A lightning protection conduction nondestructive detection system and method for a wind power blade

Abstract

The application provides a lightning protection conduction nondestructive detection system and method for a wind power blade, the detection system comprising: a flight platform and a multifunctional detection device module, the multifunctional detection device module being arranged on the flight platform; the multifunctional detection device module comprising a phased array ultrasonic detection unit and a conduction electrical test unit, so as to realize high-precision detection of internal defects of the wind power blade and nondestructive detection of conduction performance in a single flight. The application deeply integrates a UAV, phased array ultrasonic technology, conduction electrical test and artificial intelligence analysis, and solves problems such as difficulty in detecting internal defects, low efficiency and poor safety in the traditional method.

Description

Technical Field

[0001] This invention relates to the field of wind power equipment testing technology, and more specifically, to a non-destructive testing system and method for the lightning protection conductivity of wind turbine blades. Background Technology

[0002] With the continued growth in global demand for clean energy, wind power, as an important component of renewable energy, is experiencing continuous expansion in installed capacity, leading to increasingly complex operating environments for wind turbine equipment. Wind turbine blades, as one of the most critical and environmentally vulnerable components of a wind turbine, are frequently threatened by lightning strikes during long-term operation. Statistics show that approximately 80% of blade damage incidents in wind farms are related to lightning strikes. If lightning current cannot be effectively discharged, it can cause composite material ablation, structural delamination, core material damage, and even fracture of the main load-bearing structure, seriously threatening the safe operation of the turbine and the stability of the power grid.

[0003] To address this challenge, modern large wind turbine blades typically integrate built-in lightning protection systems at the blade tip, leading edge, and main beam area. These systems usually consist of lightning arresters, a lower lead conductor network, and a grounding device. Their core function is to provide a low-impedance path for lightning current, enabling rapid discharge. However, due to the long-term exposure of blades to harsh conditions such as high dynamic loads, strong ultraviolet radiation, and drastic temperature and humidity changes, the conductive path of the lightning protection system may experience problems such as localized fractures, poor contact, debonding, or corrosion due to material aging, vibration fatigue, or manufacturing defects. This weakens the overall conductivity and creates significant safety hazards.

[0004] Currently, the testing of the conductivity of wind turbine blade lightning protection systems mainly relies on traditional methods, such as visual inspection and DC resistance measurement. Visual inspection can only detect obvious surface damage and is completely powerless to detect defects such as wire breakage and interface debonding hidden inside carbon fiber reinforced composite materials or glass fiber layers. While traditional resistance measurement can be used to assess the overall circuit resistance, it has significant limitations: First, this method requires applying current and contacting electrodes between the blade root and tip, necessitating shutdown and high-altitude operation, which is risky and costly. Second, the measurement results reflect the average resistance value of the entire conductive path, failing to locate millimeter-level local damage and making it even more difficult to identify local impedance increases caused by micro-cracks or interlayer separation, posing a risk of "false safety assessment."

[0005] Furthermore, existing testing technologies generally lack the ability to jointly assess the spatial distribution characteristics and internal structural integrity of lightning protection systems. For example, when localized pores, resin accumulation, or fiber breaks exist in the conductor's downlead path, although the overall resistance remains within acceptable limits, localized hotspots may trigger high-temperature burn-through during a lightning strike, causing catastrophic consequences. Simultaneously, traditional methods cannot penetrate non-metallic composite material structures for non-destructive testing, resulting in numerous potential defects remaining dormant until a fault occurs, severely impacting maintenance efficiency and equipment reliability.

[0006] In recent years, some studies have attempted to introduce non-destructive testing technologies such as ultrasonic waves, infrared thermography, or X-ray tomography. However, these technologies still face many bottlenecks in wind power field applications: ultrasonic testing requires a coupling medium, making it unsuitable for high-altitude curved structures; X-ray radiation is strong and the equipment is bulky, making it unsuitable for field operations; infrared thermography is sensitive to surface thermal effects but slow to respond to deep conductivity anomalies. Therefore, there is an urgent need for an efficient, accurate, and fully automated non-destructive testing solution for lightning protection conductivity that is suitable for the special structure and operating environment of wind turbine blades.

[0007] Against this backdrop, combining advanced sensing technologies with intelligent mobile platforms to develop new detection systems has become a key direction for overcoming existing technological bottlenecks. Of particular note is the fact that spherical unmanned aerial vehicles (UAVs), due to their compact size, stable flight, strong wind resistance, and ability to cruise close to natural walls, offer entirely new possibilities for the autonomous detection of complex curved structures at high altitudes. By combining various measurement technologies with multi-source data fusion analysis techniques, it is expected to achieve comprehensive and high-precision evaluation of wind turbine blade lightning protection systems, from surface to interior, and from macroscopic conductivity to microscopic defects.

[0008] Chinese patent CN120294623A discloses a wind turbine blade lightning protection conductivity testing device based on a drone, including a drone and a ground measuring device, as well as a probe rod mounted on the drone. A metal mesh assembly is elastically connected to the end of the probe rod, and the metal mesh assembly is connected to the ground measuring device via wires. This device mainly consists of rod-shaped and mesh-like structures, exhibiting low wind resistance, simple assembly, stability, reliability, convenient operation, and high safety. In this structure, the contact angle of the metal mesh can automatically adjust according to the attitude of the blade tip lightning arrester, ensuring good contact and improving detection accuracy. The elastic connection component also prevents damage to the drone. However, this device only optimizes the probe rod assembly and does not incorporate multi-functional integrated design at the overall system level. Therefore, it lacks the capability to achieve full-coverage, three-dimensional, intelligent, and non-destructive testing of internal defects in wind turbine blades and lightning protection systems on a single flight platform.

[0009] Therefore, there is a need for a non-destructive testing system and method for the lightning protection conductivity of wind turbine blades to meet the requirements for non-destructive testing of the lightning protection system of wind turbine blades. Summary of the Invention

[0010] The purpose of this invention is to provide a non-destructive testing system and method for lightning protection conductivity of wind turbine blades, which can be used to efficiently and accurately identify internal defects and assess conductivity status in key areas of wind turbine blades.

[0011] To achieve the above objectives, this invention provides a non-destructive testing system and method for the lightning protection conductivity of wind turbine blades. The technical solution of this invention is implemented as follows:

[0012] A non-destructive testing system for the lightning protection conductivity of wind turbine blades is disclosed. The testing system includes a flight platform and a multi-functional testing device module, which is mounted on the flight platform. The multi-functional testing device module includes a phased array ultrasonic testing unit and a conductivity electrical testing unit, so as to achieve high-precision detection of internal defects of wind turbine blades and non-destructive testing of their conductivity performance in a single flight.

[0013] Furthermore, the phased array ultrasonic detection unit has an adjustable operating frequency of 2~10MHz to adapt to different thickness regions; the operating frequency is 2~5MHz for thick cross-section regions to enhance penetration; and the operating frequency is 6~10MHz for thin-walled or fine structures to improve resolution.

[0014] Furthermore, the lightning protection conductivity electrical detection unit uses pulsed current to measure the conductivity equivalent impedance.

[0015] Furthermore, the pulse current is a 0.5~2A pulse square wave with a duration of 5~30ms.

[0016] Furthermore, the detection system also includes a data communication and control module, a ground control and data processing module, and an intelligent analysis and report generation module.

[0017] Furthermore, the multifunctional detection device module also includes high-definition visual acquisition equipment, including a visible light camera, an infrared thermal imager, and image-aiding function equipment.

[0018] A non-destructive testing method for the lightning protection conductivity of wind turbine blades, using the aforementioned testing system, includes the following steps:

[0019] S0, Preparation before testing;

[0020] S1, Flight Inspection, including phased array ultrasonic testing, lightning protection conductivity electrical testing, and visual acquisition;

[0021] S2, Data Acquisition;

[0022] S3, Data Analysis;

[0023] S4 generates a comprehensive test report.

[0024] Furthermore, the phased array ultrasonic testing process includes: hovering the UAV to bring the probe close to or against the blade surface; starting the scanning program and focusing on the following areas: the root of the lightning arrester mainly focuses on delamination, debonding, and cracks to ensure that the lightning current is smoothly conducted into the lower lead; the metal anchoring area mainly focuses on porosity, corrosion, and loosening to verify the reliability of the electrical connection; the lower lead connection point mainly focuses on breakage and poor contact to ensure the continuity of the entire conduction path.

[0025] Furthermore, the lightning protection conductivity electrical testing process includes: the robotic arm of the UAV drives the electrode to contact the designated test point on the blade surface, introduces current, and simultaneously measures the resistance value; the resistance measurement results are all bound to the location information to form a thermal map of the conductivity resistance distribution.

[0026] Furthermore, the visual acquisition includes: using a visible light camera to photograph the appearance of the lightning arrester, the connection status of the wires, and traces of corrosion; using an infrared thermal imager to detect localized heating caused by excessive contact resistance; and using an image-assisted function device to identify the blade number and the lightning arrester label.

[0027] Compared with existing technologies, the non-destructive testing system and method for lightning protection conductivity of wind turbine blades described in this invention have the following advantages:

[0028] 1. Non-destructive testing: The entire process does not damage the blade structure or lightning protection system, and does not affect the normal operation of the equipment.

[0029] 2. High sensitivity and high precision: It can detect internal defects at the millimeter level, with positioning accuracy at the millimeter level and small resistance measurement accuracy of 0.1mΩ.

[0030] 3. Comprehensive coverage and significantly improved inspection efficiency: The spherical drone flies flexibly, breaking through the high-altitude blind spots that are difficult for humans to reach; a single flight can obtain comprehensive and full-performance measurements, and the system inspection fully covers surface and internal defects, taking into account electrical conductivity and material integrity; the inspection time of a single blade is reduced by more than 80% compared with traditional methods, and it supports remote monitoring and batch processing.

[0031] 4. Intelligent analysis and strong environmental adaptability: Supports intelligent diagnosis and resistance thermogram construction to facilitate predictive maintenance; combines machine learning and multi-source data fusion to achieve automatic defect identification and risk level assessment; introduces environmental compensation mechanisms and personalized modeling to effectively cope with the challenges of temperature and humidity changes and structural diversity. Attached Figure Description

[0032] Figure 1 This is a flowchart of the non-destructive testing system for lightning protection conductivity of wind turbine blades as described in Embodiment 1 of the present invention. Detailed Implementation

[0033] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the described embodiments are only some, not all, of the embodiments of this invention. The specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. It should be noted that, unless otherwise specified, the embodiments and features described in these embodiments can be combined with each other.

[0034] This invention provides a non-destructive testing system for the lightning protection conductivity of wind turbine blades. The system uses an unmanned aerial vehicle (UAV) as a carrier and integrates multimodal sensing technology and an intelligent analysis platform to achieve efficient and accurate detection of the internal lightning protection paths of wind turbine blades. The testing system includes: a flight platform, a multi-functional testing device module, a data communication and control module, a ground control and data processing module, and an intelligent analysis and report generation module.

[0035] The flight platform provides high-altitude operation capabilities, features wind-resistant stability and collision protection structures, and adapts to complex weather environments; it supports hovering, wall-hugging flight, and automatic obstacle avoidance. A spherical unmanned aerial vehicle (UAV) flight platform is preferred.

[0036] The spherical drone flight platform features a fully enclosed spherical frame, providing excellent aerodynamic performance and mechanical protection to prevent propeller blades from impacting the blade surface. For the power system, it is equipped with a high-torque brushless motor and vector thrusters, supporting six degrees of freedom of motion, enabling stable attachment to vertical walls or curved surfaces. For navigation and positioning, it incorporates a GNSS+IMU inertial navigation system for coarse outdoor positioning; supplemented by UWB ultra-wideband positioning and visual SLAM, it achieves centimeter-level precise positioning. In terms of power management, it uses a high-energy-density lithium battery, providing a flight time of ≥30 minutes, and supports quick replacement and hot-swapping.

[0037] The multi-functional detection device module includes: a phased array ultrasonic testing unit (PAUT), a continuity electrical testing unit, and a high-definition visual acquisition device, enabling simultaneous perception of multiple physical fields.

[0038] The phased array ultrasonic testing unit is used to detect internal defects in wind turbine blades, enabling precise location and quantitative analysis of these defects to support engineering decisions. It employs a 64- or 128-element linear / matrix array probe; the operating frequency is adjustable from 2 to 10 MHz to adapt to different thickness regions. A flexible piezoelectric film probe coupled with a micro-water mist coupling system reduces dependence on blade surface cleanliness. Imaging modes support A-scan, B-scan, S-scan, and C-scan 3D reconstruction. A curved adaptive design conforms to the blade's leading edge radius (R-angle), while supporting dynamic focusing and electronic deflection scanning to improve detection coverage and sensitivity. Considering both penetration depth and resolution, a lower frequency (2-5 MHz) is used for thick cross-section areas (such as the blade root) to enhance penetration; a higher frequency (6-10 MHz) is used for thin-walled or delicate structures (such as the lower lead wire interface) to improve resolution.

[0039] The lightning protection continuity electrical testing unit employs a low-resistance pulsed current injection method to measure the equivalent impedance between the lightning arrester and the root grounding terminal. The pulsed current is a 0.5~2A square wave with a duration of 5~30ms. The current amplitude and pulse width are dynamically adjusted according to the blade length, material resistivity, or contact condition to avoid undetectable signals due to excessively small signals or localized heating caused by excessively large currents. Furthermore, when there is slight oxidation, contamination, or pressure unevenness between the electrode and the blade surface coating, the signal-to-noise ratio can be enhanced by appropriately increasing the current to ensure measurable voltage.

[0040] Test the designated points on the blade surface (such as the top of the lightning arrester or the connection of the lower lead) by contacting them with telescopic or flexible electrodes, avoiding damage to the coating.

[0041] The parameters are: resolution ≤ 1mΩ; a judgment threshold of <50mΩ is considered good conduction, and >100mΩ indicates a risk of poor contact or breakage. It can display impedance change curves in real time and mark abnormal sections based on location information.

[0042] High-definition visual acquisition equipment includes: a visible light camera with a resolution of no less than 20 megapixels, supporting optical zoom and autofocus, used to capture images of the appearance of the lightning arrester, the connection status of the wires, corrosion and cracks; an infrared thermal imager with a resolution of no less than 640×512, used to detect localized heating caused by excessive contact resistance; and image-aided function equipment capable of OCR recognition of numbered labels and AI image classification to determine the level of damage.

[0043] The data communication and control module enables two-way wireless communication between the UAV and the ground control station, including command transmission, real-time video feedback, ultrasonic data stream upload, and remote control. The communication link includes a primary link and a backup link. The primary link is a 5G / Wi-Fi 6 dual-mode communication, ensuring high-speed data feedback (>100Mbps); the backup link is a LoRa long-range low-power communication for emergency command transmission. For remote control and telemetry, the ground control station can set the flight path, start detection programs, and view real-time images and sensor data through a graphical interface; it supports switching between manual intervention and fully automatic detection modes.

[0044] The ground control and data processing module includes a ground control station, a data storage server, and a preliminary processing unit, responsible for mission planning, status monitoring, raw data reception, and preprocessing. Hardware configuration includes an industrial-grade laptop or edge computing box; it also features a solid-state drive array for large-capacity data storage. On the software side, it has mission scheduling capabilities, can import blade CAD models, and automatically generate optimal detection paths; it has real-time monitoring capabilities, displaying the UAV's attitude, battery level, signal strength, and current detection location; and it has data caching and preprocessing functions, performing noise reduction, filtering, and gain compensation on the received ultrasonic signals.

[0045] The intelligent analysis and report generation module uses machine learning models to identify defects, assess continuity, and automatically generate structured inspection reports, supporting visualization and historical data comparison. The core algorithm flow is: raw data - cleaning and normalization / feature extraction - multi-source fusion / machine learning modeling - defect identification results.

[0046] The system comprehensively detects both surface and internal defects, balancing electrical conductivity and material integrity. It is easy to operate, requiring no scaffolding or suspended platforms, and can be remotely controlled, reducing labor costs and safety risks. The system boasts high detection accuracy; PAUT achieves millimeter-level resolution, and C-scan 3D imaging intuitively presents defect morphology. It has a fast response time, reducing single-blade inspection time by 80%, and supports batch inspections and emergency troubleshooting. The system is highly intelligent, with AI models automatically identifying defects, reducing human error. It is also highly scalable, capable of connecting to a wind power intelligent operation and maintenance cloud platform for long-term health monitoring and trend prediction.

[0047] Example 1

[0048] This embodiment provides a non-destructive testing system for the lightning protection conductivity of wind turbine blades, comprising: a spherical unmanned aerial vehicle (UAV) flight platform; a multi-functional testing device module integrating a phased array ultrasonic testing unit, a conductivity electrical testing unit, and a high-definition visual acquisition system; a data communication and control module; a ground control and data processing system; and an intelligent analysis and report generation system. The testing system is applicable to composite material blades with a length of 60-100 meters in onshore and offshore wind turbine generators, especially for high-precision identification of internal defects and assessment of electrical conductivity in key areas of their built-in lightning protection paths (such as the root of the lightning arrester, the metal anchoring area, and the lower lead connection point).

[0049] The spherical UAV adopts a fully enclosed carbon fiber frame structure, providing excellent wind resistance and collision protection. The power system is equipped with six high-torque brushless motors, supporting six-axis vector propulsion, achieving a maximum flight speed of 12 m / s and stable hovering in winds up to level 7. The navigation and positioning system is GNSS+IMU inertial navigation, achieving coarse outdoor positioning (accuracy ±30cm); supplemented by UWB ultra-wideband base stations (deployed around the tower) and monocular visual SLAM algorithms, it achieves centimeter-level precise positioning (error ≤5cm) during wall-hugging flight. In terms of endurance, it is equipped with two hot-swappable 22,000mAh lithium batteries, providing a single operation time of ≥35 minutes, meeting the requirements for complete single-blade inspection. It has a built-in obstacle avoidance radar and emergency return-to-home procedure, automatically returning to the starting position in case of strong winds or signal interruption. The UAV can perform wall-hugging flight missions along the surface of wind turbine blades under remote operator control or preset flight path modes, ensuring a constant distance (ideally 1~3cm) between the inspection probe and the blade surface.

[0050] The multi-functional testing device module includes: a phased array ultrasonic testing unit, a lightning protection conductivity electrical testing unit, and a high-definition visual acquisition device.

[0051] In this embodiment, the phased array ultrasonic detection unit uses a 128-chip linear array probe with an adjustable center frequency range of 2~10MHz. For thick cross-sectional areas at the leaf root (thickness > 30mm), a 4MHz low-frequency band is used to enhance penetration depth; for delicate structures such as thin-walled areas at the leading edge or lower lead interface, the frequency is switched to an 8MHz high-frequency band to improve spatial resolution; a flexible silicone membrane layer is provided at the probe front end, which, together with a micro-water mist coupling system, achieves good acoustic coupling without the need for large amounts of water spray.

[0052] Supports electronic focusing and sector scanning (S-scan), and can complete multi-angle imaging without moving the probe; real-time generates B-scan cross-sectional views and C-scan three-dimensional reconstruction images with a resolution of 1mm×1mm, reconstructs multiple two-dimensional scanning slices into a three-dimensional image, clearly presents the spatial distribution of defects, and assists in engineering decisions. During the detection process, the system records the spatial coordinates of each detection point provided by the UAV positioning system and the corresponding ultrasonic A-scan waveform data, and establishes a "position-signal" mapping database.

[0053] For electrical detection, the pulsed current injection method is used to measure the equivalent DC resistance between the tip of the lightning arrester and the grounding end of the blade root. During detection, two spring-loaded copper alloy electrodes are driven by the robotic arm of the UAV to contact the specified test points on the blade surface to avoid damaging the coating; current is introduced while measuring the resistance value. Preferably, the test voltage ≤ 12V to ensure safety; the injected current is a 1A pulsed square wave with a duration of 10ms; the measurement resolution is 0.1mΩ. The judgment criteria are: good conduction when R ≤ 50mΩ; mild poor contact when 50mΩ < R ≤ 100mΩ, and it is recommended to track and observe; abnormal conduction is determined when R > 100mΩ, and further investigation of the risk of fracture or corrosion is required. All resistance measurement results are bound to the GPS position information to form a "conduction resistance distribution heat map".

[0054] The traditional resistance measurement method can only reflect the overall conductivity of the lightning protection system and cannot detect local fractures, corrosion or poor contact of internal wires. By using the pulsed current injection method and combining it with GPS position binding, the equivalent DC resistance can be measured point by point along the blade length direction to form a high-resolution "conduction resistance distribution heat map". If a certain section of the down conductor has poor conduction, the abnormal resistance area can be accurately located, compensating for the deficiencies of the traditional method.

[0055] Associating the resistance data with the spatial position to generate an intuitive heat map enables the operation and maintenance personnel to clearly understand the conductivity differences of each section in the lightning protection path, provides accurate position guidance for subsequent repairs, and improves the interpretability and engineering practicability of the detection results. This setting can improve the spatial resolution ability and defect location accuracy of the lightning protection system conductivity detection of wind turbine blades, and achieve a technical upgrade from "overall judgment" to "local diagnosis".

[0056] The high-definition visual acquisition system includes a visible light camera, an infrared thermal imager, and image-aiding devices. The visible light camera is 20 megapixels with 10x optical zoom, supporting autofocus and HDR imaging, used to capture images of the lightning arrester's appearance, wire connection status, and corrosion marks. The infrared thermal imager has a resolution of 640×512, a temperature measurement range of −20°C to +150°C, and an accuracy of ±2°C, used to detect localized heating caused by excessive contact resistance. The image-aiding devices use OCR technology to identify blade numbers and lightning arrester labels; they can also determine the damage level (normal / minor / severe) based on an image classification model.

[0057] The data communication and control module includes: a main communication link with 5G+Wi-Fi6 dual-mode transmission to ensure real-time transmission of raw ultrasonic data (rate >80Mbps); and a backup link: a LoRa long-range communication module for issuing emergency commands (such as power failure or return to base). The ground control station sets the flight path and starts the detection program through a graphical interface; it supports switching between fully automatic inspection and manual intervention modes; and it displays the UAV's attitude, battery level, signal strength, current detection location, and sensor readings in real time.

[0058] The ground control and data processing module includes: a ruggedized industrial-grade laptop (Intel i7 processor, 32GB RAM, 1TB SSD); and an external solid-state drive array (total capacity 4TB) for long-term storage of detection data. Software functions include: importing blade CAD models and automatically generating the optimal detection path; real-time reception and caching of multi-source data such as ultrasonic signals, images, and resistance values; and performing preliminary preprocessing to achieve noise reduction (wavelet threshold filtering), gain compensation, and time correction.

[0059] The intelligent analysis and report generation module is used to perform data analysis and automatically generate structured inspection reports based on the analysis results.

[0060] Example 2

[0061] A non-destructive testing method for the lightning protection conductivity of wind turbine blades includes the following steps:

[0062] S0, Pre-test preparation, including the following steps:

[0063] S01, Data Collection. Collect information such as the model of the wind turbine to be inspected, blade structure drawings, lightning protection system layout diagram, and historical maintenance records to identify key inspection areas.

[0064] S02, On-site Survey. Conduct an on-site survey of the wind farm environment, assess wind speed, humidity, and light conditions; confirm the cleanliness of the blade surface, including the presence of factors affecting coupling such as ice and dust accumulation; and formulate the optimal flight path and detection strategy.

[0065] S03, Equipment Debugging. Calibrate and test the spherical UAV and its onboard equipment to ensure the ultrasonic transmitter / receiver channels are functioning correctly, and set initial testing parameters, including frequency, gain, and delay rules.

[0066] S04, Flight Path Planning. Based on the preliminary preparation conditions and information, design the drone's flight path.

[0067] S1, Flight Detection, includes the following steps:

[0068] S11, Equipment Deployment and Flight Preparation. Transport the spherical UAV to the designated location, install PAUT probes and other equipment, and establish wireless communication links; set up an automatic flight path according to the prior plan to ensure coverage of all key areas.

[0069] S12, Flight Detection: The operator remotely controls the drone via a ground control station to fly along a predetermined trajectory to the target area. This includes one or more of the following detections:

[0070] S121, Phased Array Ultrasonic Testing. The drone hovers, bringing the PAUT probe close to or against the blade surface. The scanning program is initiated, focusing on the following areas: the lightning arrester root area, primarily focusing on delamination, debonding, and cracks to ensure smooth conduction of lightning current to the lower lead; the metal anchoring area, primarily focusing on porosity, corrosion, and loosening to verify the reliability of the electrical connection; and the lower lead connection point, primarily focusing on breakage and poor contact to ensure continuous conduction throughout the entire path.

[0071] S122, Electrical Detection for Lightning Protection Conductivity. The drone's robotic arm drives two spring-loaded copper alloy electrodes to contact designated test points on the blade surface (avoiding damage to the coating), introducing current and simultaneously measuring the resistance value. When the drone's flight attitude is unstable, the robotic arm's contact time is brief; a short pulse (5-10ms) can be set to quickly complete a measurement. If the initial measurement is abnormal, multiple pulses can be repeated and averaged to improve data reliability. Resistance measurement results are linked to GPS location information to form a "continuity resistance distribution heatmap," enabling defect location (e.g., a sudden increase in resistance in a certain section) and historical trend comparison (tracking corrosion development).

[0072] S123, Visual Acquisition. The drone is equipped with a high-definition visual acquisition system, including a visible light camera, an infrared thermal imager, and image-aided functions. The visible light camera captures images of the lightning arrester's appearance, wire connection status, and corrosion marks. The infrared thermal imager is used to detect localized overheating caused by excessive contact resistance. The image-aided functions can identify blade numbers and lightning arrester tags; it can also determine the damage level in real time based on an image classification model.

[0073] S2, Data Acquisition. The acquired data includes: raw signals from various detection systems acquired in real time, as well as system control information, location information, etc. Data is acquired and transmitted synchronously for subsequent image feature extraction and fusion analysis. All data is compressed and encrypted before being uploaded to a ground server for storage in real time.

[0074] S3, Data Analysis. The process includes:

[0075] S31, Data Preprocessing.

[0076] S311, Data Cleaning: Remove noise signals and outliers caused by electromagnetic interference and vibration; smooth the resistance measurement curve using the moving average method.

[0077] S312, Data Normalization: Unifies data from different channels and with different dimensions into a standard range to facilitate modeling and analysis.

[0078] S32, Feature Extraction.

[0079] S321, Data Feature Extraction: Extract time-domain features (such as peak amplitude and rise time), frequency-domain features (dominant frequency and bandwidth), and wavelet transform coefficients from ultrasonic signals to reflect the internal state of the material.

[0080] S322, Image Feature Extraction: Using a convolutional neural network (CNN) to extract visual features such as the appearance of the lightning arrester, the connection status of the wires, and rust marks from high-definition images.

[0081] S33, Feature Analysis and Modeling.

[0082] Multi-source signal fusion analysis: Kalman filtering or deep learning methods are used to fuse ultrasonic signals and image features to improve defect identification accuracy. An attention mechanism is employed to weightedly fuse ultrasonic and image features; these features are then input into a random forest classifier for defect identification; classification results include five categories: no defects, delamination, debonding, porosity, and fracture; the model training set contains 1200 historical test samples, and the 10-fold cross-validation accuracy is 93.7%.

[0083] Establish personalized detection models: Based on the structural differences of different regions of the blade (root, middle and tip) and the layout characteristics of the lightning protection system, construct exclusive detection models and optimize the sound beam incident angle, frequency selection and criterion threshold.

[0084] Environmental compensation technology: Real-time monitoring of temperature and humidity changes, and correction of ultrasonic propagation speed and attenuation characteristics based on a pre-calibrated environmental impact model to eliminate external interference.

[0085] S34, Analytical Results Verification. Cross-validation, confusion matrix, and ROC curves were used to evaluate model performance and ensure stable and reliable detection results.

[0086] S4 generates a comprehensive test report and pushes it to the operation and maintenance platform.

[0087] A pilot test was conducted on 10 wind turbines (30 blades in total) at a wind farm. The results showed that the average inspection time per blade was 22 minutes, which was 82% shorter than the traditional aerial inspection method. Three hidden internal debonding issues and one issue with excessive conductivity (measured R=136mΩ) were successfully identified and confirmed by disassembly. No equipment damage or safety accidents occurred, and the system operated stably and reliably.

[0088] This invention enables comprehensive, high-precision, and intelligent non-destructive testing of wind turbine blade lightning protection systems. By deeply integrating spherical UAVs, phased array ultrasonic technology, conductivity electrical testing, and artificial intelligence analysis, it solves the problems of traditional methods, such as difficulty in detecting internal defects, low efficiency, and poor safety.

[0089] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A non-destructive testing system for the lightning protection conductivity of wind turbine blades, characterized in that, The detection system includes a flight platform and a multi-functional detection device module, which is mounted on the flight platform. The multi-functional detection device module includes a phased array ultrasonic detection unit and a conductivity electrical testing unit to achieve high-precision detection of internal defects in wind turbine blades and non-destructive testing of their conductivity performance during a single flight.

2. The detection system according to claim 1, characterized in that, The phased array ultrasonic detection unit operates at an adjustable frequency of 2~10MHz to adapt to regions of different thicknesses; for thick cross-section regions, the operating frequency is 2~5MHz to enhance penetration; for thin-walled or fine structures, the operating frequency is 6~10MHz to improve resolution.

3. The detection system according to claim 1, characterized in that, The lightning protection conductivity electrical detection unit uses pulse current to measure the equivalent impedance of conductivity.

4. The detection system according to claim 3, characterized in that, The pulse current is a 0.5~2A pulse square wave with a duration of 5~30ms.

5. The detection system according to claim 1, characterized in that, The detection system also includes a data communication and control module, a ground control and data processing module, and an intelligent analysis and report generation module.

6. The detection system according to claim 1, characterized in that, The multifunctional detection device module also includes high-definition visual acquisition equipment, including a visible light camera, an infrared thermal imager, and image-aiding function equipment.

7. A non-destructive testing method for the lightning protection conductivity of wind turbine blades, characterized in that, The detection method employs the detection system described in any one of claims 1 to 6, and includes the following steps: S0, Preparation before testing; S1, Flight Inspection, including phased array ultrasonic testing, lightning protection conductivity electrical testing, and visual acquisition; S2, Data Acquisition; S3, Data Analysis; S4 generates a comprehensive test report.

8. The detection method according to claim 7, characterized in that, The phased array ultrasonic testing process includes: hovering the drone to bring the probe close to or against the blade surface; starting the scanning program and focusing on the following areas: the root of the lightning arrester, mainly focusing on delamination, debonding and cracks to ensure that the lightning current is smoothly conducted into the lower lead; the metal anchoring area, mainly focusing on pores, corrosion and loosening to verify the reliability of the electrical connection; the lower lead connection point, mainly focusing on breakage and poor contact to ensure the continuity of the entire conduction path.

9. The detection method according to claim 7, characterized in that, The lightning protection conductivity electrical testing process includes: the robotic arm of the UAV drives the electrode to contact the designated test point on the blade surface, introduces current, and measures the resistance value at the same time; the resistance measurement results are all bound to the location information to form a thermal map of the conductivity resistance distribution.

10. The detection method according to claim 7, characterized in that, The visual acquisition includes: using a visible light camera to photograph the appearance of the lightning arrester, the connection status of the wires, and traces of corrosion; using an infrared thermal imager to detect localized heating caused by excessive contact resistance; and using image-assisted devices to identify the blade number and the lightning arrester label.

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