An intelligent autonomous inspection system for power distribution lines using drones

Abstract

The present invention relates to the field of unmanned aerial vehicle inspection technology, and in particular to an intelligent autonomous inspection system for distribution line unmanned aerial vehicles, comprising: a node positioning module, a unmanned aerial vehicle inspection module, a path planning module, a plan customization module, a data receiving module, a cloud server and a central control module. The specific situation of the unmanned aerial vehicle inspection is determined according to the actual inspection time of the unmanned aerial vehicle. When it is determined that the operation of the unmanned aerial vehicle inspection module is abnormal, the operation of the unmanned aerial vehicle is regulated according to the abnormal proportion, the moving speed of each unmanned aerial vehicle is adjusted to a corresponding value, the planned inspection time is corrected, or a charging instruction for the corresponding unmanned aerial vehicle is issued, thereby improving the inspection efficiency of the unmanned aerial vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle inspection, and in particular to an intelligent autonomous unmanned aerial vehicle inspection system for power distribution lines. Background Art

[0002] Cables have a specified service life, but in the course of daily use, they may experience external damage, insulation moisture, chemical corrosion, long-term overload operation, cable joint failure, and the external environment and heat source in which the cable is located causing the cable temperature to be too high, insulation breakdown, etc. These phenomena will cause the cable to age prematurely and create safety hazards. Therefore, it is necessary to conduct regular inspections of the cables to determine the degree of aging of each part of the cable.

[0003] Chinese patent publication number: CN112607022A, discloses a power transmission and distribution line inspection device, including: a drone, a first connecting rod is fixed on the drone body, and a first support plate is fixed at the end of the first connecting rod. A cable detection device is arranged in the middle of the top of the first support plate. The cable detection device includes: an arc plate and an ultrasonic probe. An end plate is fixed below each of the two axial ends of the arc plate, the bottom of the end plate is fixedly connected to the first support plate, at least one support ring is fixedly connected below the arc plate, and a plurality of second sleeves are radially fixed on the support ring, a second sliding rod is inserted inside the second sleeve, and a second spring is sleeved on the second sleeve and the outside of the second sliding rod. The bottom of the ultrasonic probe is fixedly connected to the top of the second sliding rod, and the top of the ultrasonic probe passes through the arc plate and is above the arc plate. The ultrasonic probe is electrically connected to the internal control device of the drone; it can be seen that the above technical solution has the following problems: it is impossible to determine the specific situation of the drone inspection according to the actual inspection time of the drone, and it is impossible to regulate the operation of the drone according to the specific situation of the drone inspection, which affects the inspection efficiency of the drone. Summary of the invention

[0004] To this end, the present invention provides a distribution line drone intelligent autonomous inspection system to overcome the problem in the prior art that the specific circumstances of the drone inspection cannot be determined based on the actual inspection time of the drone, and the operation of the drone cannot be regulated based on the specific circumstances of the drone inspection, thus affecting the inspection efficiency of the drone.

[0005] To achieve the above object, the present invention provides a distribution line drone intelligent autonomous inspection system, comprising:

[0006] Node positioning module, which is used to store the location information of each inspection point;

[0007] The drone inspection module includes: a number of drones for inspecting various inspection points;

[0008] A path planning module, which is connected to the node positioning module and the drone inspection module respectively, and is used to determine the inspection route of each drone based on the location information of each inspection point;

[0009] A planning customization module, which is connected to the path planning module, is used to determine the planned inspection time of each drone for each inspection point based on the inspection route and the inspection start time;

[0010] A data receiving module, which is connected to the drone inspection module and the plan customization module, and is used to obtain the actual inspection time and inspection information of each drone for the corresponding inspection point;

[0011] A cloud server, which is respectively connected to the node positioning module, the drone inspection module, the path planning module, the plan customization module and the data receiving module, and is used to store historical data of each module;

[0012] The central control module is respectively connected to the cloud server, the UAV inspection module, the path planning module and the plan customization module, and is used to determine the delay deviation parameter for a single inspection point according to the actual inspection time and the planned inspection time of the inspection point, to determine the historical delay difference based on the delay deviation parameters of the single inspection point in the historical data, to determine whether the operation of the UAV inspection module is qualified in combination with the delay deviation parameter and the historical delay difference, and to mark a single inspection point as an abnormal node when it is determined that the operation of the UAV inspection module is abnormal. The central control module completes the one-by-one judgment of each inspection point, and determines the abnormal proportion based on the number of abnormal nodes under the condition that there are abnormal nodes, and processes the UAV inspection module based on the abnormal proportion, including: adjusting the moving speed of each UAV to the corresponding value, correcting each planned inspection time, or issuing a charging instruction for the corresponding UAV.

[0013] Furthermore, for a single inspection point, the central control module is used to determine the delay deviation parameter for the inspection point based on the actual inspection time and the planned inspection time;

[0014] It is used to solve the difference between the actual inspection time and the planned inspection time to obtain the delay deviation parameter;

[0015] The central control module is used to determine whether the operation of the drone inspection module is qualified based on the delay deviation parameter, including:

[0016] If the delay deviation parameter is less than or equal to the first preset delay deviation parameter, the operation of the drone inspection module is determined to be qualified, and the drone inspection module is controlled to continue to operate using the current operating parameters;

[0017] If the delay deviation parameter is less than or equal to the second preset delay deviation parameter and greater than the first preset delay deviation parameter, then determine whether the operation of the drone inspection module is qualified in combination with the historical delay difference;

[0018] If the delay deviation parameter is greater than the second preset delay deviation parameter, the operation of the drone inspection module is determined to be abnormal, and the single inspection point is marked as an abnormal node.

[0019] Furthermore, the central control module is used to determine whether the operation of the drone inspection module is qualified based on the historical delay difference, including:

[0020] It is used to obtain and determine the historical delay difference, solve the variance of each delay deviation parameter of a single inspection point in the historical data, and obtain the historical delay difference;

[0021] If the historical delay difference is less than or equal to the preset historical delay difference, the operation of the drone inspection module is determined to be qualified, and the first preset delay deviation parameter is adjusted to a corresponding value based on the historical delay difference;

[0022] If the historical delay difference is greater than the preset historical delay difference, the operation of the drone inspection module is judged to be abnormal, and the single inspection point is marked as an abnormal node.

[0023] Further, the central control module is used to adjust the first preset delay deviation parameter to a corresponding value based on the historical delay difference, wherein:

[0024] The increase range of the first preset delay deviation parameter determined based on the historical delay difference is inversely proportional to the historical delay difference.

[0025] Furthermore, the central control module processes the drone inspection module based on the abnormality ratio, including:

[0026] To determine the abnormal proportion, solve the ratio of the number of abnormal nodes to the total number of inspection points to obtain the abnormal proportion;

[0027] If the abnormality ratio is less than or equal to the first preset abnormality ratio, the moving speed of the single UAV is adjusted to the corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV;

[0028] If the abnormality ratio is less than or equal to the second preset abnormality ratio and greater than the first preset abnormality ratio, a relative deviation-inspection point curve is drawn based on the relative deviation, and the peak point distribution parameters are determined based on the inspection point-relative deviation curve, and the processing method for the drone inspection module is determined based on the peak point distribution parameters;

[0029] If the abnormality ratio is greater than the second preset abnormality ratio, it is determined that each planned inspection time is adjusted to the corresponding emergency planned inspection time.

[0030] Furthermore, the central control module is used to adjust the moving speed of a single UAV to a corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV, wherein:

[0031] The average value of each delay deviation parameter corresponding to a single UAV is recorded as the deviation mean, and the increase in the movement speed of a single UAV determined based on the deviation mean is proportional to the deviation mean.

[0032] Further, the central control module is used to draw a patrol point-relative deviation curve based on the relative deviation, determine the peak point distribution parameters based on the patrol point-relative deviation curve, and determine the processing method for the drone patrol module based on the peak point distribution parameters, including:

[0033] The central control module is used to determine the relative deviation. For two adjacent inspection points inspected by a single drone, the planned inspection time difference and the actual inspection time difference of the two inspection points are obtained respectively, and the difference between the actual inspection time difference and the planned inspection time difference is calculated to obtain the relative deviation for the second inspection point of the two inspection points.

[0034] The central control module is used to determine the peak point distribution parameter based on the inspection point-relative deviation curve, obtain the distance between each peak point in the inspection point-relative deviation curve, solve the variance of each distance, and obtain the peak point distribution parameter;

[0035] If the peak point distribution parameter is greater than the preset peak point distribution parameter, the moving speed of the single UAV is adjusted to the corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV;

[0036] If the peak point distribution parameter is less than or equal to the preset peak point distribution parameter, the processing method for the drone inspection module is determined based on the actual operating speed.

[0037] Furthermore, for a single drone, the central control module is used to solve the ratio of the mileage of the inspection route of the single drone to the sum of the actual inspection time differences of each adjacent inspection point, and record it as the actual running speed. The central control module determines the processing method for the drone inspection module based on the actual running speed, including:

[0038] If the actual operating speed is greater than the preset actual operating speed, the planned inspection time corresponding to each single drone is adjusted to the corresponding value based on the actual operating speed;

[0039] If the actual operating speed is less than or equal to the preset actual operating speed, a charging instruction is issued to the corresponding drone, and the inspection plan is updated.

[0040] Furthermore, the central control module is used to adjust each planned inspection time corresponding to a single UAV to a corresponding value based on the actual operating speed, wherein:

[0041] The increase in the planned inspection time corresponding to a single UAV determined based on the actual operating speed is inversely proportional to the actual operating speed.

[0042] Furthermore, the central control module adjusts the planned inspection time corresponding to a single inspection point to a corresponding value based on the path distance between the single inspection point and the inspection point of the initial inspection by the drone, under the condition that the adjustment of each planned inspection time based on the actual running speed is completed, wherein:

[0043] The increase in the planned inspection time determined based on the path distance is proportional to the path distance.

[0044] Compared with the prior art, the beneficial effect of the present invention lies in that the specific situation of the drone inspection is determined based on the actual inspection time of the drone. When it is determined that the operation of the drone inspection module is abnormal, the operation of the drone is regulated according to the abnormality ratio, the moving speed of each drone is adjusted to the corresponding value, the planned inspection time is corrected, or a charging instruction is issued for the corresponding drone, thereby improving the inspection efficiency of the drone.

[0045] Furthermore, whether the operation of the UAV inspection module is qualified is determined based on the delay deviation parameter. The delay deviation parameter characterizes the operation delay of a single UAV under actual operation conditions. When the delay deviation parameter is less than or equal to the second preset delay deviation parameter and greater than the first preset delay deviation parameter, there is a short delay in the operation of the UAV, and the UAV may have an operation abnormality that causes inspection delays. In this case, the historical delay difference is obtained to comprehensively determine whether the operation of the UAV inspection module is qualified. The historical delay difference characterizes whether there are similar errors in the historical data for a single inspection point. When the historical delay difference is less than or equal to the preset historical delay difference, in this case, there are similar delay errors for a single inspection point in the historical data. At this time, due to the actual inspection environment, a slight deviation occurs in the planned inspection time. In this case, the first preset delay deviation parameter is adjusted to adjust the judgment benchmark, and the situation for a single inspection point is determined based on the adjusted judgment benchmark. The monitoring conditions for the UAV are determined in a targeted manner based on the actual inspection environment to improve the accuracy of determining the specific situation of the UAV, thereby further improving the inspection efficiency of the UAV.

[0046] Furthermore, based on the abnormality ratio, the processing method of the drone inspection module is developed. The abnormality ratio represents the delay of the drone at each inspection point during the inspection process. When the abnormality ratio is less than or equal to the first preset abnormality ratio, only a small number of inspection points are delayed in inspection. At this time, due to the deviation in path planning, the movement speed of the drone is adjusted to ensure the inspection efficiency; when the abnormality ratio is greater than the second preset abnormality ratio, a large number of inspection points are delayed in inspection due to abnormal weather. In this case, the planned inspection time is adjusted to adapt to the specific conditions of the actual inspection environment, and the parameters of the plan customization module are adjusted to reasonably determine the monitoring parameters for the drone, which further improves the monitoring efficiency of the drone. The drone is efficiently monitored through parameters such as delay deviation parameters, so that the operating parameters of the drone can be adjusted in time when the drone operates abnormally, so as to further improve the stability of the drone operation.

[0047] Furthermore, when the abnormality ratio is less than or equal to the second preset abnormality ratio and greater than the first preset abnormality ratio, the processing method for the drone inspection module is determined in combination with the peak point distribution parameter. The peak point distribution parameter characterizes the distribution of abnormal delays between adjacent inspection points. When the peak point distribution parameter is greater than the preset peak point distribution parameter, the abnormal delay inspection points are scattered. In this case, the actual inspection is delayed due to obstacle interference on the actual inspection path. At this time, the moving speed of a single drone is adjusted to ensure on-time inspection. When the peak point distribution parameter is less than or equal to the preset peak point distribution parameter, there is an abnormal inspection situation in which multiple delays occur in a concentrated area. At this time, due to abnormal power, the inspection of a single area is delayed on a large scale. At this time, the actual operating speed is obtained to determine whether the drone should be charged. When the actual operating speed is greater than the preset actual operating speed, the drone can still continue to run to complete the inspection. The planned inspection time corresponding to a single drone is adjusted to automatically control the monitoring parameters of the drone according to the actual operation of the drone. When the actual operating speed is less than or equal to the preset actual operating speed, the drone is controlled to charge, and the inspection route of the path planning module is updated to ensure that each drone can complete the inspection of the planned inspection points with sufficient power, further improving the inspection efficiency of the drone. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a module block diagram of the power distribution line UAV intelligent autonomous inspection system according to an embodiment of the present invention;

[0049] Figure 2 The present invention is a logic determination diagram for determining whether the operation of the UAV inspection module is qualified based on the delay deviation parameter by the central control module in an embodiment of the present invention. DETAILED DESCRIPTION

[0050] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0051] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0052] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0053] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0054] See also Figure 1 and Figure 2 As shown, they are respectively a module block diagram of a distribution line drone intelligent autonomous inspection system according to an embodiment of the present invention, and a logic determination diagram of whether the operation of the drone inspection module is qualified based on the delay deviation parameter of the central control module; an intelligent autonomous inspection system for distribution lines by drones according to an embodiment of the present invention, comprising:

[0055] Node positioning module, which is used to store the location information of each inspection point;

[0056] The drone inspection module includes: a number of drones for inspecting various inspection points;

[0057] A path planning module, which is connected to the node positioning module and the drone inspection module respectively, and is used to determine the inspection route of each drone based on the location information of each inspection point;

[0058] A planning customization module, which is connected to the path planning module, is used to determine the planned inspection time of each drone for each inspection point based on the inspection route and the inspection start time;

[0059] A data receiving module, which is connected to the drone inspection module and the plan customization module, and is used to obtain the actual inspection time and inspection information of each drone for the corresponding inspection point;

[0060] A cloud server, which is respectively connected to the node positioning module, the drone inspection module, the path planning module, the plan customization module and the data receiving module, and is used to store historical data of each module;

[0061] The central control module is respectively connected to the cloud server, the UAV inspection module, the path planning module and the plan customization module, and is used to determine the delay deviation parameter for a single inspection point according to the actual inspection time and the planned inspection time of the inspection point, to determine the historical delay difference based on the delay deviation parameters of the single inspection point in the historical data, to determine whether the operation of the UAV inspection module is qualified in combination with the delay deviation parameter and the historical delay difference, and to mark a single inspection point as an abnormal node when it is determined that the operation of the UAV inspection module is abnormal. The central control module completes the one-by-one judgment of each inspection point, and determines the abnormal proportion based on the number of abnormal nodes under the condition that there are abnormal nodes, and processes the UAV inspection module based on the abnormal proportion, including: adjusting the moving speed of each UAV to the corresponding value, correcting each planned inspection time, or issuing a charging instruction for the corresponding UAV.

[0062] Specifically, the specific situation of the drone inspection is determined based on the actual inspection time of the drone. When the operation of the drone inspection module is determined to be abnormal, the operation of the drone is regulated based on the abnormal proportion, the movement speed of each drone is adjusted to the corresponding value, the planned inspection time is corrected, or a charging instruction is issued for the corresponding drone, thereby improving the inspection efficiency of the drone.

[0063] Specifically, the detection information includes: line image, location of abnormal heating point and distance between the electrical measuring unit and surrounding objects.

[0064] Specifically, there is no limitation on the specific method of obtaining detection information of each inspection point of the distribution line by the drone. The image of the line can be obtained by a high-definition visible light camera installed on the drone, abnormal heating points can be detected by an infrared thermal imager installed on the drone, and the distance between the line and surrounding objects can be accurately measured by a laser radar installed on the drone. This will not be elaborated here.

[0065] Specifically, there is no limitation on the specific method of determining the inspection route of each drone based on the location information of each inspection point. The main intersection nodes in the distribution line can be identified, and then a retrieval area can be established through these intersection nodes. The distribution line can be divided into several areas, and drones can be assigned to each area. The drone planning algorithm is used to determine the inspection route of the drone for a single area. This will not be repeated here.

[0066] Specifically, there is no limitation on the specific method for determining the inspection time of each UAV for each inspection point based on the inspection route and the inspection start time. It can be determined comprehensively by the standard flight speed of the UAV, the standard detection speed and the path distance. The standard flight speed of the UAV is obtained by performing flight tests on each UAV, and the standard detection speed is obtained by recording when each UAV conducts actual inspections on each inspection point. This is existing technology and will not be elaborated on.

[0067] Specifically, for a single inspection point, the central control module is used to determine the delay deviation parameter for the inspection point based on the actual inspection time and the planned inspection time;

[0068] It is used to solve the difference between the actual inspection time and the planned inspection time to obtain the delay deviation parameter;

[0069] The central control module is used to determine whether the operation of the drone inspection module is qualified based on the delay deviation parameter, including:

[0070] If the delay deviation parameter is less than or equal to the first preset delay deviation parameter, the operation of the drone inspection module is determined to be qualified, and the drone inspection module is controlled to continue to operate using the current operating parameters;

[0071] If the delay deviation parameter is less than or equal to the second preset delay deviation parameter and greater than the first preset delay deviation parameter, then determine whether the operation of the drone inspection module is qualified in combination with the historical delay difference;

[0072] If the delay deviation parameter is greater than the second preset delay deviation parameter, the operation of the drone inspection module is determined to be abnormal, and the single inspection point is marked as an abnormal node.

[0073] Specifically, the first preset delay deviation parameter S1 is selected within the interval [0.08T0 / N, 0.12T0 / N], and the second preset delay deviation parameter S2 is selected within the interval [0.31T0 / N, 0.57T0 / N]. T0 is the difference between the planned inspection time and the inspection start time of the last inspection point in a single inspection by a single UAV determined by the planning customization module, and N is the number of inspection points of a single UAV.

[0074] Specifically, the central control module is used to determine whether the operation of the drone inspection module is qualified based on the historical delay difference, including:

[0075] It is used to obtain and determine the historical delay difference, solve the variance of each delay deviation parameter of a single inspection point in the historical data, and obtain the historical delay difference;

[0076] If the historical delay difference is less than or equal to the preset historical delay difference, the operation of the drone inspection module is determined to be qualified, and the first preset delay deviation parameter is adjusted to a corresponding value based on the historical delay difference;

[0077] If the historical delay difference is greater than the preset historical delay difference, the operation of the drone inspection module is judged to be abnormal, and the single inspection point is marked as an abnormal node.

[0078] Specifically, the preset historical delay difference L0 is selected within the interval [0.63P0, 0.71P0], and P0 is the average value of each delay deviation parameter of a single inspection point in the historical data.

[0079] Specifically, whether the operation of the UAV inspection module is qualified is determined based on the delay deviation parameter. The delay deviation parameter characterizes the operation delay of a single UAV under actual operation conditions. When the delay deviation parameter is less than or equal to the second preset delay deviation parameter and greater than the first preset delay deviation parameter, there is a short delay in the operation of the UAV, and the UAV may have an operation abnormality that causes inspection delays. In this case, the historical delay difference is obtained to comprehensively determine whether the operation of the UAV inspection module is qualified. The historical delay difference characterizes whether there are similar errors in the historical data for a single inspection point. When the historical delay difference is less than or equal to the preset historical delay difference, there are similar delay errors for a single inspection point in the historical data. At this time, due to the actual inspection environment, there is a slight deviation in the planned inspection time. In this case, the first preset delay deviation parameter is adjusted to adjust the judgment benchmark, and the situation for a single inspection point is determined based on the adjusted judgment benchmark. The monitoring conditions for the UAV are determined based on the actual inspection environment to improve the accuracy of determining the specific situation of the UAV, thereby further improving the inspection efficiency of the UAV.

[0080] Specifically, the central control module is used to adjust the first preset delay deviation parameter to a corresponding value based on the historical delay difference, wherein:

[0081] The increase range of the first preset delay deviation parameter determined based on the historical delay difference is inversely proportional to the historical delay difference.

[0082] In this embodiment, optionally,

[0083] Comparing the historical delay difference with a first preset difference comparison threshold and a second preset difference comparison threshold;

[0084] If the historical delay difference is less than or equal to the first preset difference comparison threshold, the first preset delay deviation parameter is adjusted to 1.28 times the initial first preset delay deviation parameter;

[0085] If the historical delay difference is less than or equal to the second preset difference comparison threshold and greater than the first preset difference comparison threshold, the first preset delay deviation parameter is adjusted to 1.21 times the initial first preset delay deviation parameter;

[0086] If the historical delay difference is less than or equal to the second preset difference comparison threshold, the first preset delay deviation parameter is adjusted to 1.11 times the initial first preset delay deviation parameter;

[0087] The first preset difference comparison threshold is 0.42L0, and the second preset difference comparison threshold is 0.89L0.

[0088] Specifically, after completing the adjustment of the first preset delay deviation parameter, the central control module uses the adjusted first preset delay deviation parameter to re-determine whether the operation of the UAV inspection module is qualified based on the delay deviation parameter; if the delay deviation parameter is less than or equal to the adjusted first preset delay deviation parameter, the operation of the UAV inspection module is determined to be qualified, and the UAV inspection module is controlled to continue to run using the current operating parameters; if the delay deviation parameter is greater than the adjusted first preset delay deviation parameter, the operation of the UAV inspection module is determined to be abnormal, and the single inspection point is marked as an abnormal node.

[0089] Specifically, the central control module processes the drone inspection module based on the abnormal proportion, including:

[0090] To determine the abnormal proportion, solve the ratio of the number of abnormal nodes to the total number of inspection points to obtain the abnormal proportion;

[0091] If the abnormality ratio is less than or equal to the first preset abnormality ratio, the moving speed of the single UAV is adjusted to the corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV;

[0092] If the abnormality ratio is less than or equal to the second preset abnormality ratio and greater than the first preset abnormality ratio, a relative deviation-inspection point curve is drawn based on the relative deviation, and the peak point distribution parameters are determined based on the inspection point-relative deviation curve, and the processing method for the drone inspection module is determined based on the peak point distribution parameters;

[0093] If the abnormality ratio is greater than the second preset abnormality ratio, it is determined that each planned inspection time is adjusted to the corresponding emergency planned inspection time.

[0094] Specifically, the first preset abnormality ratio is selected within the interval [0.23, 0.35], and the second preset abnormality ratio is selected within the interval [0.77, 0.86].

[0095] Specifically, in this embodiment, optionally, when it is determined that each planned inspection time is adjusted to the corresponding emergency planned inspection time, each planned inspection time is adjusted to 1.21 times the initial planned inspection time.

[0096] Specifically, the processing method of the drone inspection module is based on the abnormality ratio. The abnormality ratio represents the delay of the drone at each inspection point during the inspection process. When the abnormality ratio is less than or equal to the first preset abnormality ratio, only a small number of inspection points are delayed. At this time, due to the deviation in path planning, the movement speed of the drone is adjusted to ensure the inspection efficiency; when the abnormality ratio is greater than the second preset abnormality ratio, a large number of inspection points are delayed due to abnormal weather. In this case, the planned inspection time will be adjusted to adapt to the specific conditions of the actual inspection environment. The parameters of the plan customization module are adjusted to reasonably determine the monitoring parameters for the drone, further improving the monitoring efficiency of the drone. The drone is efficiently monitored through parameters such as delay deviation parameters, so that the operating parameters of the drone can be adjusted in time when the drone operates abnormally, so as to further improve the stability of the drone operation.

[0097] Specifically, the central control module is used to adjust the moving speed of a single drone to a corresponding value based on the average value of each delay deviation parameter corresponding to the single drone, wherein:

[0098] The average value of each delay deviation parameter corresponding to a single UAV is recorded as the deviation mean, and the increase in the movement speed of a single UAV determined based on the deviation mean is proportional to the deviation mean.

[0099] In this embodiment, optionally,

[0100] Comparing the deviation mean with a first preset mean comparison threshold and a second preset mean comparison threshold;

[0101] If the deviation mean is less than or equal to the first preset mean comparison threshold, the moving speed of the single UAV is adjusted to 1.13 times the initial moving speed;

[0102] If the deviation mean is less than or equal to the second preset mean comparison threshold and greater than the first preset mean comparison threshold, the moving speed of the single UAV is adjusted to 1.21 times the initial moving speed;

[0103] If the deviation mean is greater than the second preset mean comparison threshold, the moving speed of the single UAV is adjusted to 1.29 times the initial moving speed;

[0104] The first preset mean comparison threshold is 1.39S2, and the second preset mean comparison threshold is 1.54S2.

[0105] Specifically, the central control module is used to draw a patrol point-relative deviation curve based on the relative deviation, determine the peak point distribution parameters based on the patrol point-relative deviation curve, and determine the processing method for the drone patrol module based on the peak point distribution parameters, including:

[0106] The central control module is used to determine the relative deviation. For two adjacent inspection points inspected by a single drone, the planned inspection time difference and the actual inspection time difference of the two inspection points are obtained respectively, and the difference between the actual inspection time difference and the planned inspection time difference is calculated to obtain the relative deviation for the second inspection point of the two inspection points.

[0107] The central control module is used to determine the peak point distribution parameter based on the inspection point-relative deviation curve, obtain the distance between each peak point in the inspection point-relative deviation curve, solve the variance of each distance, and obtain the peak point distribution parameter;

[0108] If the peak point distribution parameter is greater than the preset peak point distribution parameter, the moving speed of the single UAV is adjusted to the corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV;

[0109] If the peak point distribution parameter is less than or equal to the preset peak point distribution parameter, the processing method for the drone inspection module is determined based on the actual operating speed.

[0110] Specifically, the preset peak point distribution parameter is selected within the interval [0.04N2, 0.09N2], where N2 is the average value of the distances between the peak points.

[0111] Specifically, for a single drone, the central control module is used to solve the ratio of the mileage of the inspection route of a single drone to the sum of the actual inspection time differences of each adjacent inspection point, and record it as the actual running speed. The central control module determines the processing method for the drone inspection module based on the actual running speed, including:

[0112] If the actual operating speed is greater than the preset actual operating speed, the planned inspection time corresponding to each single drone is adjusted to the corresponding value based on the actual operating speed;

[0113] If the actual operating speed is less than or equal to the preset actual operating speed, a charging instruction is issued to the corresponding drone, and the inspection plan is updated.

[0114] Specifically, the preset actual running speed V0 is selected within the interval [11.2, 13.5], and the unit is m / s.

[0115] Specifically, updating the inspection plan involves merging the peripheral inspection points in each inspection point corresponding to a single drone into the inspection area corresponding to an adjacent drone.

[0116] Specifically, when the abnormal proportion is less than or equal to the second preset abnormal proportion and greater than the first preset abnormal proportion, the processing method for the drone inspection module is determined in combination with the peak point distribution parameter. The peak point distribution parameter characterizes the distribution of abnormal delays between adjacent inspection points. When the peak point distribution parameter is greater than the preset peak point distribution parameter, the abnormal delay inspection points are scattered. In this case, the actual inspection is delayed due to obstacle interference on the actual inspection path. At this time, the moving speed of a single drone is adjusted to ensure on-time inspection. When the peak point distribution parameter is less than or equal to the preset peak point distribution parameter, there is an abnormal inspection situation with multiple delays in a concentrated area. At this time, due to abnormal power, the inspection of a single area is delayed on a large scale. At this time, the actual operating speed is obtained to determine whether the drone should be charged. When the actual operating speed is greater than the preset actual operating speed, the drone can still continue to run to complete the inspection. The planned inspection time corresponding to a single drone is adjusted to automatically control the monitoring parameters of the drone according to the actual operation of the drone. When the actual operating speed is less than or equal to the preset actual operating speed, the drone is controlled to charge, and the inspection route of the path planning module is updated to ensure that each drone can complete the inspection of the planned inspection points with sufficient power, further improving the inspection efficiency of the drone.

[0117] Specifically, the central control module is used to adjust each planned inspection time corresponding to a single drone to a corresponding value based on the actual operating speed, wherein:

[0118] The increase in the planned inspection time corresponding to a single UAV determined based on the actual operating speed is inversely proportional to the actual operating speed.

[0119] In this embodiment, optionally,

[0120] Comparing the actual running speed with a first preset speed comparison threshold and a second preset speed comparison threshold;

[0121] If the actual running speed is less than or equal to the first preset speed comparison threshold, the planned inspection time corresponding to each single UAV is adjusted to 1.29 times the initial planned inspection time;

[0122] If the actual running speed is less than or equal to the second preset speed comparison threshold and greater than the first preset speed comparison threshold, the planned inspection time corresponding to each single UAV is adjusted to 1.21 times the initial planned inspection time;

[0123] If the actual running speed is greater than the second preset speed comparison threshold, the planned inspection time corresponding to each single UAV is adjusted to 1.12 times the initial planned inspection time;

[0124] The first preset speed comparison threshold is 1.3V0, and the second preset speed comparison threshold is 1.6V0.

[0125] Specifically, the central control module adjusts the planned inspection time corresponding to a single inspection point to a corresponding value based on the path distance between the single inspection point and the inspection point of the initial inspection of the drone, under the condition that the adjustment of each planned inspection time based on the actual running speed is completed, wherein:

[0126] The increase in the planned inspection time determined based on the path distance is proportional to the path distance.

[0127] In this embodiment, optionally,

[0128] The adjusted planned inspection time is the product of the path distance parameter, the initial planned inspection time and the electric energy coefficient;

[0129] The path distance parameter is the ratio of the path distance to the total inspection path length of a single UAV;

[0130] The electric energy coefficient is 1.5.

[0131] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0132] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A distribution line drone intelligent autonomous inspection system, characterized in that: include: Node positioning module, which is used to store the location information of each inspection point; The drone inspection module includes several drones for inspecting various inspection points; A path planning module, which is connected to the node positioning module and the drone inspection module respectively, and is used to determine the inspection route of each drone based on the location information of each inspection point; A planning customization module, which is connected to the path planning module, is used to determine the planned inspection time of each drone for each inspection point based on the inspection route and the inspection start time; A data receiving module, which is connected to the drone inspection module and the plan customization module, and is used to obtain the actual inspection time and inspection information of each drone for the corresponding inspection point; A cloud server, which is respectively connected to the node positioning module, the drone inspection module, the path planning module, the plan customization module and the data receiving module, and is used to store historical data of each module; A central control module, which is respectively connected to the cloud server, the drone inspection module, the path planning module and the plan customization module, and is used to determine the delay deviation parameter for a single inspection point according to the actual inspection time and the planned inspection time of the inspection point, and to determine the historical delay difference based on the delay deviation parameters of the single inspection point in the historical data, and to determine whether the operation of the drone inspection module is qualified in combination with the delay deviation parameter and the historical delay difference, and to mark a single inspection point as an abnormal node when it is determined that the operation of the drone inspection module is abnormal. The central control module determines the abnormality ratio based on the number of abnormal nodes after completing the one-by-one judgment on each inspection point and the existence of abnormal nodes, and determines the processing method for the drone inspection module based on the abnormality ratio, including adjusting the moving speed of each drone to the corresponding value, correcting each planned inspection time, or issuing a charging instruction for the corresponding drone; The central control module determines the processing method for the drone inspection module based on the abnormal proportion, including: To determine the abnormal proportion, solve the ratio of the number of abnormal nodes to the total number of inspection points to obtain the abnormal proportion; If the abnormality ratio is less than or equal to the first preset abnormality ratio, the moving speed of the single UAV is adjusted to a corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV; If the abnormality ratio is less than or equal to the second preset abnormality ratio and greater than the first preset abnormality ratio, a patrol point-relative deviation curve is drawn based on the relative deviation, and the peak point distribution parameters are determined based on the patrol point-relative deviation curve, and the processing method for the drone patrol module is determined based on the peak point distribution parameters; If the abnormality ratio is greater than the second preset abnormality ratio, it is determined that each planned inspection time is adjusted to the corresponding emergency planned inspection time; The central control module is used to draw a patrol point-relative deviation curve based on the relative deviation, determine the peak point distribution parameters based on the patrol point-relative deviation curve, and determine the processing method for the drone patrol module based on the peak point distribution parameters, including: The central control module is used to determine the relative deviation. For two adjacent inspection points inspected by a single drone, the planned inspection time difference and the actual inspection time difference of the two inspection points are obtained respectively, and the difference between the actual inspection time difference and the planned inspection time difference is calculated to obtain the relative deviation for the second inspection point of the two inspection points. The central control module is used to determine the peak point distribution parameter based on the inspection point-relative deviation curve, obtain the distance between each peak point in the inspection point-relative deviation curve, solve the variance of each distance, and obtain the peak point distribution parameter; If the peak point distribution parameter is greater than the preset peak point distribution parameter, the moving speed of the single UAV is adjusted to the corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV; If the peak point distribution parameter is less than or equal to the preset peak point distribution parameter, the processing method for the drone inspection module is determined based on the actual running speed; For a single UAV, the central control module is used to solve the ratio of the mileage of the inspection route of a single UAV to the sum of the actual inspection time differences of each adjacent inspection point, and record it as the actual running speed. The central control module determines the processing method for the UAV inspection module based on the actual running speed, including: If the actual operating speed is greater than the preset actual operating speed, the planned inspection time corresponding to each single drone is adjusted to the corresponding value based on the actual operating speed; If the actual operating speed is less than or equal to the preset actual operating speed, a charging instruction is issued to the corresponding UAV, and a decision is made to update the inspection plan.

2. The power distribution line drone intelligent autonomous inspection system according to claim 1 is characterized in that: For a single inspection point, the central control module is used to determine the delay deviation parameter for the inspection point based on the actual inspection time and the planned inspection time; It is used to solve the difference between the actual inspection time and the planned inspection time to obtain the delay deviation parameter; The central control module is used to determine whether the operation of the drone inspection module is qualified based on the delay deviation parameter, including: If the delay deviation parameter is less than or equal to the first preset delay deviation parameter, the operation of the drone inspection module is determined to be qualified, and the drone inspection module is controlled to continue to operate using the current operating parameters; If the delay deviation parameter is less than or equal to the second preset delay deviation parameter and greater than the first preset delay deviation parameter, then determine whether the operation of the drone inspection module is qualified in combination with the historical delay difference; If the delay deviation parameter is greater than the second preset delay deviation parameter, the operation of the drone inspection module is determined to be abnormal, and the single inspection point is marked as an abnormal node.

3. The power distribution line drone intelligent autonomous inspection system according to claim 2 is characterized in that: The central control module is used to determine whether the operation of the drone inspection module is qualified based on the historical delay difference, including: It is used to obtain and determine the historical delay difference, solve the variance of each delay deviation parameter of a single inspection point in the historical data, and obtain the historical delay difference; If the historical delay difference is less than or equal to the preset historical delay difference, the operation of the drone inspection module is determined to be qualified, and the first preset delay deviation parameter is adjusted to a corresponding value based on the historical delay difference; If the historical delay difference is greater than the preset historical delay difference, the operation of the drone inspection module is judged to be abnormal, and the single inspection point is marked as an abnormal node.

4. The power distribution line drone intelligent autonomous inspection system according to claim 3 is characterized in that: The central control module is used to adjust the first preset delay deviation parameter to a corresponding value based on the historical delay difference, wherein: The increase range of the first preset delay deviation parameter determined based on the historical delay difference is inversely proportional to the historical delay difference.

5. The power distribution line drone intelligent autonomous inspection system according to claim 4 is characterized in that: The central control module is used to adjust the moving speed of a single UAV to a corresponding value based on the average value of each delay deviation parameter corresponding to the single UAV, wherein: The average value of each delay deviation parameter corresponding to a single UAV is recorded as the deviation mean, and the increase in the movement speed of a single UAV determined based on the deviation mean is proportional to the deviation mean.

6. The power distribution line drone intelligent autonomous inspection system according to claim 5 is characterized in that: The central control module is used to adjust each planned inspection time corresponding to a single UAV to a corresponding value based on the actual operating speed, wherein: The increase in the planned inspection time corresponding to a single UAV determined based on the actual operating speed is inversely proportional to the actual operating speed.

7. The power distribution line drone intelligent autonomous inspection system according to claim 6 is characterized in that: The central control module adjusts the planned inspection time corresponding to a single inspection point to a corresponding value based on the path distance between the single inspection point and the inspection point of the initial inspection by the drone, while completing the adjustment of each planned inspection time based on the actual running speed, wherein: The increase in the planned inspection time determined based on the path distance is proportional to the path distance.

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