Unmanned aerial vehicle mounted insulator vibration deicing device and deicing method

Abstract

The invention discloses an unmanned aerial vehicle mounted insulator vibration deicing device and deicing method, the unmanned aerial vehicle mounted insulator vibration deicing device comprises an insulating rod connected with an unmanned aerial vehicle, controllers symmetrically arranged at two ends of the insulating rod, an eccentric pump, a laser radar and a mechanical clamping jaw, and a supporting wheel is arranged in the mechanical clamping jaw. During working, an insulating rod is lifted through the unmanned aerial vehicle, an insulator is held through the mechanical clamping jaw, then the laser radar detects the thickness of an ice layer and transmits information to the position of the controller, the controller controls the action frequency of the eccentric pump, the eccentric pump acts to drive the arc-shaped clamping jaw to vibrate, and icing on the surface of the insulator can be effectively removed. Manual climbing is not needed, the labor intensity is reduced, the insulator is protected from being damaged through a vibration deicing mode, the vibration frequency can be adjusted, and the deicing efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent operation and maintenance of transmission lines, and specifically to an insulator vibration de-icing device and method mounted on an unmanned aerial vehicle (UAV). Background Art

[0002] The types of insulators for overhead transmission lines include composite insulators, glass insulators, and silicone rubber composite insulators. Ice coating on insulators poses a great threat to the stable operation of the power grid, and transmission lines in China have also suffered from different degrees of insulator ice coating disasters. Severe ice coating will lead to insulator flashover and line tripping accidents. The existing technologies have the following deficiencies: 1. Manual de-icing: The patent of insulator de-icing device CN201520286676.1 proposes to use a detachable de-icing shovel, which requires manual tower climbing operation. The risk of high-altitude de-icing is high and the de-icing efficiency is low. 2. Mechanical de-icing device: A patent of a UHV insulator de-icing device CN202121526264.2 uses a knocking device and a hot air blower to directly remove the ice coating on the insulator, which is easy to cause surface damage. 3. Thermal de-icing: A patent of an insulator de-icing device CN201920913338.4 uses an air duct and a blowing structure to blow out the heat of the heating wire to melt the ice coating on the insulator, with high energy consumption and a risk of thermal aging for composite material insulators.

[0003] Existing UAV de-icing: Most use a vibration mechanism and can only de-ice the conductor, such as the patent CN202210797969.0, which cannot be applied to insulator ice coating. Moreover, the existing vibration de-icing technologies mostly adopt a fixed frequency mode and cannot flexibly adjust according to the changes in the ice layer type and thickness, resulting in unstable de-icing effect or residual ice layer being difficult to completely remove. Summary of the Invention

[0004] The purpose of the present invention is to solve the above problems and provide an insulator vibration de-icing device and method mounted on a UAV, which can achieve automatic de-icing, reduce labor intensity, protect the insulator, and improve de-icing efficiency.

[0005] The technical solution adopted by the present invention to solve its technical problems is as follows:

[0006] An insulator vibration de-icing device mounted on a UAV includes an insulating rod connected to the UAV, a controller, an eccentric pump, a lidar, and mechanical claws symmetrically arranged at both ends of the insulating rod. A support wheel is provided inside the mechanical claws.

[0007] Furthermore, fixing frames are provided at both ends of the insulating rod.

[0008] Furthermore, the eccentric pump and the lidar are both installed on the fixing frame, and the mechanical claws are installed outside the fixing frame.

[0009] Furthermore, an insulator vibration de-icing method for an unmanned aerial vehicle (UAV) using the de-icing device includes the following steps:

[0010] a. Obtain the point cloud data of the insulator surface through lidar, extract the ice layer thickness and distribution characteristics from the point cloud data, and obtain the initial ice layer thickness value and ice type classification result;

[0011] b. Determine the natural frequency range according to the initial ice layer thickness value and the ice type classification result, and generate a vibration parameter combination;

[0012] c. Execute vibration according to the vibration parameter combination through an eccentric pump, and obtain the ice layer response data after de-icing;

[0013] d. Extract the remaining ice layer thickness and distribution characteristics from the ice layer response data, judge whether the remaining ice layer thickness is lower than a preset threshold, and obtain the de-icing completion status.

[0014] Furthermore, step a includes the following steps:

[0015] Scan the insulator surface through lidar to obtain the point cloud data;

[0016] Adopt a stereomicroscopic algorithm to extract the three-dimensional characteristics of the ice layer surface from the point cloud data, and determine the ice layer thickness and distribution characteristic parameters;

[0017] Perform a secondary measurement of the ice layer thickness through lidar, and fuse the initial ice layer thickness value to obtain accurate ice layer thickness data.

[0018] Furthermore, step b includes the following steps:

[0019] Match the ice type category corresponding to the initial ice layer thickness value from the preset database to obtain the natural frequency range;

[0020] Generate a vibration parameter combination of the eccentric pump according to the natural frequency range;

[0021] If the ice type classification result is mixed rime, generate a vibration parameter combination including low-frequency vibration and high-frequency vibration.

[0022] Furthermore, step c includes the following steps:

[0023] Execute vibration through the eccentric pump for a preset time;

[0024] Obtain the ice layer thickness data after vibration, switch to the sweep frequency mode to adjust the vibration frequency to cover the preset range;

[0025] Scan the insulator surface through the laser ranging unit to obtain the updated ice layer thickness data, and judge whether it is lower than the preset threshold.

[0026] Further, in step d, determining whether the residual ice layer thickness is lower than a preset threshold includes the following steps:

[0027] Determining whether the residual ice layer thickness is lower than a preset threshold includes:

[0028] Verifying the residual ice layer thickness through a millimeter lidar to obtain the thickness distribution characteristics;

[0029] Using an adaptive control algorithm to calculate the correction value of the vibration parameters according to the thickness distribution characteristics and generate an optimized vibration parameter combination;

[0030] Driving a vibration device to perform vibration through the optimized vibration parameter combination to obtain the final de-icing result.

[0031] The beneficial effects of the present invention are:

[0032] 1. The present invention includes an insulating rod connected to a drone, controllers, eccentric pumps, lidars, and mechanical claws symmetrically arranged at both ends of the insulating rod. A support wheel is provided inside the mechanical claw. During operation, the insulating rod is lifted by the drone, and the insulator is held by the mechanical claw. Then, the lidar detects the thickness of the ice layer and transmits the information to the controller. The controller controls the action frequency of the eccentric pump, and the action of the eccentric pump drives the arc-shaped claw to vibrate, which can effectively remove the ice covering the surface of the insulator. It does not require manual climbing, reduces labor intensity, protects the insulator from damage through the vibration de-icing method, the vibration frequency can be adjusted, and the de-icing efficiency is improved. By arranging a support wheel inside the mechanical claw, it is convenient for the mechanical claw to rise as the drone ascends without getting stuck, achieving comprehensive de-icing.

[0033] 2. The present invention scans the surface of the insulator through a lidar to obtain point cloud data and extract the ice layer thickness and distribution characteristics. Combining with a pre-established ice type frequency database, the natural frequency range and the initial value of the vibration parameters are determined. The present invention uses an adaptive control algorithm to dynamically adjust the vibration parameters according to the real-time updated ice layer state and generate a matching vibration waveform. The eccentric pump performs vibration de-icing while monitoring the ice layer response. If the residual ice layer thickness exceeds the threshold, the system automatically adjusts the parameters for a new round of de-icing. Through this closed-loop feedback mechanism, the present invention can precisely control the de-icing process, adapt to different ice types and thickness changes, and effectively improve the de-icing efficiency and completion rate. This method is especially suitable for de-icing live equipment in complex environments and has the characteristics of high safety and strong adaptability. Description of the Drawings

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0035] Figure 1 Structural schematic diagram of the present invention;

[0036] Figure 2 Flowchart of the present invention.

[0037] In the figure: insulating rod 1, controller 2, eccentric pump 3, lidar 4, mechanical gripper 5, fixing bracket 6, support wheel 7. Specific embodiments

[0038] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0039] As Figure 1 shown, an insulator vibration de-icing device mounted on a drone includes an insulating rod 1 connected to the drone, and controllers 2, eccentric pumps 3, lidars 4, and mechanical grippers 5 symmetrically arranged at both ends of the insulating rod 1. The mechanical gripper 5 is driven by a motor to hold the insulator, and a support wheel 7 is provided inside the mechanical gripper 5. During operation, the insulating rod 1 is lifted by the drone and the insulator is held by the mechanical gripper 5. Then, the lidar 4 detects the thickness of the ice layer and transmits the information to the position of the controller 2. The controller 2 controls the action frequency of the eccentric pump 3, and the action of the eccentric pump drives the arc-shaped gripper to vibrate, which can effectively remove the ice covering on the surface of the insulator. It does not require manual climbing, reduces labor intensity, protects the insulator from damage by the vibration de-icing method, and the vibration frequency can be adjusted to improve the de-icing efficiency. By providing a support wheel 7 inside the mechanical gripper 5, it is convenient for the mechanical gripper 5 to rise as the drone ascends without getting stuck, achieving comprehensive de-icing.

[0040] Fixing brackets 6 are provided at both ends of the insulating rod 1.

[0041] The eccentric pump 3 and the lidar 4 are both installed on the fixing bracket 6, and the mechanical gripper 5 is installed outside the fixing bracket 6.

[0042] As Figure 2 shown, a method for vibrating and de-icing insulators mounted on a drone includes the following steps:

[0043] a Obtain the point cloud data of the insulator surface through the lidar 4, extract the ice layer thickness and distribution characteristics from the point cloud data, and obtain the initial value of the ice layer thickness and the ice type classification result;

[0044] b Determine the natural frequency range according to the initial value of the ice layer thickness and the ice type classification result, and generate a vibration parameter combination;

[0045] c Execute vibration according to the vibration parameter combination through the vibration device, and obtain the ice layer response data after de-icing;

[0046] d Extract the residual ice layer thickness and distribution characteristics from the ice layer response data, judge whether the residual ice layer thickness is lower than a preset threshold, and obtain the de-icing completion status.

[0047] Step a includes the following steps:

[0048] Scan the insulator surface through the lidar 4 to obtain point cloud data, extract the ice layer thickness and distribution characteristics, and obtain the initial ice layer thickness value and the ice type classification result. Extract the three-dimensional characteristics of the ice layer surface from the point cloud data by using the stereomicroscopic algorithm to determine the ice layer thickness and distribution characteristic parameters. Use the lidar 4 to perform secondary measurement on the ice layer thickness, and fuse the initial ice layer thickness value to obtain accurate ice layer thickness data. If the accurate ice layer thickness data exceeds the preset threshold, query the preset database according to the ice type classification result to obtain the corresponding natural frequency range. According to the natural frequency range, use the dynamic programming algorithm to generate a vibration parameter combination, and determine the frequency and amplitude settings of the eccentric pump 3. Perform constant-frequency vibration according to the generated vibration parameters through the eccentric pump 3, switch to the frequency-sweeping mode after a preset time to remove the residual ice layer, and obtain the de-icing completion status. Extract the residual ice layer distribution characteristics from the de-icing completion status. If the residual ice layer distribution characteristics are lower than the preset threshold, it is determined that the de-icing process is over.

[0049] Scanning the insulator surface through the lidar to obtain point cloud data is the basis for realizing the extraction of the ice layer thickness and distribution characteristics.

[0050] For example, on the insulators of transmission lines in high-cold regions in winter, lidar can generate high-precision three-dimensional point cloud data by emitting laser pulses and receiving reflected signals to reflect the ice coverage. Each point in the point cloud data contains spatial coordinates, which can visually present the surface morphology of the ice layer. When extracting the ice layer thickness, it can be analyzed through the height difference of the point cloud. For example, if the reference height of the surface of a certain insulator is 0 and the point cloud shows that the height of a certain area increases to 5 mm, it can be preliminarily judged that the ice layer thickness is 5 mm. Ice type classification depends on the geometric features of the point cloud. For example, an ice layer with uniform coverage presents a smooth surface, while dendritic ice shows irregular protrusions. This method can quickly locate the problem areas of the ice layer and provide a basis for subsequent processing. Extracting the three-dimensional features of the ice layer surface from the point cloud data using a stereomicroscopic algorithm is a further refinement step.

[0051] Step b includes the following steps: Scanning the surface of the insulator through the eccentric pump 3 to obtain ice layer thickness data. Matching the ice type category corresponding to the ice layer thickness from the preset ice type frequency database to determine the natural frequency range. Generating a combination of vibration parameters according to the natural frequency range, including low-frequency vibration and high-frequency vibration. If the ice type is mixed rime, execute low-frequency vibration while executing high-frequency vibration for a fixed time. After vibrating for a fixed time, switch to the frequency sweep mode, adjust the vibration frequency to cover the preset range, and remove the residual ice layer. Scanning the surface of the insulator again through the lidar 4 to obtain the updated ice layer thickness data, and judge whether it reaches the preset threshold. If the ice layer thickness is higher than the preset threshold, re-match the ice type frequency according to the updated ice layer thickness data, generate a new combination of vibration parameters, and repeat the vibration operation.

[0052] Specifically, there may be multiple ice types stored in the database, such as hard rime, soft rime, and mixed rime, and each ice type corresponds to a specific thickness range and natural frequency.

[0053] For example, an ice layer thickness of 5.2 mm may match mixed rime, and its natural frequency range is 50 Hz to 120 Hz. The determination of this range provides a basis for the subsequent design of vibration parameters and avoids energy waste caused by blindly setting frequencies. Generating a combination of vibration parameters according to the natural frequency range, including low-frequency vibration and high-frequency vibration.

[0054] It is also possible to perform layered destruction according to the different physical properties of the ice layer. Low-frequency vibration loosens the ice layer structure, and high-frequency vibration breaks the surface of the ice layer to improve the de-icing efficiency.

[0055] Low-frequency vibration separates the ice layer from the surface of the insulator, and high-frequency vibration accelerates the fragmentation of the ice layer. This collaborative working method makes full use of the characteristics of both to ensure the comprehensiveness of the de-icing process. After vibrating for a fixed time, switch to the frequency sweep mode, adjust the vibration frequency to cover the preset range, and remove the residual ice layer.

[0056] It should be noted that the significance of repeated scanning verification is to monitor the de-icing progress in real time and avoid excessive vibration or missed residual ice. If the ice layer thickness is higher than the preset threshold, based on the updated ice layer thickness data, re-match the ice type frequency, generate a new combination of vibration parameters, and repeat the vibration operation.

[0057] Step c includes the following steps: Obtain the ice layer thickness data through the lidar 4 to determine the initial thickness value. Match the corresponding natural frequency range of the ice layer thickness according to the preset database to obtain the initial combination of vibration parameters. Use Fourier transform to process the data of the change of the ice layer thickness over time and judge the thickness change trend. If the thickness change trend exceeds the preset threshold, update the vibration parameters according to the dynamic adjustment demand signal and start the combined vibration. Obtain the data of the change of the ice layer thickness after the combined vibration, analyze the state of the residual ice layer through Fourier transform, and determine whether to switch to the frequency sweep mode. Adjust the natural frequency range in the frequency sweep mode to remove the residual ice layer and obtain the final thickness data. Verify the final thickness data through the millimeter-wave radar to judge whether the de-icing process is completed.

[0058] It can be understood that the database stores the ice type and frequency data corresponding to different ice thicknesses.

[0059] Exemplarily, if the ice thickness is 5 mm, the corresponding natural frequency range that may be matched is 20 - 50 Hz. At this time, the initial combination of vibration parameters can be set as the electromagnetic vibrator frequency of 25 Hz and the piezoelectric vibrator frequency of 45 Hz.

[0060] Specifically, this matching method is based on the physical properties of ice to ensure the pertinence of vibration. Use Fourier transform to process the data of the change of the ice layer thickness over time and judge the thickness change trend.

[0061] In a possible implementation, the thickness data is collected once per second, and a time series is formed continuously for 10 seconds. After Fourier transform, if the low-frequency components are significantly enhanced, it indicates that the ice layer starts to loosen.

[0062] For example, the initial 5 mm thickness becomes 4 mm after vibration, and the trend shows that the ice layer thinning rate is stable. This analysis helps to dynamically adjust the strategy. If the thickness change trend exceeds the preset threshold, update the vibration parameters according to the dynamic adjustment demand signal.

[0063] In step c: Obtain ice layer thickness data through lidar 4 to determine the initial ice layer distribution characteristics. Extract the natural frequency information from the initial ice layer distribution characteristics, and generate a vibration parameter combination in combination with a preset database. Activate the electromagnetic vibrator for the vibration parameter combination to obtain the residual ice layer data after preliminary de-icing. Perform high-frequency vibration processing on the residual ice layer data through a piezoelectric vibrator to obtain the updated thickness distribution. Extract the residual ice layer characteristics from the updated thickness distribution and determine whether it is below the clearing threshold. If it is not below the clearing threshold, switch to the frequency sweep mode to process the residual ice layer to obtain the de-icing completion result. Classify the de-icing completion result through a random forest algorithm to determine the final de-icing state.

[0064] The physical properties of the ice layer can be queried through a preset database. The natural frequency of the ice layer is closely related to its thickness, density, and attachment state.

[0065] Exemplarily, for a 5-mm thick uniform ice layer, the database may show that its natural frequency is about 200 Hz, while the frequency of a 10-mm thick ice layer may drop to 150 Hz. When generating the vibration parameter combination in combination with the database, the output power and vibration frequency of the electromagnetic vibrator can be designed according to the frequency range to ensure matching with the ice layer characteristics.

[0066] For example, for an ice layer with a frequency of 200 Hz, the vibration parameters can be set to a narrow-band vibration of 180 to 220 Hz to avoid damage to the insulator body. After activating the electromagnetic vibrator for the vibration parameter combination, obtaining the residual ice layer data after preliminary de-icing is a possible implementation.

[0067] For a 3-mm thick residual ice layer, a high-frequency vibration of 500 Hz can be applied to further fragment and shed the ice layer. The updated thickness distribution can be confirmed by a millimeter-wave radar. For example, the thickness may drop below 1 mm. This high-frequency vibration can accurately act on the thin ice layer to avoid excessive stress on the insulator surface. When extracting the residual ice layer characteristics from the updated thickness distribution and determining whether it is below the clearing threshold.

[0068] For example, 1 mm can be set as the clearing threshold. If the thickness is below this value, it is considered that the de-icing has reached the standard. If it is not below the threshold, switch to the frequency sweep mode to process the residual ice layer.

[0069] In one embodiment, the frequency sweep mode can gradually increase from 100 Hz to 600 Hz for 30 seconds to cover various ice layer frequency characteristics.

[0070] For example, the residual ice layer may completely fall off under the action of the frequency sweep, and the millimeter-wave radar shows that the thickness is close to 0 mm, indicating a high de-icing completion. When classifying the de-icing completion result through a random forest algorithm.

[0071] Specifically, the thickness, ice layer distribution uniformity, and residual area can be used as input features, and the de-icing state category can be output.

[0072] For example, a thickness below 1 mm with uniform distribution can be classified as "complete de-icing", while a thickness between 1 and 2 mm with non-uniform distribution can be classified as "further treatment required". Through the integration judgment of multiple decision trees, the random forest can improve the robustness of classification.

[0073] For example, in one operation, the algorithm analysis shows that 95% of the insulator surface reaches the "complete de-icing" state, confirming the completion of the de-icing task. This classification method can provide clear guidance for subsequent maintenance decisions.

[0074] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by terms such as "left", "right", "upper", "lower", etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention.

[0075] In the description of the present invention, it should be noted that unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection, an electrical connection, a direct connection, or an indirect connection through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

Claims

1. An insulator vibration de-icing device mounted on a drone, characterized in that, It includes an insulating rod (1) connected to a drone, controllers (2), eccentric pumps (3), lidars (4) and mechanical grippers (5) symmetrically arranged at both ends of the insulating rod (1), and support wheels (7) are provided inside the mechanical grippers (5).

2. The insulator vibration de-icing device mounted on a drone according to claim 1, characterized in that, Fixed frames (6) are provided at both ends of the insulating rod (1).

3. The insulator vibration de-icing device mounted on a drone according to claim 2, characterized in that, The eccentric pumps (3) and lidars (4) are both installed on the fixed frames (6), and the mechanical grippers (5) are installed outside the fixed frames (6).

4. A method for removing ice from insulators mounted on an unmanned aerial vehicle, using the ice removal device described in any one of claims 1 to 3, characterized in that, It includes the following steps: a Obtain the point cloud data of the insulator surface through the lidar (4), extract the ice layer thickness and distribution characteristics from the point cloud data to obtain the initial value of the ice layer thickness and the ice type classification result; b Determine the natural frequency range according to the initial value of the ice layer thickness and the ice type classification result, and generate a vibration parameter combination; c Execute vibration according to the vibration parameter combination through the eccentric pump (3) to obtain the ice layer response data after deicing; d Extract the residual ice layer thickness and distribution characteristics from the ice layer response data, and judge whether the residual ice layer thickness is lower than a preset threshold to obtain the deicing completion status.

5. The method for removing ice from insulators mounted on an unmanned aerial vehicle according to claim 4, characterized in that, Step a includes the following steps: Scan the insulator surface through the lidar to obtain the point cloud data; Adopt a stereomicroscopic algorithm to extract the three-dimensional characteristics of the ice layer surface from the point cloud data to determine the ice layer thickness and distribution characteristic parameters; Perform a secondary measurement of the ice layer thickness through the lidar and fuse the initial value of the ice layer thickness to obtain accurate ice layer thickness data.

6. The insulator vibration de-icing method mounted on a drone as described in claim 4, characterized in that, Step b includes the following steps: Match the ice type category corresponding to the initial value of the ice layer thickness from a preset database to obtain the natural frequency range; Generate a vibration parameter combination of the eccentric pump (3) according to the natural frequency range; If the ice type classification result is mixed rime, generate a vibration parameter combination including low-frequency vibration and high-frequency vibration.

7. The method for removing ice from insulators mounted on an unmanned aerial vehicle according to claim 4, wherein Step c includes the following steps: Execute vibration through the eccentric pump (3) for a preset time; Obtain the ice layer thickness data after vibration, switch to the sweep frequency mode to adjust the vibration frequency to cover a preset range; Scan the insulator surface through the laser ranging unit to obtain the updated ice layer thickness data and judge whether it is lower than a preset threshold.

8. The method for removing ice from insulators mounted on an unmanned aerial vehicle according to claim 4, characterized in that, In step d, judging whether the residual ice layer thickness is lower than a preset threshold includes the following steps: Judging whether the residual ice layer thickness is lower than a preset threshold includes: Verify the residual ice layer thickness through the lidar to obtain the thickness distribution characteristics; Adopt an adaptive control algorithm to calculate the correction value of the vibration parameters according to the thickness distribution characteristics and generate an optimized vibration parameter combination; Drive the vibration device to execute vibration through the optimized vibration parameter combination to obtain the final deicing result.

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