Autonomous line-imitating flight inspection method and system for side edge of power transmission line

Abstract

The invention provides a power transmission line side autonomous line-imitating flight inspection method and a power transmission line side autonomous line-imitating flight inspection system. The method comprises the following steps: receiving first position information of flight equipment and second position information of a target power transmission line; planning a flight path along the direction of the power transmission line according to the first position information and the second position information so as to ensure that the flight equipment can keep autonomous flight within the safe distance range of the side edge of the power transmission line; when the flight equipment flies along the flight path, multi-angle image data of the power transmission line and the surrounding environment of the power transmission line are collected in real time; performing real-time analysis on the acquired multi-angle image data by using an intelligent analysis module carried on the flight equipment, and identifying an abnormal state of the power transmission line; automatically adjusting the flight attitude of the flight equipment so as to check when the flight equipment is close to the abnormal position, and recording the specific coordinate information of the abnormal position; and generating an inspection report. According to the technical scheme provided by the invention, the inspection efficiency and the inspection safety are improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of power transmission line maintenance, and in particular to a method and system for autonomous line-flight inspection of the side of a power transmission line. Background Art

[0002] At present, there are two main ways to inspect power transmission lines: one is the traditional manual inspection, where professionals carry necessary inspection tools to conduct on-site inspections of power transmission lines; the other is the inspection technology based on drones, which use drones to carry sensors such as cameras to conduct non-contact inspections of power transmission lines. Among them, drone inspection technology has gradually gained popularity due to its high efficiency and flexibility.

[0003] Although drone inspection technology has obvious advantages over traditional manual inspection, it still has some shortcomings: most existing drone inspection technologies rely on pre-set flight paths or manual control, making it difficult to accurately and stably track transmission lines, especially in complex environments, where deviations from the planned route are likely to occur. Most drone inspection systems lack effective image recognition and analysis capabilities, making it impossible to monitor the status of transmission lines in real time, and unable to respond promptly when problems are discovered.

[0004] Due to the lack of an effective obstacle avoidance mechanism, when drones approach power transmission lines for detailed inspections, they may collide due to misjudgment or improper operation, causing damage to equipment and even affecting the safety of the power grid. Summary of the invention

[0005] The embodiments of the present application provide a method and system for autonomous line-flight inspection of the side of a power transmission line, which are used to solve the problems of low inspection efficiency and low safety in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a method for autonomous line-mimicking flight inspection of a transmission line side, comprising:

[0007] receiving first location information of the flying device and second location information of the target power transmission line;

[0008] Planning a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line;

[0009] During the flight of the flying device along the flight path, real-time collection of multi-angle image data of the power transmission line and its surrounding environment;

[0010] Using the intelligent analysis module on the flying device, the collected multi-angle image data is analyzed in real time to identify abnormal conditions of the transmission line, including line damage, hanging foreign objects, tilted towers, and defects in conductor spacers;

[0011] When an abnormal state is detected, the flight attitude of the flying device is automatically adjusted so that the flying device is inspected when it approaches the abnormal position, and the specific coordinate information of the abnormal position is recorded;

[0012] After the flight equipment has completed the inspection, an inspection report is generated, which includes all abnormal conditions found during the inspection, specific location information of the abnormal location, and corresponding maintenance suggestions.

[0013] In a second aspect, an embodiment of the present application provides a transmission line side autonomous line-mimicking flight inspection system, comprising:

[0014] A receiving module, used for receiving first position information of the flying device and second position information of the target power transmission line;

[0015] a planning module, configured to plan a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line;

[0016] A collection module, used for collecting multi-angle image data of the power transmission line and its surrounding environment in real time during the flight of the flying device along the flight path;

[0017] An analysis module, used to use the intelligent analysis module carried by the flying device to perform real-time analysis on the collected multi-angle image data to identify abnormal conditions of the transmission line, wherein the abnormal conditions include line damage, hanging foreign objects, tower tilt, and conductor spacer defects (specifically including conductor spacer breakage, conductor spacer damage, conductor spacer fall-off, and bolt pin loss);

[0018] An adjustment module, for automatically adjusting the flight attitude of the flying device when an abnormal state is detected, so that the flying device is inspected when it approaches an abnormal position, and records the specific coordinate information of the abnormal position;

[0019] The generation module is used to generate an inspection report after the flight equipment completes the inspection. The inspection report contains all abnormal conditions found during the inspection, specific location information of the abnormal location, and corresponding maintenance suggestions.

[0020] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an autonomous line-simulating flight inspection method for the side of a transmission line as described in any one of the first aspects.

[0021] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program, which, when executed by a computer, implements a method for autonomous line-simulating flight inspection of the side of a transmission line as described in any one of the first aspects.

[0022] In the embodiment of the present application, the first position information of the flying device and the second position information of the target transmission line are received; a flight path along the transmission line is planned based on the first position information and the second position information to ensure that the flying device can maintain autonomous flight within a safe distance range on the side of the transmission line; during the flight of the flying device along the flight path, multi-angle image data of the transmission line and its surrounding environment are collected in real time; the intelligent analysis module on the flying device is used to analyze the collected multi-angle image data in real time to identify the abnormal state of the transmission line; when an abnormal state is detected, the flight attitude of the flying device is automatically adjusted to allow the flying device to be inspected when it is close to the abnormal position, and the specific coordinate information of the abnormal position is recorded; after the flying device completes the inspection, an inspection report is generated. The technical solution provided by the present application improves the inspection efficiency, safety and data analysis capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a flow chart of the autonomous line-simulating flying inspection method for the side of the transmission line;

[0024] Figure 2 This is a schematic diagram of the structure of the autonomous line-flying inspection system for the side of the transmission line;

[0025] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0027] Figure 1 A flowchart of a method for autonomous line-simulating flight inspection of a transmission line side is provided for an embodiment of the present application, such as Figure 1As shown, the method includes:

[0028] 101. Receive first location information of a flying device and second location information of a target power transmission line;

[0029] In this step, the system first needs to obtain two key location information:

[0030] The first location information of the flying device refers to the exact geographical location of the drone or other aircraft at the moment, which is usually determined by the global positioning system or other positioning technologies.

[0031] The second location information of the target transmission line refers to the specific location data of the transmission line that needs to be inspected, including the starting point, end point and key node locations along the line. This information can be obtained through map data, geographic information system and other means.

[0032] The acquisition of these two position information is the basis for subsequent flight path planning and ensuring that the aircraft can fly safely along the power transmission line. With accurate position information, the system can calculate the optimal flight path to ensure that the aircraft always stays within a safe distance from the side of the power transmission line during the inspection process.

[0033] The present application takes into account that in the existing power transmission line inspection technology, the acquisition of the location information of the flight equipment and the location information of the target power transmission line often relies on manual input or simple positioning equipment. This method has the following problems: the manually input location information is prone to errors and has low accuracy, which may cause the flight equipment to deviate from the predetermined inspection path. The existing positioning technology cannot update the location of the flight equipment in real time, resulting in position deviations during the flight process, affecting the accuracy and safety of the inspection. Relying solely on simple positioning equipment cannot provide detailed geographic information of the transmission line, such as the latitude and longitude coordinates of the starting point, end point, and intermediate support point of the line, which limits the accuracy of path planning and the comprehensiveness of the inspection. In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, which obtains the current location coordinates of the flight equipment in real time through the global positioning system or the Beidou satellite navigation system, and uses the geographic information system database or the pre-built digital map of the power transmission line to determine the geographic location information of the target power transmission line. This solution aims to improve the accuracy and real-time performance of the location information and ensure that the flight equipment can be inspected accurately and safely.

[0034] The options are as follows:

[0035] Optionally, the receiving of the first position information of the flying device and the second position information of the target transmission line in step 101 includes: acquiring the current position coordinates of the flying device in real time through a global positioning system or a Beidou satellite navigation system as the first position information of the flying device; and determining the geographical location information of the target transmission line, including the latitude and longitude coordinates of the starting point, end point, and intermediate support points of the line, using a geographic information system database or a pre-built digital map of transmission lines, as the second position information of the target transmission line.

[0036] In this step, Global Positioning System: A satellite navigation system that provides precise geographic location information through satellite signals.

[0037] BeiDou Navigation Satellite System: A satellite navigation system independently developed by China that provides high-precision positioning services.

[0038] Geographic Information System: A system for capturing, managing, analyzing, and presenting geographic data.

[0039] Transmission line digital map: A digital map containing detailed geographic information of the transmission line, including the latitude and longitude coordinates of the starting point, end point, and intermediate support points of the line.

[0040] Global Positioning System or BeiDou Satellite Navigation System: The flight equipment is equipped with a GPS or BDS receiver, which can receive satellite signals in real time and calculate the latitude and longitude coordinates of the current location.

[0041] Current location coordinates: The exact geographic location of the flight device at a certain moment, usually expressed as latitude and longitude coordinates (longitude, latitude).

[0042] Geographic Information System Database: A database that stores detailed geographic information of power transmission lines, which can query the longitude and latitude coordinates of the starting point, end point, and intermediate support points of the line.

[0043] Transmission Line Digital Map: A pre-built digital map containing detailed geographic information of transmission lines, which can provide high-precision line path data.

[0044] Geographic location information: the latitude and longitude coordinates of the starting point, end point, and intermediate support points of the transmission line, which are used for path planning and navigation.

[0045] In the embodiment of the present application, it is assumed that a power transmission line located in a mountainous area needs to be inspected. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), the end point is B (longitude: 116.4174, latitude: 39.9142), and there are several supporting points in the middle, and the longitude and latitude coordinates of each supporting point are known.

[0046] The flight device is equipped with a GPS receiver, which receives satellite signals in real time and calculates the longitude and latitude coordinates of the current position. Assume that the initial position of the flight device is C (longitude: 116.4070, latitude: 39.9040).

[0047] Using the GIS database or the pre-built digital map of the power transmission line, query the longitude and latitude coordinates of the starting point A, the end point B and the intermediate support point of the power transmission line. For example, the intermediate support point D (longitude: 116.4124, latitude: 39.9092).

[0048] By using the global positioning system or Beidou satellite navigation system to obtain the current position coordinates of the flying device in real time, and using the geographic information system database or the pre-built digital map of the transmission line to determine the geographic location information of the target transmission line, this solution achieves the following beneficial effects: the high-precision positioning service provided by the global positioning system or Beidou satellite navigation system ensures the accuracy of the flying device's location information, and the real-time updated location information enables the flying device to fly more accurately along the predetermined path. Using the detailed geographic information provided by the geographic information system database or the digital map of the transmission line, the system can plan the flight path more accurately, ensuring that the flying device always stays within a safe distance range on the side of the transmission line during the inspection process. The detailed geographic location information enables the system to fully cover all parts of the transmission line, ensuring that the inspection is complete and improving the accuracy and reliability of the inspection.

[0049] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of insufficient positioning accuracy, poor real-time performance and incomplete data in the prior art, and improves the efficiency and safety of transmission line inspection.

[0050] 102. Planning a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line;

[0051] In this step, the system will use the previously acquired location information of the flight equipment and the target transmission line to plan the flight path. The specific process is as follows:

[0052] The system receives first location information of the flying device and second location information of the target power transmission line.

[0053] Use a path planning algorithm, combined with the direction of the transmission line and terrain data, to calculate an optimal flight path.

[0054] When planning a route, the system will set a safe distance range to ensure that the aircraft always maintains a certain safe distance from the power transmission line during flight. This safe distance can be adjusted according to the voltage level of the power transmission line, environmental factors and other factors.

[0055] Taking into account environmental factors such as wind speed and weather during actual flight, the system will further optimize the path to ensure that the flight equipment can complete the inspection task smoothly and efficiently.

[0056] Through this step, the system can generate a flight path that is consistent with the direction of the transmission line and ensures safety, laying the foundation for subsequent autonomous flight and inspection tasks.

[0057] The present application takes into account that in the existing power transmission line inspection technology, the flight path planning of the flight equipment usually relies on a simple straight path or a manually set path. This method has the following problems: simple path planning cannot fully consider the actual direction of the transmission line and terrain changes, which may cause the flight equipment to deviate from the predetermined path. The manually set path is difficult to ensure that the flight equipment always stays within the safe distance range of the side of the transmission line during the inspection process, and it is easy to cause safety accidents such as collisions. The existing path planning method fails to fully consider the dynamic factors such as the flight speed and wind speed of the flight equipment, affecting the stability and safety of the flight. In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, by applying a path planning algorithm, combined with dynamic factors such as the flight speed and wind speed of the flight equipment, a series of discrete points along the direction of the transmission line are calculated, ensuring that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line. This solution is intended to improve the accuracy and safety of the flight path and ensure that the flight equipment can complete the inspection task efficiently and safely.

[0058] The options are as follows:

[0059] Optionally, the step 102 of planning a flight path along the direction of the transmission line based on the first position information and the second position information to ensure that the flying device can maintain autonomous flight within a safe distance range on the side of the transmission line, includes: based on the first position information and the second position information, applying a path planning algorithm to determine the relative position relationship between the flying device and the target transmission line; based on the relative position relationship and the acquired flight speed and wind speed of the flying device, calculating a series of discrete points along the direction of the transmission line to form a flight path along the direction of the transmission line; wherein, in the process of calculating a series of discrete points along the direction of the transmission line, it is ensured that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line, and the preset safety distance includes the minimum safety distance between the flying device and the transmission line.

[0060] In this step, path planning algorithm: an algorithm used to calculate the optimal path, common ones include A-Star algorithm, Dijkstra algorithm, etc.

[0061] Relative position relationship: The spatial position relationship between the flight equipment and the target transmission line, including distance and direction.

[0062] Discrete points: A series of points on a path that describe the flight trajectory of a flying device.

[0063] Preset safety distance: The minimum safety distance that must be maintained between the flight equipment and the power transmission line to ensure flight safety.

[0064] First location information: the current location coordinates of the flight device.

[0065] Second location information: geographical location information of the target transmission line, including the latitude and longitude coordinates of the starting point, end point and intermediate support points.

[0066] Path planning algorithm: Select a suitable path planning algorithm to calculate the relative position relationship between the flight equipment and the transmission line based on the location information of the flight equipment and the transmission line.

[0067] Relative position relationship: Determine the position of the flight equipment relative to the transmission line.

[0068] Flight speed: The current flight speed of the aircraft.

[0069] Wind speed: The current wind speed in the environment, which affects the flight trajectory of the aircraft.

[0070] Discrete points: A series of points calculated by the path planning algorithm that make up the flight path.

[0071] In the process of calculating a series of discrete points along the transmission line, it is ensured that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line, wherein the preset safety distance includes a minimum safety distance between the flight device and the transmission line:

[0072] Preset safety distance: The minimum safety distance set according to the voltage level of the transmission line and environmental factors.

[0073] Discrete point location: Ensure that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line.

[0074] In the embodiment of the present application, it is assumed that a transmission line needs to be inspected. The starting point of the transmission line is A (longitude: 116.4074, latitude: 39.9042), the end point is B (longitude: 116.4174, latitude: 39.9142), there are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The initial position of the flying device is C (longitude: 116.4070, latitude: 39.9040), the flying speed is 10m / s, and the current wind speed is 2m / s.

[0075] Using the A-Star algorithm, the relative position relationship between the flying device and the transmission line is calculated based on the current position C of the flying device and the longitude and latitude coordinates of the starting point A, the end point B and the intermediate support points of the transmission line.

[0076] According to the relative position relationship, flight speed (10m / s) and wind speed (2m / s), a series of discrete points along the transmission line are calculated. Assuming that a discrete point is set every 10 meters, ensure that each discrete point is located on one side of the transmission line and maintains a preset safety distance of at least 5 meters from the transmission line.

[0077] The location of each discrete point is verified to ensure that its distance from the transmission line is greater than or equal to 5 meters. For example, the first discrete point D1 (longitude: 116.4075, latitude: 39.9043), the second discrete point D2 (longitude: 116.4080, latitude: 39.9046), and so on, until the last discrete point Dn (longitude: 116.4175, latitude: 39.9143).

[0078] By applying the path planning algorithm, taking into account the relative position relationship between the flight equipment and the transmission line, the flight speed, the wind speed and other factors, a series of discrete points along the transmission line are calculated. This solution achieves the following beneficial effects: The path planning algorithm ensures the accuracy of the relative position relationship between the flight equipment and the transmission line, allowing the flight equipment to fly along the transmission line more accurately. Dynamic factors such as flight speed and wind speed are taken into account to make the flight path more stable and predictable, improving the safety and reliability of the flight. By calculating the position of each discrete point, it is ensured that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line, effectively avoiding the risk of collision between the flight equipment and the transmission line.

[0079] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems existing in the prior art of insufficient path planning accuracy, inadequate consideration of dynamic factors and difficulty in ensuring a safe distance, thereby improving the efficiency and safety of transmission line inspection.

[0080] The present application takes into account that in the existing power transmission line inspection technology, the planning of the flight path mainly focuses on the optimization of the path itself, while less consideration is given to the optimal flight speed and flight altitude of the flight equipment. This single path planning method has the following problems: the fixed flight speed and altitude may not adapt to different environmental conditions, such as wind speed, temperature changes, etc., resulting in low flight efficiency or increased flight safety risks. The existing path planning method usually does not consider the impact of dynamic environmental factors such as wind speed and temperature on the flight, which may lead to the instability and unpredictability of the flight path. Failure to adjust the flight speed and altitude according to real-time environmental conditions may cause the flight efficiency of the flight equipment to be low in some cases, extending the inspection time. In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, by calculating the optimal flight speed and flight altitude of the flight equipment, comprehensively considering the real-time distance between the flight equipment and the transmission line, wind speed, temperature and other dynamic factors, so as to optimize the flight path and improve flight efficiency and safety.

[0081] The options are as follows:

[0082] Optionally, the step 102 of planning a flight path along the transmission line according to the first position information and the second position information further includes:

[0083] Calculating the optimal flight speed and flight altitude of the flying device to plan a flight path along the transmission line;

[0084] The optimal flight speed and flight altitude of the flight device are calculated by the following formula:

[0085]

[0086] Where v(t) represents the flight speed of the flight equipment at time t, h(t) represents the flight altitude of the flight equipment at time t, v0 is the basic flight speed, H0 is the basic flight altitude, D(t) is the real-time flight distance between the flight equipment and the transmission line, T is the expected flight time, ΔW(t) is the difference between the actual wind speed at time t and the basic wind speed W0, ΔT a (t) is the difference between the actual air temperature at time t and the base temperature T a0 The difference, H max is the maximum flight altitude, k1, k2, k3, k4, k5, k6, k7, k8, k9, k 10 are the adjustment coefficients of the corresponding parameters respectively, P is the sine wave period in flight speed adjustment, Q is the cosine wave period in flight speed adjustment, R is the sine wave period in flight altitude adjustment, and S is the cosine wave period in flight altitude adjustment.

[0087] In this step, the optimal flight speed v represents the optimal flight speed that the flight device can reach under the current environmental conditions; the optimal flight altitude h represents the optimal flight altitude that the flight device can maintain under the current environmental conditions; the basic flight speed v0 represents the basic flight speed of the flight device under standard environmental conditions; the basic flight altitude H0 represents the basic flight altitude of the flight device under standard environmental conditions; the real-time flight distance D(t) represents the real-time distance between the flight device and the transmission line; the expected flight time T represents the expected flight time from the starting point to the end point; the current wind speed W(t) represents the wind speed of the current environment; the basic wind speed W0 represents the basic wind speed under standard environmental conditions; the current air temperature T a (t) represents the current ambient air temperature; the base temperature T a0 Indicates the base temperature under standard ambient conditions; the maximum flight altitude H max Indicates the maximum allowable flight altitude of the flight equipment; adjustment coefficients k1, k2, k3, k4, k5, k6, k7, k8, k9, k 10 Represents the coefficient used to adjust the flight speed and altitude; the speed and altitude adjustment period P, Q, R, S are the periodic parameters used to adjust the flight speed and altitude.

[0088] The optimal flight speed v(t) is calculated by the following formula:

[0089]

[0090] The optimal flight altitude h(t) is calculated by the following formula:

[0091]

[0092] After calculating the optimal flight speed and altitude, combined with the relative position relationship between the flight equipment and the transmission line, a path planning algorithm (such as the A-Star algorithm) is applied to determine a series of discrete points along the transmission line to form an optimal flight path.

[0093] In the above technical scheme, P is the sine wave period in the flight speed adjustment, Q is the cosine wave period in the flight speed adjustment, R is the sine wave period in the flight altitude adjustment, and S is the cosine wave period in the flight altitude adjustment; taking the cosine wave period in the Q flight speed adjustment as an example: the embodiment of the present application refers to the cosine waveform period adjustment method of the flight speed when adjusting the flight speed, that is, the use of a cosine waveform can make the speed change smoother and avoid sudden changes, thereby improving the stability and safety of the flight.

[0094] In the embodiment of the present application, it is assumed that a power transmission line needs to be inspected. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), the end point is B (longitude: 116.4174, latitude: 39.9142), and there are several support points in the middle. The longitude and latitude coordinates of each support point are known. The initial position of the flight equipment is C (longitude: 116.4070, latitude: 39.9040), the basic flight speed v0 is 10m / s, the basic flight altitude H0 is 30 meters, the basic wind speed W0 is 2m / s, and the basic temperature T a0 At 25°C, the maximum flight altitude is H max The estimated flight time T is 30 minutes.

[0095] Calculate the optimal flight speed:

[0096] Assume that the real-time flight distance D(t) between the current flight equipment and the power transmission line is 100 meters, the current wind speed W(t) is 3m / s, and the current air temperature T a (t) is 28°C, adjustment coefficients k1=0.1, k2=0.2, k3=0.1, k4=0.05, k5=0.05, speed adjustment period P=60 seconds, speed adjustment period Q=60 seconds.

[0097] Calculation formula:

[0098]

[0099] Assume t = 0 seconds, calculate the result:

[0100] v(0)=10.16756m / s

[0101] Calculate the optimal flight altitude:

[0102] Assume that the adjustment coefficients k6 = 0.1, k7 = 0.2, k8 = 0.1, k9 = 0.05, k 10 =0.05, height adjustment cycle R = 120 seconds, S = 180 seconds.

[0103] Calculation formula:

[0104]

[0105]

[0106] 10.1176m / s and the optimal flight altitude h(0)=30.362m, as well as the relative position relationship between the flight equipment and the transmission line, a series of discrete points along the transmission line are calculated to ensure that each discrete point is located on one side of the transmission line and maintains a safe distance of at least 5m from the transmission line.

[0107] By calculating the optimal flight speed and altitude of the flight equipment, and comprehensively considering the real-time distance between the flight equipment and the transmission line, wind speed, temperature and other dynamic factors, this solution achieves the following beneficial effects: the flight speed and altitude are adjusted according to the real-time environmental conditions, so that the flight equipment can fly in the optimal state, improving flight efficiency and shortening inspection time. The impact of dynamic factors such as wind speed and temperature on flight is taken into account, making the flight path more stable and predictable, and improving the safety and reliability of flight. By calculating the position of each discrete point, it is ensured that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line, effectively avoiding the risk of collision between the flight equipment and the transmission line.

[0108] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems existing in the prior art such as the incompatibility of flight speed and altitude, insufficient consideration of dynamic environmental factors and low flight efficiency, and improves the efficiency and safety of transmission line inspection.

[0109] 103. While the flying device is flying along the flight path, real-time multi-angle image data of the power transmission line and its surrounding environment are collected;

[0110] In this step, the flying device will fly along the previously planned flight path and collect multi-angle image data of the power transmission line and its surrounding environment in real time. The specific process is as follows:

[0111] The flying device starts autonomous flight according to the planned path.

[0112] The camera or other imaging equipment on the flying device will capture the power transmission line and its surrounding environment from multiple angles during the flight. These angles may include looking down, sideways, oblique, etc. to ensure that different parts of the power transmission line are fully covered.

[0113] The collected image data will be transmitted back to the ground control station in real time through the wireless communication module or stored in the local memory of the flight equipment for subsequent processing and analysis.

[0114] In addition to the transmission lines themselves, the flying equipment also collects information about the surrounding environment, such as vegetation, terrain, buildings, etc. This information helps to assess the operating environment and potential risks of the transmission lines.

[0115] Through this step, the system can obtain detailed image data of the transmission line and its surrounding environment, providing rich information support for subsequent intelligent analysis and abnormality detection. This not only improves the comprehensiveness and accuracy of the inspection, but also provides an important reference for subsequent maintenance work.

[0116] The present application takes into account that in the existing power transmission line inspection technology, the collection and analysis of image data mainly rely on simple cameras and basic image processing technology. This method has the following problems: traditional cameras can only capture images from a fixed angle, and cannot fully capture the status information of the transmission line, which may cause certain abnormal conditions to be missed. Existing image processing technology usually relies on simple threshold judgment or template matching, with low recognition accuracy and prone to false alarms or omissions. When processing a large amount of image data, the existing image processing technology has a large amount of calculation and is difficult to achieve real-time analysis, affecting the efficiency and timeliness of the inspection. In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, which is equipped with a multi-angle camera to collect multi-angle image data of the transmission line and its surrounding environment in real time, and uses a deep learning algorithm to train a neural network model for real-time abnormal state recognition to improve the comprehensiveness and accuracy of the inspection.

[0117] The options are as follows:

[0118] Optionally, in step 103, during the flight of the flying device along the flight path, real-time collection of multi-angle image data of the transmission line and its surrounding environment includes: using a multi-angle camera equipped on the flying device to capture multi-angle image data of the transmission line and its surrounding environment in real time, wherein the camera can cover different viewing angles to ensure that the status information of the transmission line can be fully captured; using the intelligent analysis module carried by the flying device to perform real-time analysis on the collected multi-angle image data to identify abnormal states of the transmission line, including: applying a deep learning algorithm to pre-train a neural network for abnormal state recognition of the transmission line The neural network model can identify a variety of abnormal conditions including line damage, hanging foreign objects, tower tilt, and conductor spacer defects. The training data set contains a large number of labeled transmission line image samples in normal and abnormal states to ensure that the model has good generalization ability and high-precision recognition ability; the collected multi-angle image data is input into the trained neural network model, and the neural network model is used to perform real-time abnormal state recognition. The neural network model is used to extract features from the multi-angle image data, and compare the features in the multi-angle image data with the features learned during training to determine whether the transmission line has an abnormal state.

[0119] In this step, multi-angle cameras: cameras that can capture images from multiple different perspectives, ensure that the status information of the transmission line is fully captured.

[0120] Deep learning algorithm: A machine learning method that learns complex features of data through a multi-layer neural network model.

[0121] Neural network model: A computational model that simulates the structure of neurons in the human brain and is used to process and analyze data.

[0122] Training dataset: Contains a large number of labeled transmission line image samples in normal and abnormal states for training neural network models.

[0123] Feature extraction: Extract useful features from image data for recognition and classification.

[0124] Real-time analysis: Analyze data while it is being collected to ensure timely results.

[0125] Multi-angle camera: The flying device is equipped with multiple cameras that can capture images of the power transmission line and its surrounding environment from different angles to ensure that the status information of the power transmission line is fully captured.

[0126] Real-time capture: The camera collects image data in real time as the aircraft flies along the flight path.

[0127] Apply deep learning algorithms to pre-train a neural network model for abnormal state recognition of transmission lines:

[0128] Deep Learning Algorithms: Use deep learning frameworks to train neural network models.

[0129] Training dataset: Contains a large number of labeled transmission line image samples in normal and abnormal states for training neural network models.

[0130] Abnormal conditions: including line damage, hanging foreign objects, tower tilt, conductor spacer defects (specifically including conductor spacer breakage, conductor spacer damage, conductor spacer detachment, bolt pin missing) and other abnormal conditions.

[0131] Generalization ability: The ability of the model to accurately identify abnormal states even in unseen data.

[0132] Multi-angle image data: Transmission line image data taken from multiple angles.

[0133] Feature extraction: The neural network model extracts useful features from the image data.

[0134] Feature comparison: Compare the extracted features with the features learned during training to determine whether there is an abnormal state in the transmission line.

[0135] In the embodiment of the present application, it is assumed that a drone equipped with a multi-angle camera is used to inspect a power transmission line. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), and the end point is B (longitude: 116.4174, latitude: 39.9142). There are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The flight path of the drone has been planned, the flight speed is 10m / s, and the flight altitude is 30 meters.

[0136] The drone is equipped with four cameras, which can capture images of the power transmission lines and their surrounding environment from four angles: looking down, sideways, obliquely and upward.

[0137] As the drone flies along the flight path, each camera takes an image per second to ensure comprehensive capture of the status of the transmission line.

[0138] A neural network model was trained using a deep learning framework, and the training dataset contained 100,000 labeled images of power transmission lines in normal and abnormal states.

[0139] Abnormal conditions include line damage, hanging foreign objects, tilted pole towers, conductor spacer defects (specifically including conductor spacer breakage, conductor spacer damage, conductor spacer detachment, missing bolt pins), etc.

[0140] After multiple iterations of training, the accuracy of the neural network model reached over 95%, with good generalization ability.

[0141] The multi-angle image data collected by the drone is transmitted in real time to the intelligent analysis module on the flight equipment.

[0142] The intelligent analysis module inputs the image data into the trained neural network model. The neural network model extracts features from the image and compares them with the features learned during training.

[0143] If an abnormal state is detected, the intelligent analysis module will record the specific coordinate information of the abnormal location and generate corresponding alarm information.

[0144] By equipping multi-angle cameras to collect multi-angle image data of the transmission line and its surrounding environment in real time, and using deep learning algorithms to train neural network models for real-time abnormal state recognition, this solution achieves the following beneficial effects: Multi-angle cameras capture images from different perspectives to ensure that the status information of the transmission line is fully captured, avoiding the omission of abnormal states caused by a single perspective. The neural network model trained by the deep learning algorithm has high-precision recognition capabilities and can accurately identify a variety of abnormal states, reducing false alarms and missed reports. The neural network model can perform real-time analysis while collecting data, ensuring the timely discovery and processing of abnormal states, and improving the efficiency and timeliness of inspections.

[0145] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of single viewing angle, low recognition accuracy and poor real-time performance in the prior art, and improves the comprehensiveness and accuracy of power transmission line inspection.

[0146] 104. Utilize the intelligent analysis module on the flying device to analyze the collected multi-angle image data in real time to identify abnormal conditions of the transmission line, including line damage, hanging foreign objects, tilted towers, and defects in conductor spacers;

[0147] In this step, the intelligent analysis module: a computing unit installed on the flight equipment, equipped with a high-performance processor and memory, capable of running complex image processing and machine learning algorithms.

[0148] Multi-angle image data: image data of the power transmission line and its surrounding environment taken from different angles.

[0149] Deep learning algorithm: A machine learning method that learns complex features of data through a multi-layer neural network model.

[0150] Neural network model: A computational model that simulates the structure of neurons in the human brain and is used to process and analyze data.

[0151] Training dataset: Contains a large number of labeled transmission line image samples in normal and abnormal states for training neural network models.

[0152] Feature extraction: Extract useful features from image data for recognition and classification.

[0153] Abnormal conditions: abnormal conditions that may occur in transmission lines, including line damage, hanging foreign objects, tilted towers, defects in conductor spacers, etc.

[0154] Intelligent Analysis Module: A high-performance computing unit installed on the flight equipment that is capable of running complex image processing and machine learning algorithms.

[0155] Multi-angle image data: Image data of the power transmission line and its surrounding environment taken from multiple angles to ensure comprehensive capture of the status information of the power transmission line.

[0156] Deep learning algorithm: Use deep learning framework to train neural network model to identify abnormal status of transmission lines.

[0157] Neural network model: A pre-trained model that can identify a variety of abnormal conditions, including line damage, hanging foreign objects, tower tilt, conductor spacer defects (specifically including conductor spacer breakage, conductor spacer damage, conductor spacer detachment, and missing bolt pins), etc.

[0158] Training dataset: Contains a large number of labeled transmission line image samples in normal and abnormal states, which are used to train the neural network model to ensure that the model has good generalization ability and high-precision recognition ability.

[0159] Feature extraction: The neural network model extracts useful features from the image data and compares them with the features learned during training to determine whether there is any abnormal state in the transmission line.

[0160] In the embodiment of the present application, it is assumed that a drone equipped with a multi-angle camera is used to inspect a power transmission line. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), and the end point is B (longitude: 116.4174, latitude: 39.9142). There are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The flight path of the drone has been planned, the flight speed is 10m / s, and the flight altitude is 30 meters.

[0161] The drone is equipped with four cameras, which can capture images of the power transmission lines and their surrounding environment from four angles: looking down, sideways, obliquely and upward.

[0162] As the drone flies along the flight path, each camera takes an image per second to ensure comprehensive capture of the status of the transmission line.

[0163] The intelligent analysis module on the drone receives multi-angle image data and processes it immediately.

[0164] The intelligent analysis module uses a pre-trained neural network model to perform real-time analysis of image data.

[0165] A neural network model was trained using a deep learning framework, and the training dataset contained 100,000 labeled images of power transmission lines in normal and abnormal states.

[0166] Abnormal conditions include line damage, hanging foreign objects, tilted poles, defects in conductor spacers, etc.

[0167] Neural network models extract useful features from image data, such as edges, textures, colors, etc.

[0168] The extracted features are compared with the features learned during training to determine whether the transmission line is in an abnormal state.

[0169] If an abnormal state is detected, the intelligent analysis module will record the specific coordinate information of the abnormal location and generate corresponding alarm information.

[0170] By using the intelligent analysis module on the flight equipment to analyze the collected multi-angle image data in real time and identify the abnormal state of the transmission line, this solution achieves the following beneficial effects: The neural network model trained by the deep learning algorithm has high-precision recognition ability and can accurately identify a variety of abnormal states, reducing false alarms and missed reports. The intelligent analysis module can perform real-time analysis while collecting data to ensure the timely discovery and processing of abnormal states, improving the efficiency and timeliness of inspections. The multi-angle camera captures images from different perspectives to ensure that the status information of the transmission line is fully captured, avoiding the omission of abnormal states caused by a single perspective.

[0171] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of low recognition accuracy, poor real-time performance and incomplete inspection in the prior art, and improves the accuracy and efficiency of transmission line inspection.

[0172] 105. When an abnormal state is detected, the flight attitude of the flying device is automatically adjusted so that the flying device is inspected when it approaches an abnormal position, and the specific coordinate information of the abnormal position is recorded;

[0173] In this step, the system will use the abnormal status information detected by the intelligent analysis module to automatically adjust the flight attitude of the flight equipment in order to check the abnormal location in more detail and record relevant data.

[0174] The specific process is as follows:

[0175] The intelligent analysis module on the flight equipment analyzes the multi-angle image data collected in real time to identify abnormal conditions of the transmission line, such as line damage, hanging foreign objects, tilted towers, defects in conductor spacers, etc.

[0176] Once an abnormal state is detected, the system will automatically adjust the flight attitude of the aircraft to bring it closer to the abnormal location. This may include changing the flight altitude, flight direction or flight speed to ensure that the aircraft can conduct a detailed inspection of the abnormal location from the best angle.

[0177] When the flight equipment approaches the abnormal location, it will conduct a more detailed inspection and collect more high-resolution image data to more accurately assess the abnormal situation.

[0178] The system will record the specific coordinate information of the abnormal location, including longitude and latitude, altitude, etc., to ensure that the abnormal location can be accurately located and processed later.

[0179] The collected detailed image data and abnormal location information will be stored in the local memory of the flight equipment and transmitted back to the ground control station in real time through the wireless communication module for further analysis and processing by technicians.

[0180] Through this step, the system can promptly discover and check in detail the abnormal status of the transmission line, ensuring that the problem is dealt with in a timely manner, improving the accuracy and efficiency of inspections, and also providing important data support for subsequent maintenance work.

[0181] The present application takes into account that in the existing power transmission line inspection technology, when an abnormal state is detected, the flying device usually needs to manually adjust the flight attitude to approach the abnormal position for detailed inspection. This method has the following problems: Manual adjustment of the flight attitude is prone to errors, resulting in the flying device being unable to accurately approach the abnormal position, affecting the accuracy and efficiency of the inspection. Manual adjustment of the flight attitude takes time and cannot achieve a quick response, delaying the timing of handling the abnormal state. Manual adjustment of the flight attitude lacks automation, increases the workload of the operator, and reduces the automation level of the inspection. In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, which automatically adjusts the flight attitude of the flying device to ensure that the flying device can accurately approach the abnormal position and conduct an inspection, while recording the specific coordinate information of the abnormal position. This solution aims to improve the accuracy and efficiency of the inspection and achieve full automation.

[0182] The options are as follows:

[0183] Optionally, when an abnormal state is detected in step 105, the flight attitude of the flying device is automatically adjusted so that the flying device can be inspected when it approaches the abnormal position, and the specific coordinate information of the abnormal position is recorded, including: when an abnormal state is detected, the pixel coordinates of the abnormal position in the corresponding multi-angle image data are determined, and the specific coordinate information of the abnormal position is calculated by a geographic coordinate conversion algorithm in combination with the current position information of the flying device; according to the specific coordinate information of the abnormal position, an adjusted flight path and a corresponding attitude adjustment instruction are calculated; according to the adjusted flight path and the corresponding attitude adjustment instruction, the flight attitude of the flying device is adjusted to ensure that the flying device can approach the abnormal position and conduct an inspection.

[0184] In this step, pixel coordinates: the coordinates of the abnormal position in the multi-angle image data, usually expressed as (x, y).

[0185] Current location information: The current geographic location of the flight device, usually expressed as (longitude, latitude, altitude).

[0186] Geographic coordinate conversion algorithm: an algorithm that converts pixel coordinates in an image into geographic coordinates (longitude, latitude, altitude).

[0187] Attitude adjustment command: command used to adjust the flight attitude of the aircraft, including the adjustment of heading angle, pitch angle and roll angle.

[0188] Flight path: The flight trajectory of the flying device from the current location to the abnormal location.

[0189] Detecting abnormal conditions: The intelligent analysis module detects abnormal conditions of the transmission line.

[0190] Determine pixel coordinates: Determine the pixel coordinates (x, y) of the abnormal position in the multi-angle image data.

[0191] Current location information: Get the current location information (longitude, latitude, altitude) of the aircraft.

[0192] Geographic coordinate conversion algorithm: Use the geographic coordinate conversion algorithm to convert pixel coordinates (x, y) into geographic coordinates (longitude, latitude, altitude).

[0193] According to the specific coordinate information of the abnormal position, the adjusted flight path and the corresponding attitude adjustment instructions are calculated:

[0194] Specific coordinate information: The geographic coordinates (longitude, latitude, altitude) of the abnormal location obtained through the geographic coordinate conversion algorithm.

[0195] Flight path: Based on the specific coordinate information of the abnormal location, calculate the flight path from the current location to the abnormal location.

[0196] Attitude adjustment instructions: Based on the flight path, calculate the instructions required to adjust the flight attitude of the flight device, including the adjustment of the heading angle, pitch angle and roll angle.

[0197] Adjust the flight attitude of the flying device according to the adjusted flight path and the corresponding attitude adjustment instruction to ensure that the flying device can approach the abnormal position and conduct an inspection:

[0198] Adjust flight path: The aircraft flies according to the calculated flight path.

[0199] Attitude adjustment: The flight equipment adjusts its flight attitude according to the attitude adjustment command to ensure that it can accurately approach the abnormal location and conduct a detailed inspection.

[0200] In the embodiment of the present application, it is assumed that a drone equipped with a multi-angle camera is used to inspect a power transmission line. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), and the end point is B (longitude: 116.4174, latitude: 39.9142). There are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The flight path of the drone has been planned, the flight speed is 10m / s, and the flight altitude is 30 meters.

[0201] The intelligent analysis module detects an abnormal condition at a certain location of the transmission line, such as a foreign object hanging.

[0202] The pixel coordinates of the abnormal position in the multi-angle image data are (100, 150).

[0203] The current geographic location information of the flight device is obtained (longitude: 116.4080, latitude: 39.9050, altitude: 30 meters).

[0204] Use the geographic coordinate conversion algorithm to convert the pixel coordinates (100, 150) to geographic coordinates (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters).

[0205] According to the specific coordinate information of the abnormal location (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters), the flight path from the current location (longitude: 116.4080, latitude: 39.9050, altitude: 30 meters) to the abnormal location is calculated.

[0206] Calculate the instructions required to adjust the flight attitude of the flight device, including adjusting the heading angle to 10°, the pitch angle to 5°, and the roll angle to 0°.

[0207] The flying device flies according to the calculated flight path.

[0208] The flight equipment adjusts its flight attitude according to the attitude adjustment instructions to ensure that it can accurately approach the abnormal location and conduct a detailed inspection.

[0209] After the flying device reaches the abnormal location, it collects high-resolution image data, records the specific coordinate information of the abnormal location (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters) and generates corresponding alarm information.

[0210] By automatically adjusting the flight attitude of the flying device to ensure that the flying device can accurately approach the abnormal position and conduct inspection, this solution achieves the following beneficial effects: Automatically adjusting the flight attitude ensures that the flying device can accurately approach the abnormal position, avoiding errors caused by manual adjustment and improving the accuracy of inspection. Automatically adjusting the flight attitude can quickly respond to abnormal conditions, shorten the inspection time and improve the efficiency of inspection. Automatically adjusting the flight attitude reduces the workload of operators, realizes the full automation of inspection and improves the intelligence level of inspection.

[0211] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of inaccurate manual adjustment, long response time and lack of automation in the prior art, and improves the accuracy and efficiency of transmission line inspection.

[0212] In the existing power transmission line inspection technology, when an abnormal state is detected, the flying device usually needs to manually or simply automatically adjust the flight attitude to approach the abnormal location for detailed inspection. This method has the following problems: Simple path planning methods cannot take into account complex environmental factors such as wind speed, gravity, etc., resulting in the path of the flying device when approaching the abnormal location is not accurate enough, affecting the accuracy and safety of the inspection. Existing path planning methods usually do not take into account the dynamic characteristics of the flying device, such as acceleration and angular velocity, resulting in insufficient adjustment ability of the flying device when approaching the abnormal location, increasing the flight risk. Manual or simple automatic adjustment of the flight attitude takes time, cannot achieve rapid response, and delays the timing of handling abnormal conditions.

[0213] In order to solve the above problems, the embodiment of the present invention proposes a further optional solution, which automatically adjusts the flight attitude of the flying device by calculating the optimal flight path when the flying device approaches the abnormal position and taking into account various dynamic factors, so as to ensure that the flying device can accurately and safely approach the abnormal position and conduct inspection. This solution aims to improve the accuracy and safety of inspection and achieve full automation.

[0214] Optionally, when an abnormal state is detected in step 105, automatically adjusting the flight attitude of the flying device further includes:

[0215] acceleration, g is the acceleration due to gravity, w is the wind speed vector, n is the unit vector pointing to the abnormal position, m is the unit vector perpendicular to the flight path, b is the unit vector perpendicular to n and m, γ, δ, η are adjustment coefficients, k 11 , k 12 , k 13 is the acceleration adjustment coefficient, and c is the angular velocity vector of the flight device.

[0216] In this step, the optimal flight path p(t) represents the optimal flight trajectory from the current position to the abnormal position; the initial position p0 represents the current position of the flight device; the initial velocity v0 represents the current velocity of the flight device; the acceleration a represents the acceleration of the flight device; the basic acceleration a0 represents the basic acceleration of the flight device under standard environmental conditions; the gravity acceleration g represents the gravity acceleration of the earth, which is about 9.8m / s 2 ; Wind speed vector w represents the wind speed vector of the current environment; unit vector n pointing to the abnormal position represents the unit vector pointing from the current position to the abnormal position; unit vector m perpendicular to the flight path represents the unit vector perpendicular to the flight path; unit vector b perpendicular to n and m represents the unit vector perpendicular to n and m; adjustment coefficients γ, δ, η are used to adjust the coefficients of the flight path; acceleration adjustment coefficient k 11 , k 12 , k 13 A coefficient used to adjust acceleration; the angular velocity vector c of the flying device represents the angular velocity vector of the flying device.

[0217] Detecting abnormal conditions: The intelligent analysis module detects abnormal conditions of the transmission line.

[0218] Determine pixel coordinates: Determine the pixel coordinates (x, y) of the abnormal position in the multi-angle image data.

[0219] Current location information: Get the current location information (longitude, latitude, altitude) of the aircraft.

[0220] Geographic coordinate conversion algorithm: Use the geographic coordinate conversion algorithm to convert pixel coordinates (x, y) into geographic coordinates (longitude, latitude, altitude).

[0221] Optimal flight path:

[0222]

[0223] Acceleration formula:

[0224] a=a0+k 11 ·g+k 12 w+k 13 ·c

[0225] Where t is time, p0 is the initial position, V0 is the initial velocity, a is the acceleration, a0 is the base acceleration, g is the acceleration due to gravity, w is the wind speed vector, n is the unit vector pointing to the abnormal position, m is the unit vector perpendicular to the flight path, b is the unit vector perpendicular to n and m, γ, δ, η are adjustment coefficients, and k 11 , k 12 , k 13 is the acceleration adjustment coefficient, and c is the angular velocity vector of the flight device.

[0226] Adjust flight path: The aircraft will fly according to the calculated optimal flight path.

[0227] Attitude adjustment: The flight equipment adjusts its flight attitude according to the attitude adjustment command to ensure that it can accurately approach the abnormal location and conduct a detailed inspection.

[0228] In the embodiment of the present application, it is assumed that a drone equipped with a multi-angle camera is used to inspect a power transmission line. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), and the end point is B (longitude: 116.4174, latitude: 39.9142). There are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The flight path of the drone has been planned, the flight speed is 10m / s, and the flight altitude is 30 meters.

[0229] The intelligent analysis module detects an abnormal condition at a certain location of the transmission line, such as a foreign object hanging.

[0230] The pixel coordinates of the abnormal position in the multi-angle image data are (100, 150).

[0231] The current geographic location information of the flight device is obtained (longitude: 116.4080, latitude: 39.9050, altitude: 30 meters).

[0232] Use the geographic coordinate conversion algorithm to convert the pixel coordinates (100, 150) to geographic coordinates (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters).

[0233] Initial position p0: (longitude: 116.4080, latitude: 39.9050, altitude: 30 meters); initial velocity v0: 10 m / s; basic acceleration a0: 1 m / s 2 ; Gravitational acceleration g: 9.8m / s 2; Wind speed vector w: (2m / s, 0m / s, 0m / s); Unit vector n pointing to the abnormal position: (0.1, 0.1, 0); Unit vector m perpendicular to the flight path: (0, 1, 0); Unit vector b perpendicular to n and m: (1, 0, 0); Adjustment coefficients γ, δ, η: 0.1, 0.1, 0.1; Acceleration adjustment coefficient k 11 , k 12 , k 13 : 0.1, 0.1, 0.1; angular velocity vector c of the flight device: (0, 0, 0.1rad / s);

[0234] Calculate the acceleration a:

[0235] a=1+0.1·9.8+0.1·2+0.1·0.1=1+0.98+0.2+0.01=2.19m / s 2

[0236] Calculate the optimal flight path p(t):

[0237]

[0238] p(t)=(116.4080, 39.9050, 30)+10t+1.095t 2 +(0, 0.1, 0)

[0239] +(0.1, 0, 0)

[0240] p(t)=(116.4080+10t+1.095t 2 +0.11,39.9050+10t+1.095t

[0241] +0.11,30)

[0242] The flight device flies according to the calculated optimal flight path.

[0243] The flight equipment adjusts its flight attitude according to the attitude adjustment instructions to ensure that it can accurately approach the abnormal location and conduct a detailed inspection.

[0244] After the flying device reaches the abnormal location, it collects high-resolution image data, records the specific coordinate information of the abnormal location (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters) and generates corresponding alarm information.

[0245] By calculating the optimal flight path when the flying device approaches an abnormal position, and considering a variety of dynamic factors, the flying device's flight attitude is automatically adjusted. This solution achieves the following beneficial effects: It takes into account a variety of dynamic factors such as gravity, wind speed, acceleration and angular velocity, ensuring that the flying device can accurately approach the abnormal position, improving the accuracy and safety of the inspection. By adjusting the acceleration and flight attitude, the flying device can respond quickly in a complex environment, improving the stability and reliability of the flight. Automatically adjusting the flight attitude can quickly respond to abnormal conditions, shorten the inspection time, and improve the efficiency of the inspection. Automatically adjusting the flight attitude reduces the workload of operators, realizes the full automation of the inspection, and improves the intelligence level of the inspection.

[0246] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of inaccurate path planning, insufficient dynamic adjustment capability and long response time existing in the prior art, and improves the accuracy and safety of transmission line inspection.

[0247] 106. After the flight equipment completes the inspection, an inspection report is generated, where the inspection report includes all abnormal conditions found during the inspection, specific location information of the abnormal locations, and corresponding maintenance suggestions.

[0248] In this step, the inspection report: a document generated after the inspection is completed, including all abnormal conditions found during the inspection, specific location information of the abnormal location, and corresponding maintenance suggestions.

[0249] Abnormal conditions: abnormal conditions that may occur in transmission lines, including line damage, hanging foreign objects, tilted towers, defects in conductor spacers, etc.

[0250] Specific location information of the abnormal location: geographical coordinate information of the abnormal location, usually expressed as (longitude, latitude, altitude).

[0251] Maintenance recommendations: Repair and maintenance recommendations are made based on any abnormal conditions found to ensure the safe operation of the transmission line.

[0252] Inspection completed: The flight equipment completes the inspection task according to the planned flight path.

[0253] Generate inspection report: The system generates an inspection report based on the data collected during the inspection process.

[0254] Abnormal status: abnormal conditions of the transmission line detected by the intelligent analysis module, such as line damage, hanging foreign objects, tilted towers, defects in conductor spacers, etc.

[0255] Record abnormal conditions: During the inspection process, the system records all abnormal conditions detected.

[0256] Location information: Geographic coordinate information of the abnormal location, including longitude, latitude and altitude.

[0257] Record location information: The system records the specific coordinate information of each abnormal location.

[0258] Maintenance suggestions: For each abnormal condition, the system generates corresponding maintenance suggestions, including maintenance methods, required materials and estimated maintenance time.

[0259] In the embodiment of the present application, it is assumed that a drone equipped with a multi-angle camera is used to inspect a power transmission line. The starting point of the power transmission line is A (longitude: 116.4074, latitude: 39.9042), and the end point is B (longitude: 116.4174, latitude: 39.9142). There are several support points in the middle, and the longitude and latitude coordinates of each support point are known. The flight path of the drone has been planned, the flight speed is 10m / s, and the flight altitude is 30 meters.

[0260] The drone completed the inspection mission of the transmission line according to the planned flight path.

[0261] The intelligent analysis module detected multiple abnormal conditions, including line damage, hanging foreign objects, tower tilt, and conductor spacer defects.

[0262] Line damage: A line damage was detected at (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters).

[0263] Hanging foreign object: A hanging foreign object was detected at (longitude: 116.4090, latitude: 39.9060, altitude: 30 meters).

[0264] Tower tilt: A tower tilt was detected at (longitude: 116.4095, latitude: 39.9065, height: 30 meters).

[0265] Conductor spacer defect: For example, a conductor spacer break is detected and the location is marked, such as the location (longitude: 116.4099, latitude: 39.9077, altitude: 30 meters);

[0266] Inspection report: The inspection report generated by the system contains the following contents:

[0267] Abnormal status:

[0268] Line damage: Location (longitude: 116.4085, latitude: 39.9055, altitude: 30 meters)

[0269] Foreign object hanging: Location (longitude: 116.4090, latitude: 39.9060, altitude: 30 meters)

[0270] Tower tilt: Location (longitude: 116.4095, latitude: 39.9065, height: 30 meters)

[0271] For example, conductor spacer defect: location (longitude: 116.4099, latitude: 39.9077, altitude: 30 meters);

[0272] Maintenance recommendations:

[0273] Line damage: It is recommended to immediately dispatch maintenance personnel to repair and replace the damaged line section. The estimated repair time is 2 hours.

[0274] Hanging foreign objects: It is recommended to dispatch maintenance personnel to remove the hanging foreign objects to ensure the safety of the line. The estimated maintenance time is 1 hour.

[0275] Tower tilt: It is recommended to reinforce or recalibrate the tilted tower to ensure the stability of the tower. The estimated maintenance time is 4 hours.

[0276] By generating an inspection report that includes all abnormal conditions found during the inspection, the specific location information of the abnormal location, and the corresponding maintenance suggestions, this solution achieves the following beneficial effects: The inspection report records in detail all abnormal conditions found during the inspection and their location information, which facilitates managers to fully understand the health status of the transmission line. For each abnormal condition, the system generates specific maintenance suggestions, including maintenance methods, required materials, and estimated maintenance time, providing maintenance personnel with clear operating guidelines. The detailed information and maintenance suggestions in the inspection report help maintenance personnel quickly locate problems, reduce maintenance time, and improve maintenance efficiency. By timely discovering and handling abnormal conditions, the safe operation of the transmission line is ensured and potential safety risks are reduced.

[0277] In summary, the optional solution proposed in the embodiment of the present invention effectively solves the problems of opaque inspection information, vague maintenance suggestions and low maintenance efficiency in the prior art, and improves the transparency and safety of transmission line inspection.

[0278] Figure 2 A schematic diagram of the structure of a transmission line side autonomous line-flying inspection system is provided for the present application embodiment. Figure 2 As shown, the system includes:

[0279] The receiving module 21 is used to receive the first position information of the flying device and the second position information of the target transmission line; the planning module 22 is used to plan a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can maintain autonomous flight within a safe distance range on the side of the transmission line; the acquisition module 23 is used to collect multi-angle image data of the transmission line and its surrounding environment in real time during the flight of the flying device along the flight path; the analysis module 24 is used to use the intelligent analysis module carried by the flying device to perform real-time analysis on the collected multi-angle image data, identify the transmission line, and analyze the image data. Abnormal conditions of electric lines, the abnormal conditions including line damage, hanging foreign objects, tilted pole towers, defects in conductor spacers (specifically including conductor spacer breakage, conductor spacer breakage, conductor spacer detachment, and missing bolt pins); an adjustment module 25, which is used to automatically adjust the flight attitude of the flying device when an abnormal condition is detected, so that the flying device can be inspected when it approaches the abnormal position, and the specific coordinate information of the abnormal position is recorded; a generation module 26, which is used to generate an inspection report after the flying device completes the inspection, the inspection report containing all abnormal conditions found during the inspection, the specific location information of the abnormal position, and the corresponding maintenance suggestions.

[0280] Figure 2 The transmission line side autonomous line imitation flight inspection system can perform Figure 1 The implementation principle and technical effects of the autonomous line-flying inspection method for the side of the transmission line described in the illustrated embodiment will not be repeated here.

[0281] In one possible design, Figure 2 The transmission line side autonomous line simulation flight inspection system of the embodiment shown can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32;

[0282] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0283] The processing component 32 is used to: receive the first position information of the flying device and the second position information of the target transmission line; plan a flight path along the transmission line according to the first position information and the second position information to ensure that the flying device can maintain autonomous flight within a safe distance range on the side of the transmission line; collect multi-angle image data of the transmission line and its surrounding environment in real time during the flight of the flying device along the flight path; use the intelligent analysis module on the flying device to perform real-time analysis on the collected multi-angle image data to identify abnormal conditions of the transmission line; when an abnormal condition is detected, automatically adjust the flight attitude of the flying device to allow the flying device to be inspected when it is close to the abnormal position, and record the specific coordinate information of the abnormal position; after the flying device completes the inspection, generate an inspection report.

[0284] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The transmission line side of the embodiment shown is autonomously simulated

[0285] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for autonomous line-flying inspection of the side of a power transmission line, characterized in that: include: receiving first location information of the flying device and second location information of the target power transmission line; Planning a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line; During the flight of the flying device along the flight path, real-time collection of multi-angle image data of the power transmission line and its surrounding environment; Using the intelligent analysis module on the flying device, the collected multi-angle image data is analyzed in real time to identify abnormal conditions of the transmission line, including line damage, hanging foreign objects, tilted towers, and defects in conductor spacers; When an abnormal state is detected, the flight attitude of the flying device is automatically adjusted so that the flying device is inspected when it approaches the abnormal position, and the specific coordinate information of the abnormal position is recorded; After the flight equipment has completed the inspection, an inspection report is generated, which includes all abnormal conditions found during the inspection, specific location information of the abnormal location, and corresponding maintenance suggestions.

2. The method according to claim 1, characterized in that The receiving first position information of the flying device and second position information of the target power transmission line includes: Acquire the current position coordinates of the flight device in real time through the global positioning system or the Beidou satellite navigation system as the first position information of the flight device; The geographic information system database or a pre-built digital map of power transmission lines is used to determine the geographic location information of the target power transmission line, including the latitude and longitude coordinates of the starting point, end point, and intermediate support points of the line, as the second location information of the target power transmission line.

3. The method according to claim 1, characterized in that The step of planning a flight path along the transmission line according to the first position information and the second position information to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line includes: Based on the first position information and the second position information, applying a path planning algorithm to determine a relative position relationship between the flying device and the target power transmission line; Based on the relative position relationship and the acquired flight speed and wind speed of the flying device, a series of discrete points along the direction of the transmission line are calculated to form a flight path along the direction of the transmission line; In the process of calculating a series of discrete points along the transmission line, it is ensured that each discrete point is located on one side of the transmission line and maintains at least a preset safety distance from the transmission line, and the preset safety distance includes the minimum safety distance between the flying device and the transmission line.

4. The method according to claim 1, characterized in that: The real-time collection of multi-angle image data of the power transmission line and its surrounding environment during the flight of the flying device along the flight path includes: The multi-angle camera equipped on the flying device is used to capture multi-angle image data of the power transmission line and its surrounding environment in real time. The camera can cover different viewing angles to ensure that the status information of the power transmission line can be fully captured; The intelligent analysis module carried by the flying device is used to analyze the collected multi-angle image data in real time to identify the abnormal state of the power transmission line, including: A deep learning algorithm is used to pre-train a neural network model for abnormal state recognition of power transmission lines. The neural network model can recognize a variety of abnormal states, including line damage, hanging foreign objects, tower tilt, and conductor spacer defects. The training data set contains a large number of labeled transmission line image samples in normal and abnormal states to ensure that the model has good generalization ability and high-precision recognition ability; The collected multi-angle image data is input into a trained neural network model, and the neural network model is used to perform real-time abnormal state recognition. The neural network model is used to extract features from the multi-angle image data and compare the features in the multi-angle image data with the features learned during training to determine whether there is an abnormal state in the transmission line.

5. The method according to claim 1, characterized in that When an abnormal state is detected, the flight attitude of the flying device is automatically adjusted so that the flying device is inspected when it approaches an abnormal position, and the specific coordinate information of the abnormal position is recorded, including: When an abnormal state is detected, the pixel coordinates of the abnormal position in the corresponding multi-angle image data are determined, and the specific coordinate information of the abnormal position is calculated by a geographic coordinate conversion algorithm in combination with the current position information of the flight device; According to the specific coordinate information of the abnormal position, the adjusted flight path and the corresponding attitude adjustment instructions are calculated; The flight attitude of the flying device is adjusted according to the adjusted flight path and the corresponding attitude adjustment instruction to ensure that the flying device can approach the abnormal position and perform an inspection.

6. The method according to claim 3, characterized in that The step of planning a flight path along the power transmission line according to the first position information and the second position information further includes: Calculating the optimal flight speed and flight altitude of the flying device to plan a flight path along the transmission line; The optimal flight speed and flight altitude of the flight device are calculated by the following formula: Where v(t) represents the flight speed of the flight equipment at time t, h(t) represents the flight altitude of the flight equipment at time t, v0 is the basic flight speed, H0 is the basic flight altitude, D(t) is the real-time flight distance between the flight equipment and the transmission line, T is the expected flight time, ΔW(t) is the difference between the actual wind speed at time t and the basic wind speed W0, ΔT a (t) is the difference between the actual air temperature at time t and the base temperature T a0 The difference, H max is the maximum flight altitude, k1, k2, k3, k4, k5, k6, k7, k8, k9, k 10 are the adjustment coefficients of the corresponding parameters respectively, P is the sine wave period in flight speed adjustment, Q is the cosine wave period in flight speed adjustment, R is the sine wave period in flight altitude adjustment, and S is the cosine wave period in flight altitude adjustment.

7. The method according to claim 5, characterized in that When an abnormal state is detected, automatically adjusting the flight attitude of the flying device also includes: Calculate the optimal flight path p(t) of the flying device when it approaches the abnormal position: Where t is time, p0 is the initial position, V0 is the initial velocity, a is the acceleration, a0 is the base acceleration, g is the acceleration due to gravity, w is the wind speed vector, n is the unit vector pointing to the abnormal position, m is the unit vector perpendicular to the flight path, b is the unit vector perpendicular to n and m, γ, δ, η are adjustment coefficients, and k 11 , k 12 , k 13 is the acceleration adjustment coefficient, and c is the angular velocity vector of the flight device.

8. A transmission line side autonomous line-flight inspection system, characterized in that: include: A receiving module, used for receiving first position information of the flying device and second position information of the target power transmission line; a planning module, configured to plan a flight path along the transmission line according to the first position information and the second position information, so as to ensure that the flying device can fly autonomously within a safe distance range on the side of the transmission line; A collection module, used for collecting multi-angle image data of the power transmission line and its surrounding environment in real time during the flight of the flying device along the flight path; An analysis module, used to use the intelligent analysis module carried by the flying device to perform real-time analysis on the collected multi-angle image data to identify abnormal conditions of the transmission line, wherein the abnormal conditions include line damage, hanging foreign objects, tilted towers, and defects in conductor spacers; An adjustment module, for automatically adjusting the flight attitude of the flying device when an abnormal state is detected, so that the flying device is inspected when it approaches an abnormal position, and records the specific coordinate information of the abnormal position; The generation module is used to generate an inspection report after the flight equipment completes the inspection. The inspection report contains all abnormal conditions found during the inspection, specific location information of the abnormal location, and corresponding maintenance suggestions.

9. A computing device, characterized in that It comprises a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement an autonomous line-simulating flying inspection method for the side of a transmission line as described in any one of claims 1-7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, an autonomous line-simulating flying inspection method for the side of a transmission line as described in any one of claims 1 to 7 is implemented.

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