Power grid equipment unmanned aerial vehicle inspection method

Abstract

The invention provides an unmanned aerial vehicle inspection method for power grid equipment, and the method comprises the steps: calculating the number Kmax of farthest reachable nodes which can return along an inspection planning path after an unmanned aerial vehicle inspection module completes the inspection of the current node power grid equipment; the unmanned aerial vehicle electric energy management module judges whether Kmax is smaller than Kthreshold or not, if yes, power module replacement strategy updating and replacement processing are carried out through the unmanned aerial vehicle communication module, and if not, the unmanned aerial vehicle flight control module flies to the next node according to the routing inspection planning path to carry out power grid equipment routing inspection; the unmanned aerial vehicle communication module updates a power supply module replacement strategy and executes replacement processing; and the unmanned aerial vehicle flight control module performs power grid equipment inspection according to the inspection planning path, and controls the unmanned aerial vehicle to perform return flight charging at the return flight time point. According to the method, Kthreshold redundancy iteration is established based on energy consumption prediction, the electric energy supplementation strategy in the long-distance inspection operation process of the unmanned aerial vehicle of the power grid system is dynamically updated, and the problem of insufficient electric energy supply in the long-distance inspection process is solved.

Description

Technical Field

[0001] The present application relates to the field of drone inspection technology, and in particular to a drone inspection method for power grid equipment. Background Art

[0002] The statements in this section merely provide background technical information related to the present application and do not necessarily constitute prior art.

[0003] With the rapid development of society, all areas of life and work rely more and more on electrical equipment. Electric energy has become an indispensable core supporting force for social development, and power facilities have become key infrastructure for social development.

[0004] In order to ensure the continuous safe and reliable operation of the transmission lines, the power grid operation and management departments need to regularly carry out inspections and maintenance of the power grid system, solve faults and hidden dangers in a timely manner, and prevent them before they happen. At present, my country's power grid lines exceed one million kilometers and cover an extremely wide range. The traditional manual inspection scheme is no longer sustainable and cannot guarantee the effective inspection of the power grid. In the later stage, accident repair and regular maintenance are used to make up for it. Therefore, it is impossible to prevent safety hazards in time, which brings great negative challenges to social life. With the advancement of science and technology, drone inspections have become an effective way to inspect power grid lines. However, the power grid is widely distributed and the tower nodes are scattered in every corner. Therefore, the use of drone inspections will inevitably encounter battery life problems. In order to cope with the battery life problem, the inspection process needs to solve the problem of power supply. The traditional round-trip flight to achieve charging will be unsustainable. In order to overcome the existing problems, the industry has proposed a variety of solutions, including using high-voltage lines to build charging stations, solving the problem of charging alignment, and realizing the purpose of charging by docking drones at charging stations. The power supply is carried out by air-deployed motorboats. When the power is insufficient, the drone contacts the nearest motorboat carrying power, and the motorboat charges the drone in the air.

[0005] The field of UAV power inspection operations is vast. In order to solve the problem of insufficient air endurance, replacing the power supply of UAVs in the air will become a trend in the future. After the low-altitude airspace is widely opened in the future, low-altitude flying objects will develop rapidly. It will become a trend for each aircraft to carry a backup power supply as its own power backup or to provide emergency power supply for third-party flying chess. At that time, how to achieve dynamic matching of two dynamic nodes and realize efficient power supply replacement will be a problem to be solved in the industry. Summary of the invention

[0006] In order to solve the above problems, this application proposes a method for drone inspection of power grid equipment, establishes Kthreshold redundant iteration based on energy consumption prediction, and dynamically updates the power compensation strategy during the long-distance inspection operation of the power grid system drone based on the principle of efficiency first, so as to solve the problem of insufficient power supply during the long-distance inspection process.

[0007] The present application provides a method for unmanned aerial vehicle inspection of power grid equipment, based on an inspection system consisting of an unmanned aerial vehicle inspection module, an unmanned aerial vehicle power management module, an unmanned aerial vehicle communication module, and an unmanned aerial vehicle flight control module, comprising the following steps;

[0008] Step 1: After completing the inspection of the power grid equipment at the current node, the UAV inspection module calculates the farthest reachable node number Kmax along the inspection planning path;

[0009] Step 2: The UAV power management module determines whether Kmax is less than the preset threshold value Kthreshold.

[0010] If yes, go to step 3.

[0011] If not, jump to step 4;

[0012] Step 3: The drone communication module broadcasts the power supply replacement requirement, and then determines whether a response is received within the preset time T.

[0013] If yes, the power module replacement strategy is updated according to the efficiency optimization principle, and the replacement process is performed, and then jump to step 4.

[0014] If not, determine whether Kmax is 0. If so, jump to step 5. If not, jump to step 4.

[0015] Step 4: The UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment;

[0016] Step 5: The drone flight control module controls the drone to return and charge.

[0017] Preferably, in step 1, the calculation method of the farthest reachable node number Kmax is:

[0018] Step 1.1: The UAV inspection module calculates the average inspection energy consumption CostSiteAvg and the unit distance navigation energy consumption CostPerDistance of the N nodes before the current node, where N is the preset value;

[0019] Step 1.2: The drone inspection module calculates the energy consumption value CostGo(r) after inspecting each node on the remaining path and returning according to the inspection planning path. The value of r is 1, ..., R, where R is the number of remaining inspection nodes and r is the number of the remaining inspection nodes.

[0020] CostGo(r)=r*CostSiteAvg+(Distance(r)+ReturnFlyDistance(r))*CostPerDistance,

[0021] Where Distance(r) is the flight distance from the current node to the node r on the remaining inspection path, and ReturnFlyDistance(r) is the flight distance required for the node r on the remaining inspection path to return;

[0022] Step 1.3, the UAV inspection module selects the r value with the largest CostGo(r) value that does not exceed SueplusEnergy from the r values ​​of 1, ..., R. The corresponding r value is the farthest reachable node number Kmax, and SueplusEnergy is the current remaining energy value of the UAV.

[0023] Preferably, in step 3, the content of the broadcast of the power supply replacement requirement by the drone communication module at least includes:

[0024] Requester ID, current location coordinates, power module model, and upper limit of broadcast response time;

[0025] The response shall at least include:

[0026] The responder's identity ID, current location coordinates, planned navigation route, navigation speed, and remaining power of the supported power module.

[0027] Preferably, the responder sends a message response after determining that it can support the replacement of the power module of the current drone. If the replacement cannot be supported, no response message is sent.

[0028] Preferably, in step 3, the specific method of the UAV communication module updating the power module replacement strategy and executing the replacement process is as follows:

[0029] Step 3.1, the drone communication module receives the power supply replacement broadcast response information and forms a response list ListRsp;

[0030] Step 3.2: The drone communication module determines whether ListRsp is empty.

[0031] If yes, go to step 3.4.

[0032] If not, take out an element Y from ListRsp, delete Y from ListRsp, and then jump to step 3.3;

[0033] Step 3.3, the UAV communication module calculates the time OptTime(p) taken for the current node to patrol to node p, where p takes values ​​of 0, 1, ..., Kmax, and when p takes a value of 0, it represents the current node;

[0034] Calculate the position coordinates Axis(p) of Y after OptTime(p) according to the current position coordinates, navigation planned route, and navigation speed in the response message, and then calculate the distance between node p and Axis(p) to obtain Distance(p);

[0035] From the values ​​of p of 0, 1, ..., Kmax, select the p value with the smallest Distance(p) and assign it to p_min, store {the ID corresponding to Y, the remaining power of the supporting power module, the absolute number of the node, Distance(p_min)} into the queue ListSupport, where the absolute number of the node is the node number p_min corresponding to the unified number of nodes on the inspection planning path, and then jump to step 3.2;

[0036] Step 3.4: The UAV communication module checks whether there is a node with the absolute number of the current node in ListSupport.

[0037] If it exists, the preset efficiency optimization method is used to perform the power supply replacement operation.

[0038] If it does not exist, the node does not perform power supply replacement processing.

[0039] Preferably, in step 3.4, the specific method for the drone communication module to perform the power supply replacement processing operation using the preset efficiency optimization method is:

[0040] Store all elements whose node absolute number is the current node into ListDo, and then use any of the following methods to perform the power supply replacement operation:

[0041] Method 1:

[0042] Determine whether there is a situation in ListDo where the "remaining power of the supporting power module" is greater than CostGo(R),

[0043] If it exists, select the drone ID corresponding to the element with the smallest Distance (p_min) from the elements greater than CostGo (R), and perform a power replacement processing operation with the drone, wherein the power replacement processing operation includes the requester sending a power replacement execution request command to the drone corresponding to the identity ID, the responder replies with a response execution, and then the requester waits at the current node for the response method to come and replace the power module, and then clears ListSupport and ListDo;

[0044] If it does not exist: select the ID of the drone with the largest "remaining power of the supporting power module" from the candidate elements, and perform the power replacement processing operation with the drone, and then clear ListSupport and ListDo;

[0045] Method 2:

[0046] Select the ID of the drone with the largest "remaining power of the supporting power module" from the candidate elements, and perform the power replacement operation with the drone, and then clear ListSupport and ListDo;

[0047] Method 3:

[0048] Select the ID of the drone with the smallest "Distance(p_min)" from the candidate elements, perform the power replacement processing operation with the drone, and then clear ListSupport and ListDo.

[0049] Compared with the prior art, the beneficial effects of this application are:

[0050] The present application establishes Kthreshold redundant iteration based on energy consumption prediction, and based on the principle of efficiency first, dynamically updates the power compensation strategy for the long-distance inspection operation process of the power grid system UAV, realizes iterative matching between dynamic nodes, and performs power module replacement processing based on the optimal result obtained by iteration, effectively solving the problem of insufficient power supply during the long-distance inspection process. The present invention can effectively improve the efficiency of long-distance inspection of power grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] The drawings in the specification, which constitute a part of the present application, are used to provide further understanding of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute improper limitations on the present application.

[0052] Figure 1 The method flow diagram of this application is as follows:

[0053] Figure 2 The following is a schematic diagram of the system composition of this application. DETAILED DESCRIPTION

[0054] The present application is further described below in conjunction with the accompanying drawings and embodiments.

[0055] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0056] In the present disclosure, terms such as "upper", "lower", "left", "right", "front", "back", "vertical", "horizontal", "side", "bottom" and the like indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. They are relational words determined only for the convenience of describing the structural relationships of the various parts or elements of the present disclosure, and do not specifically refer to any part or element in the present disclosure and should not be understood as limitations on the present disclosure.

[0057] Example 1

[0058] like Figure 1 to Figure 2 As shown, the present application provides a power grid equipment drone inspection system, including a drone inspection module, a drone power management module, a drone communication module, and a drone flight control module. The functions of each module are as follows:

[0059] The UAV inspection module calculates the farthest reachable node number Kmax along the inspection planning path after completing the inspection of the current node power grid equipment;

[0060] The UAV power management module determines whether Kmax is less than Kthreshold. If so, the UAV communication module updates the power module replacement strategy and performs the replacement process. If not, the UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment.

[0061] The UAV communication module is responsible for updating the power module replacement strategy and executing the replacement process;

[0062] The UAV flight control module is responsible for inspecting the power grid equipment according to the inspection plan route, and controlling the UAV to return and charge at the return time.

[0063] Based on the above inspection system, the present application also provides a power grid equipment drone inspection method, including the following steps:

[0064] Step 1: After completing the inspection of the power grid equipment at the current node, the UAV inspection module calculates the farthest reachable node number Kmax along the inspection planning path;

[0065] Step 2: The UAV power management module determines whether Kmax is less than the preset threshold value Kthreshold.

[0066] If yes, go to step 3.

[0067] If not, jump to step 4;

[0068] Step 3: The drone communication module broadcasts the power supply replacement requirement, and then determines whether a response is received within the preset time T.

[0069] If yes, the power module replacement strategy is updated according to the efficiency optimization principle, and the replacement process is performed, and then jump to step 4.

[0070] If not, determine whether Kmax is 0. If so, jump to step 5. If not, jump to step 4.

[0071] Step 4: The UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment;

[0072] Step 5: The drone flight control module controls the drone to return and charge.

[0073] Specifically, in step 1, the calculation method of the farthest reachable node number Kmax is:

[0074] Step 1.1: The UAV inspection module calculates the average inspection energy consumption CostSiteAvg and the unit distance navigation energy consumption CostPerDistance of the N nodes before the current node, where N is the preset value;

[0075] Step 1.2: The UAV inspection module calculates the energy consumption value CostGo(r) after inspecting each node on the remaining path and returning according to the inspection planning path. The value of r is 1, ..., R, where R is the number of remaining inspection nodes and r is the number of remaining inspection nodes. CostGo(r) = r*CostSiteAvg+(Distance(r)+ReturnFlyDistance(r))*CostPerDistance, where Distance(r) is the flight distance from the current node to the node r on the remaining inspection path, and ReturnFlyDistance(r) is the flight distance required for returning to the node r on the remaining inspection path.

[0076] Step 1.3, the UAV inspection module selects the r value with the largest CostGo(r) value that does not exceed SueplusEnergy from the r values ​​of 1, ..., R. The corresponding r value is the farthest reachable node number Kmax, and SueplusEnergy is the current remaining energy value of the UAV.

[0077] Specifically, in step 3, the content of the broadcast of the power supply replacement requirement by the drone communication module at least includes:

[0078] Requester ID, current location coordinates, power module model, and upper limit of broadcast response time;

[0079] The response shall at least include:

[0080] The responder's identity ID, current location coordinates, planned navigation route, navigation speed, and remaining power of the supported power module.

[0081] Preferably, the responder sends a message response after determining that it can support the replacement of the power module of the current drone. If the replacement cannot be supported, no response message is sent.

[0082] Specifically, in step 3, the specific method for the drone communication module to update the power module replacement strategy and perform the replacement process is as follows:

[0083] Step 3.1, the drone communication module receives the power supply replacement broadcast response information and forms a response list ListRsp;

[0084] Step 3.2: The drone communication module determines whether ListRsp is empty.

[0085] If yes, go to step 3.4.

[0086] If not, take out an element Y from ListRsp, delete Y from ListRsp, and then jump to step 3.3;

[0087] Step 3.3, the UAV communication module calculates the time OptTime(p) taken for the current node to patrol to node p, where p takes values ​​of 0, 1, ..., Kmax, and when p takes a value of 0, it represents the current node;

[0088] Calculate the position coordinates Axis(p) of Y after OptTime(p) according to the current position coordinates, navigation planned route, and navigation speed in the response message, and then calculate the distance between node p and Axis(p) to obtain Distance(p);

[0089] From the values ​​of p of 0, 1, ..., Kmax, select the p value with the smallest Distance(p) and assign it to p_min, store {the ID corresponding to Y, the remaining power of the supporting power module, the absolute number of the node, Distance(p_min)} into the queue ListSupport, where the absolute number of the node is the node number p_min corresponding to the unified number of nodes on the inspection planning path, and then jump to step 3.2;

[0090] Step 3.4: The UAV communication module checks whether there is a node with the absolute number of the current node in ListSupport.

[0091] If it exists, the preset efficiency optimization method is used to perform the power supply replacement operation.

[0092] If it does not exist, the node does not perform power supply replacement processing.

[0093] Specifically, in step 3.4, the specific method for the drone communication module to perform the power supply replacement processing operation using the preset efficiency optimization method is:

[0094] Store all elements whose node absolute number is the current node into ListDo, and then use any of the following methods to perform the power supply replacement operation:

[0095] Method 1:

[0096] Determine whether there is a situation in ListDo where the "remaining power of the supporting power module" is greater than CostGo(R),

[0097] If it exists, select the drone ID corresponding to the element with the smallest Distance (p_min) from the elements greater than CostGo (R), and perform a power replacement processing operation with the drone, wherein the power replacement processing operation includes the requester sending a power replacement execution request command to the drone corresponding to the identity ID, the responder replies with a response execution, and then the requester waits at the current node for the response method to come and replace the power module, and then clears ListSupport and ListDo;

[0098] If it does not exist: select the ID of the drone with the largest "remaining power of the supporting power module" from the candidate elements, and perform the power replacement processing operation with the drone, and then clear ListSupport and ListDo;

[0099] Method 2:

[0100] Select the ID of the drone with the largest "remaining power of the supporting power module" from the candidate elements, and perform the power replacement operation with the drone, and then clear ListSupport and ListDo;

[0101] Method 3:

[0102] Select the ID of the drone with the smallest "Distance(p_min)" from the candidate elements, perform the power replacement processing operation with the drone, and then clear ListSupport and ListDo.

[0103] The following is a detailed description of the implementation of the present application:

[0104] Assume that the power grid inspection route includes 100 nodes, each node corresponds to a power tower, and this embodiment takes the inspection to the 60th node, and then determines whether Kmax is less than Kthreshold at the current node as an example for explanation, where Kthreshold is preset to 5. The specific implementation process is as follows:

[0105] First, according to step 1, after completing the inspection of the power grid equipment at the current node (the 60th node), the UAV inspection module calculates the farthest reachable node number Kmax that can be returned along the inspection planning path. The specific calculation method is as follows:

[0106] According to step 1.1, the UAV inspection module calculates the average inspection energy consumption CostSiteAvg and the unit distance navigation energy consumption CostPerDistance of the N node power grid equipment before the current node;

[0107] Next, according to step 1.2, the UAV inspection module calculates the energy consumption value CostGo(r) after inspecting each node on the remaining path and returning according to the inspection planning path. The value of r is 1, ..., R, where R is the number of remaining inspection nodes. In this embodiment, since this node is the 60th node and there are a total of 100 nodes, the value of R is 40, and r is the number of the remaining inspection nodes. CostGo(r) = r*CostSiteAvg+(Distance(r)+ReturnFlyDistance(r))*CostPerDistance, where Distance(r) is the navigation distance from the current node to the node r on the remaining inspection path, and ReturnFlyDistance(r) is the navigation distance required for returning to the node r on the remaining inspection path.

[0108] Then, according to step 1.3, the UAV inspection module selects the r value with the largest CostGo(r) value that does not exceed the r value corresponding to SueplusEnergy from r values ​​of 1, ..., R, where r is the farthest reachable node number Kmax, and SueplusEnergy is the current remaining energy value of the UAV. In this embodiment, it is assumed that the calculation result Kmax is 5.

[0109] Next, according to step 2, the UAV power management module determines whether Kmax is less than Kthreshold. In this embodiment, the determination result is no, so the process jumps to step 4.

[0110] Then, according to step 4, the UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment, and now flies to the 61st node.

[0111] Then, according to step 1, after completing the inspection of the power grid equipment at the current node (i.e., the 61st node), the drone inspection module calculates the farthest number of nodes Kmax that can be reached along the inspection planning path. The calculation method of Kmax is as above. Assuming the calculation result here, Kmax takes a value of 4.

[0112] Next, according to step 2, the UAV power management module determines whether Kmax is less than Kthreshold. The result of this determination is yes, so the process jumps to step 3.

[0113] Next, according to step 3, the drone communication module broadcasts the power supply replacement requirement, and then determines whether a response is received within the preset time T. After the broadcast, the present embodiment receives responses from two drones, which are drones with drone identification IDs 1 and 2, respectively. The remaining power of the power supply modules of the two drones is fully loaded. Next, the power supply module replacement strategy is updated according to the efficiency optimization principle, and the replacement process is executed. The specific processing process is as follows:

[0114] Next, according to step 3.1, the drone communication module receives the power supply replacement broadcast response information and forms a response list ListRsp. At this time, the response list includes two elements, which are two drones with drone identity IDs 1 and 2 respectively;

[0115] Next, according to step 3.2, the drone communication module determines whether ListRsp is empty. If the result is no, an element Y is taken out from ListRsp and Y is deleted from ListRsp. Assuming that the drone with ID 1 is taken out first and then deleted from ListRsp, only the drone with ID 2 is left in ListRsp, and then jump to step 3.3;

[0116] Then, according to step 3.3, the UAV communication module calculates the time OptTime(p) taken by the current node to patrol to node p, where p takes values ​​of 0, 1, ..., Kmax, and p takes a value of 0 to represent the current node. The position coordinates Axis(p) of Y after OptTime(p) are calculated according to the current position coordinates, navigation planning route, and navigation speed in the response message, and then the distance between node p and Axis(p) is calculated to obtain Distance(p), and then the p value with the smallest Distance(p) is selected from the p values ​​of 0, 1, ..., Kmax and assigned to p_min, and {the identity ID corresponding to Y, the remaining power of the supporting power module, the absolute number of the node, and Distance(p_min)} are stored in the queue ListSupport. In this embodiment, it is assumed that the calculation result is {the identity ID is 1, the remaining power of the supporting power module is fully loaded, the absolute number of the node is 62, and the Distance(p_min) is 2000 meters}, and the absolute number of the node is 62, which is equivalent to the value of p being 1, and then jump to step 3.2;

[0117] Next, according to step 3.2, the drone communication module determines whether ListRsp is empty. If the result is no, an element Y is taken out from ListRsp and Y is deleted from ListRsp. Only one element is taken out here, that is, the drone with ID 2 nearby, and then it is deleted from ListRsp. ListRsp is empty, and then jump to step 3.3;

[0118] Next, according to step 3.3, the UAV communication module calculates the time OptTime(p) taken by the current node to patrol to node p, where p takes values ​​of 0, 1, ..., Kmax, and p takes a value of 0 to represent the current node. Y is calculated according to the current location coordinates, navigation planning route, and navigation speed in the response message, and the location coordinates Axis(p) after OptTime(p) time. Then, the distance between node p and Axis(p) is calculated to obtain Distance(p), and then Distance(p) is selected from the values ​​of p of 0, 1, ..., Kmax. The smallest p value of tance(p) is assigned to p_min, and {the identity ID corresponding to Y, the remaining power of the supporting power module, the absolute number of the node, and Distance(p_min)} are stored in the queue ListSupport. In this embodiment, it is assumed that the calculation result is {the identity ID is 2, the remaining power of the supporting power module is fully loaded, the absolute number of the node is 63, and the Distance(p_min) is 1000 meters}. The absolute number of the node is 63, which is equivalent to the value of p being 2. At this time, ListSupport already includes two elements:

[0119] {The ID is 1, the remaining power of the supporting power module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 2000 meters}

[0120] {The ID is 2, the remaining power of the supporting power module is fully loaded, the node absolute number is 63, and the Distance (p_min) is 1000 meters}

[0121] Then jump to step 3.2;

[0122] Next, according to step 3.2, the drone communication module determines whether ListRsp is empty. If it is, it jumps to step 3.4;

[0123] Next, according to step 3.4, the UAV communication module checks whether there is a node in ListSupport with an absolute number of the current node. If the result of the determination does not exist, the node does not perform the power supply replacement process.

[0124] Then jump to step 4. According to step 4, the UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment, that is, flies to the 62nd node for inspection.

[0125] Then, according to step 1, after completing the inspection of the power grid equipment at the current node (the 62nd node), the drone inspection module calculates the farthest reachable node number Kmax that can be returned along the inspection planning path, assuming that the calculation result here is 3.

[0126] Next, according to step 2, the UAV power management module determines whether Kmax is less than Kthreshold. If the determination result is yes, it jumps to step 3.

[0127] Next, according to step 3, the UAV communication module broadcasts the power supply replacement requirement, and then determines whether a response is received within the preset time T. If the determination result is yes, the power supply module replacement strategy is updated according to the efficiency optimization principle. The execution process is the same as the 61st node, and no further description is given. Assume that the execution result is: the element {identity ID is 3, the remaining power of the supporting power supply module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 300 meters} is written into ListSupport, then ListSupport now includes three elements as follows:

[0128] {The ID is 1, the remaining power of the supporting power module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 2000 meters},

[0129] {The ID is 2, the remaining power of the supporting power module is fully loaded, the node absolute number is 63, and the Distance (p_min) is 1000 meters},

[0130] {The ID is 3, the remaining power of the supporting power module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 300 meters};

[0131] Next, according to step 3.4, the UAV communication module checks whether there is a node with an absolute number of the current node in ListSupport. Since the current node is 62, there are two elements in ListSupport with an absolute number of 62. The result is yes, and all elements with an absolute number of the current node are stored in ListDo. That is, ListDo includes the following two elements:

[0132] {The ID is 1, the remaining power of the supporting power module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 2000 meters}

[0133] {The identification ID is 3, the remaining power of the supporting power module is fully loaded, the node absolute number is 62, and the Distance (p_min) is 300 meters}.

[0134] Then, use any of the following methods to perform the power supply replacement operation, assuming that method three is used in this embodiment:

[0135] Then select the drone ID with the smallest "Distance(p_min)" from the two candidate elements. In this embodiment, since the Distance(p_min) of the drone ID 1 is 2000 meters, and the Distance(p_min) of the drone ID 3 is 300 meters, the selection result is to select the drone ID 3 to perform the power replacement operation. Therefore, the drone and the drone ID 3 perform the power replacement processing operation, and then clear ListSupport and ListDo.

[0136] At this point, the drone power supply replacement is completed.

[0137] It can be seen from this embodiment that Kthreshold is set to 5 in this embodiment. Therefore, the drone starts to select the feasibility of power replacement with the third-party drone from the first 5 nodes after the endurance is consumed. For each third-party drone that has responded, this drone finds the optimal aggregation node according to the navigation route of this drone and the navigation route of the third-party drone, so that the navigation cost of the same third-party drone for power replacement of this drone is minimized, and the optimal aggregation nodes of all third-party drones are recorded and recorded in ListSupport. Before reaching the optimal aggregation node, the continuous optimization selection of the feasibility of power update of the third-party drone is maintained, and the information is continuously summarized in ListSupport. Finally, after reaching the node where power replacement can be executed, the optimal aggregation node is selected from the summary list ListSupport as the element of this node, stored in ListDo, and the third-party drone that executes the power replacement is determined by selecting the best from ListDo, thereby ensuring that the power input of the power replacement is optimal and the third-party navigation cost is minimized, thereby achieving the goal of efficiency priority.

[0138] The method of the present invention is adopted, based on energy consumption prediction, by establishing Kthreshold redundant iteration, based on the principle of efficiency priority, the power compensation strategy of the long-distance inspection operation process of the unmanned aerial vehicle of the power grid system is dynamically updated, so as to realize iterative matching between dynamic nodes, and execute the power module replacement processing based on the optimal result obtained by iteration, so as to effectively solve the problem of insufficient power supply in the long-distance inspection process. The present invention can effectively improve the efficiency of long-distance inspection of power grids.

[0139] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0140] Although the above describes the specific implementation methods of the present application in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present application. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present application, various modifications or variations that can be made by technical personnel in this field without creative work are still within the scope of protection of the present application.

Claims

1. A method for inspecting power grid equipment by using a drone, characterized in that: The inspection system based on the UAV inspection module, the UAV power management module, the UAV communication module and the UAV flight control module includes the following steps; Step 1: After completing the inspection of the power grid equipment at the current node, the UAV inspection module calculates the farthest reachable node number Kmax along the inspection planning path; Step 2: The UAV power management module determines whether Kmax is less than the preset threshold value Kthreshold. If yes, go to step 3. If not, jump to step 4; Step 3: The drone communication module broadcasts the power supply replacement requirement, and then determines whether a response is received within the preset time T. If yes, the power module replacement strategy is updated according to the efficiency optimization principle, and the replacement process is performed, and then jump to step 4. If not, determine whether Kmax is 0. If so, jump to step 5. If not, jump to step 4. Step 4: The UAV flight control module flies to the next node according to the inspection planning path to inspect the power grid equipment; Step 5: The drone flight control module controls the drone to return and charge.

2. A method for inspecting power grid equipment by drone according to claim 1, characterized in that: In step 1, the calculation method of the farthest reachable node number Kmax is: Step 1.1: The UAV inspection module calculates the average inspection energy consumption CostSiteAvg and the unit distance navigation energy consumption CostPerDistance of the N nodes before the current node, where N is the preset value; Step 1.2: The drone inspection module calculates the energy consumption value CostGo(r) after inspecting each node on the remaining path and returning according to the inspection planning path. The value of r is 1, ..., R, where R is the number of remaining inspection nodes and r is the number of the remaining inspection nodes. CostGo(r)=r*CostSiteAvg+(Distance(r)+ReturnFlyDistance(r))*CostPerDistance, Where Distance(r) is the flight distance from the current node to the node r on the remaining inspection path, and ReturnFlyDistance(r) is the flight distance required for the node r on the remaining inspection path to return; Step 1.3, the UAV inspection module selects the r value with the largest CostGo(r) value that does not exceed SueplusEnergy from the r values ​​of 1, ..., R. The corresponding r value is the farthest reachable node number Kmax, and SueplusEnergy is the current remaining energy value of the UAV.

3. A method for inspecting power grid equipment by drone according to claim 1, characterized in that: In step 3, the broadcast content of the power supply replacement requirement broadcast by the drone communication module at least includes: Requester ID, current location coordinates, power module model, and upper limit of broadcast response time; The response shall at least include: The responder's identity ID, current location coordinates, planned navigation route, navigation speed, and remaining power of the supported power module.

4. A method for inspecting power grid equipment by using a drone according to claim 3, characterized in that: The responder sends a message response after determining that it can support the replacement of the power module of the current drone. If it cannot support the replacement, no response message is sent.

5. A method for inspecting power grid equipment by using an unmanned aerial vehicle according to any one of claims 1, 3 and 4, characterized in that: In step 3, the specific method for the UAV communication module to update the power module replacement strategy and perform the replacement process is as follows: Step 3.1, the drone communication module receives the power supply replacement broadcast response information and forms a response list ListRsp; Step 3.2: The drone communication module determines whether ListRsp is empty. If yes, go to step 3.

4. If not, take out an element Y from ListRsp, delete Y from ListRsp, and then jump to step 3.3; Step 3.3, the UAV communication module calculates the time consumed by the current node to patrol to node p, OptTime(p), where p takes values ​​of 0, 1, ..., Kmax, and when p takes a value of 0, it represents the current node; Calculate the position coordinates Axis(p) of Y after OptTime(p) according to the current position coordinates, navigation planned route, and navigation speed in the response message, and then calculate the distance between node p and Axis(p) to obtain Distance(p); From the values ​​of p of 0, 1, ..., Kmax, select the p value with the smallest Distance(p) and assign it to p_min, store {the ID corresponding to Y, the remaining power of the supporting power module, the absolute number of the node, Distance(p_min)} into the queue ListSupport, where the absolute number of the node is the node number p_min corresponding to the unified number of nodes on the inspection planning path, and then jump to step 3.2; Step 3.4: The UAV communication module checks whether there is a node with the absolute number of the current node in ListSupport. If it exists, the preset efficiency optimization method is used to perform the power supply replacement operation. If it does not exist, the node does not perform power supply replacement processing.

6. A method for inspecting power grid equipment by using a drone according to claim 5, characterized in that: In step 3.4, the specific method for the UAV communication module to perform the power supply replacement processing operation using the preset efficiency optimization method is: Store all elements whose node absolute number is the current node into ListDo, and then use any of the following methods to perform the power supply replacement operation: Method 1: Determine whether there is a situation in ListDo where the "remaining power of the supporting power module" is greater than CostGo(R), If it exists, select the drone ID corresponding to the element with the smallest Distance (p_min) from the elements greater than CostGo (R), and perform a power replacement processing operation with the drone, wherein the power replacement processing operation includes the requester sending a power replacement execution request command to the drone corresponding to the identity ID, the responder replies with a response execution, and then the requester waits at the current node for the response method to come and replace the power module, and then clears ListSupport and ListDo; If it does not exist: select the ID of the drone with the largest "remaining power of the supported power module" from the candidate elements, and perform the power replacement operation with the drone, and then clear ListSupport and ListDo; Method 2: Select the ID of the drone with the largest "support power module remaining power" from the candidate elements, perform the power replacement operation with the drone, and then clear ListSupport and ListDo; Method 3: Select the drone ID with the smallest "Distance(p_min)" from the candidate elements, perform the power replacement processing operation with the drone, and then clear ListSupport and ListDo.

Images