduce the potential safety hazards that may be brought by the electricity theft risk areas and electricity theft areas.

[0056] When it is determined that there is electricity theft behavior but it cannot be dealt with immediately, users can accurately estimate the potential safety hazards at this location and make corresponding treatments in a timely manner when safety hazards occur or are about to occur, thereby reducing safety hazards and decreasing the probability of fire.

[0057] Embodiment 2:

[0058] Please refer to Figures 1-3 , the present invention provides an Internet of Things-based water and electricity safety monitoring system, including: A three-dimensional map unit 10, which determines the monitoring area and creates an electronic three-dimensional map, determines the high-risk areas from the monitoring area, and marks them on the electronic three-dimensional map; An evaluation and detection unit 20, which evaluates several high-risk areas in sequence and uses a drone system to inspect several high-risk areas in sequence based on the evaluation results. After the inspection is completed, other areas are randomly inspected; An installation unit 30, which determines the area where electricity theft exists based on the inspection results of the drone inspection unit and sets up an electronic fence system and a video monitoring system in this area; The confirmation unit 40 determines the area where power theft may exist or already exists, marks it on a three-dimensional map, and detects the area. If power theft exists, after confirmation, it communicates with the outside; The warning unit 50 sets up a security monitoring system to monitor the power theft location when it is not convenient to immediately clean up the power theft behavior in the area where power theft exists, and alarms to the outside and cuts off the power emergently when danger occurs or may occur.

[0059] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that the computer can access, or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0060] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present application.

[0061] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0062] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only based on the logical function division of the water and electricity safety monitoring system and the waterway underwater terrain change analysis system and method based on the Internet of Things. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the devices or units can be in electrical, mechanical, or other forms.

[0063] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0064] In addition, in each embodiment of the present application, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0065] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the essence of the technical solution of the present application, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks, or optical discs, etc., which can store program codes.

[0066] As described above, it is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0067] Finally, the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for hydropower safety monitoring based on the Internet of Things, characterized in that: Including, Step 1: Determine the monitoring area and create an electronic 3D map. Identify high-risk areas from the monitoring area and mark them on the electronic 3D map; The said Step 1 includes: Step 101: Determine the power generation or power supply location, obtain the power supply area associated with the location, and establish an electronic 3D map based on existing map data; Step 102: Determine the locations that are prone to illegal wiring based on whether the distance between the power supply line and the ground exceeds the threshold, and mark these locations prone to illegal wiring on the 3D map; Step 2: Evaluate several high-risk areas in sequence, and use the drone system to inspect several high-risk areas in sequence based on the evaluation results. After the inspection is completed, randomly inspect other areas; The said Step 2 includes: Step 201: Image the high-risk areas through imaging equipment, obtain the terrain features of several high-risk areas, and establish a feature library; Step 202: Based on the deep learning algorithm, establish and train a terrain walking difficulty scoring model, score the terrain features of each high-risk area, and output the scores; Step 203: Obtain the height of the power transmission line in the high-risk area and output the height data; Step 3: Based on the inspection results of the drone inspection unit, determine the areas where electricity theft exists, and set up an electronic fence system and a video monitoring system in these areas; Step 4: Determine the areas where electricity theft may exist or already exists, mark them on the 3D map, and detect these areas. If electricity theft exists, confirm and communicate externally; Step 5: When it is not convenient to immediately clean up the electricity theft behavior in the areas where electricity theft exists, set up a safety monitoring system to monitor the electricity theft locations, and when danger occurs or may occur, alarm externally and cut off the power emergently.

2. The method for hydropower safety monitoring based on the Internet of Things according to claim 1, characterized in that: After the said Step 203, it includes: Step 204: Obtain the height data H and the scoring data F, and determine the electricity theft difficulty scoring strategy, score the high-risk areas, and determine the electricity theft risk value Qf; Step 205: Obtain several electricity theft risk values Qf, sort several high-risk areas, and thus determine the areas that are most prone to electricity theft; Step 206: Through the path planning algorithm, establish and train a path planning model. The path planning model combines the electricity theft risk value ranking to plan the inspection order of the high-risk areas; Output the inspection order and execute it by the drone inspection unit.

3. The method for hydropower safety monitoring based on the Internet of Things according to claim 2, characterized in that: The said electricity theft difficulty scoring strategy is: Obtain the height data H and the scoring data F, perform normalization processing, and synthesize them to form the electricity theft risk value Qf. The confirmation logic of the electricity theft risk value Qf is as follows: ； Among them, , are variable constant parameters, where and , which can be adjusted by the user according to the actual situation. The C and E constant correction coefficients can be corrected according to the actual pollution determination situation.

4. The method for hydropower safety monitoring based on the Internet of Things according to claim 1, characterized in that: The said Step 3 includes the following contents: Step 301, obtain the inspection results of the drone inspection unit for the high-risk areas and establish an inspection image library; Step 302: Determine whether there is illegal wiring behavior in the high-risk areas involved through image recognition from the inspection images. If so, mark these areas and determine them as suspected electricity theft areas; Step 303: Use the drone inspection unit to verify the suspected electricity theft area, determine the electricity theft areas therein, and mark them on the electronic three-dimensional map; Step 304: Obtain several high-risk areas with electricity theft risk values higher than the threshold, determine them as electricity theft risk areas, and set up an electronic fence system and a video surveillance system in the electricity theft risk areas and the electricity theft areas respectively.

5. The method for monitoring the safety of hydropower based on the Internet of Things according to claim 1, wherein: The fourth step includes the following content: Step 401: Set up a power supply data monitoring device on the transformer adjacent to the electricity theft area to detect nearby electricity theft users. If there are electricity theft users, send an alarm to the outside. Among them, the method for detecting electricity theft is as follows: Collect the high-voltage side current through the power consumption management monitoring terminal and upload it to the power consumption management main station. The power management main station collects the low-voltage side load current collected by the user acquisition system, compares the high-voltage side and low-voltage side load current curves, calculates the load current difference, and determines that there is an electricity theft behavior if it reaches the preset threshold. Locate the users with electricity theft behavior and send the location information to the outside.

6. The method for hydropower safety monitoring based on the Internet of Things according to claim 5, characterized in that: After step 401, there is also: Step 402: Set up a monitoring system in the electricity theft area to monitor each area with an electricity theft risk value higher than the threshold, so as to determine whether there will still be electricity theft behavior; Enter the information of all electricity theft personnel with electricity theft behavior in the electricity theft area into the database, determine them as high-risk personnel, and conduct verification in sequence according to the risk level when electricity theft behavior occurs again.

7. The method for hydropower safety monitoring based on the Internet of Things according to claim 1, characterized in that: The fifth step includes the following content: Step 501: Determine the location of illegal wiring in the electricity theft area. In case of possible leakage, establish a safe area and set up an electronic fence system along the outer edge of the safe area; Step 502: Set up smoke sensors and heat sensors outside the electronic fence system to monitor the energized lines inside the electronic fence system respectively, and output the smoke concentration and temperature data in real time; Step 503: Obtain the temperature data and smoke concentration data, compare them with the warning thresholds respectively. If at least one of them exceeds the threshold, send an alarm to the outside.

8. The method for monitoring the safety of hydropower based on the Internet of Things according to claim 7, characterized in that: After step 503, there is also: Step 504: Obtain the temperature T and the smoke concentration Yw. When both of them do not exceed the threshold, generate a hidden danger assessment value Yp according to the hidden danger assessment strategy; among them, the hidden danger assessment strategy is as follows: Obtain the temperature T and the smoke concentration Yw, perform normalization processing, and synthesize them to form the hidden danger assessment value Yp. The confirmation logic of the pollution assessment value Yp is as follows: ； Among them, , are variable constant parameters. Among them, and , and users can adjust according to the actual situation. The constant correction coefficients of A and B can be corrected according to the actual pollution determination situation.

9. The method for monitoring the safety of hydropower based on the Internet of Things according to claim 8, characterized in that: After step 504, it includes: Step 505: Obtain several groups of hidden danger assessment values. When the current hidden danger assessment value exceeds the corresponding threshold, or when two of the three consecutive predicted values generated based on the quadratic smoothing index exceed the threshold, send an alarm to the outside. Step 506: In steps 503 and 505, if the alarm sent to the outside is not responded within the preset time, cut off the power supply to the electricity theft area emergently.

10. The hydropower safety monitoring system based on the Internet of Things is characterized in that: It includes: Three-dimensional map unit (10): Determine the monitoring area and make an electronic three-dimensional map, determine the high-risk areas from the monitoring area, and mark them on the electronic three-dimensional map. An evaluation and detection unit (20) sequentially evaluates a number of high-risk areas, and based on the evaluation results, uses a drone system to sequentially inspect a number of high-risk zones. After the inspection is completed, other areas are randomly inspected; An installation unit (30) determines the areas where power theft exists based on the inspection results of the drone inspection unit, and sets up an electronic fence system and a video surveillance system in these areas; A confirmation unit (40) determines the areas where power theft may exist or already exists, marks them on a three-dimensional map, and detects these areas. If power theft is detected, after confirmation, it communicates externally; An early warning unit (50) sets up a security monitoring system to monitor the power theft location when it is not convenient to immediately clean up the power theft behavior in the area where power theft exists, and alarms externally and cuts off power emergently when danger occurs or may occur.

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