Impacts of flexible obstructive working environment on dynamic performances of inspection robot for power transmission line

The rigid-flexible coupling dynamic modeling and simulation of an inspection robot were conducted to study the influences of the flexible obstructive working environment i.e. overhead transmission line on the robot＇s dynamic performance. First, considering the structure of the obstacles and symmetrical mechanism of the robot prototype, four basic subactions were abstracted to fulfill full-path kinematic tasks. Then, a multi-rigid-body dynamic model of the robot was built with Lagrange equation, whil^e a multi-flexible-body dynamic model of a span of lin~ was obtained by combining finite element method （FEM）, modal synthesis method and Lagrange equation. The two subsystem models were coupled under rolling along no-obstacle segment and overcoming obstacle poses, and these simulations of three subactions along different spans of line were performed in ADMAS. The simulation results, including the coupling vibration parameters and driving moment of joint motors, show the dynamic performances of the robot along ftexibile obstructive working path： in flexible obstructive working environment, the robot can fulfill the preset motion goals; it responses slower in more flexible path; the fluctuation of robot as well as driving moment of the corresponding joint in startup and brake region is greater than that in rigid environment; the fluctuation amplitude increases with increasing working environment flexibility.

Hand-eye-vision based control for an inspection robot's autonomous line grasping

In order to ensure that the off-line arm of a two-arm-wheel combined inspection robot can reliably grasp the line in case of autonomous obstacle crossing,a control method is proposed for line grasping based on hand-eye visual servo.On the basis of the transmission line's geometrical characteristics and the camera's imaging principle,a line recognition and extraction method based on structure constraint is designed.The line's intercept and inclination are defined in an imaging space to represent the robot's change of pose and a law governing the pose decoupling servo control is developed.Under the integrated consideration of the influence of light intensity and background change,noise(from the camera itself and electromagnetic field)as well as the robot's kinetic inertia on the robot's imaging quality in the course of motion and the grasping control precision,a servo controller for grasping the line of the robot's off-line arm is designed with the method of fuzzy control.An experiment is conducted on a 1:1 simulation line using an inspection robot and the robot is put into on-line operation on a real overhead transmission line,where the robot can grasp the line within 18 s in the case of autonomous obstacle-crossing.The robot's autonomous line-grasping function is realized without manual intervention and the robot can grasp the line in a precise,reliable and efficient manner,thus the need of actual operation can be satisfied.

Dynamic Balance Control Based on an Adaptive Gain-scheduled Backstepping Scheme for Power-line Inspection Robots

This paper presents an adaptive gain-scheduled backstepping control(AGSBC) scheme for the balance control of an underactuated mechanical power-line inspection(PLI) robotic system with two degrees of freedom and a single control input.First, a nonlinear dynamic model of the balance adjustment process of the PLI robot is constructed, and then the model is linearized at a nominal equilibrium point to overcome the computational infeasibility of the conventional backstepping technique. Second, to solve generalized stabilization control issue for underactuated systems with multiple equilibrium points,an equilibrium manifold linearized model is developed using a scheduling variable, and then a gain-scheduled backstepping control(GSBC) scheme for expanding the operational area of the controlled system is constructed. Finally, an adaptive mechanism is proposed to counteract the impact of external disturbances. The robust stability of the closed-loop system is ensured by Lyapunov theorem. Simulation results demonstrate the effectiveness and high performance of the proposed scheme compared with other control schemes.

Variable universe fuzzy control of walking stability for flying‐walking power line inspection robot based on multi‐work conditions

To address complex work conditions incredibly challenging to the stability of power line inspection robots,we design a walking mechanism and propose a variable universe fuzzy control(VUFC)method based on multi‐work conditions for flying‐walking power line inspection robots(FPLIRs).The contributions of this paper are as follows:(1)A flexible pressing component is designed to improve the adaptability of the FPLIR to the ground line slope.(2)The influence of multi‐work conditions on the FPLIR's walking stability is quantified using three condition parameters(i.e.,slope,slipping degree and swing angle),and their measurement methods are proposed.(3)The VUFC method based on the condition parameters is proposed to improve the walking stability of the FPLIR.Finally,the effect of the VUFC method on walking stability of the FPLIR is teste.The experimental results show that the maximum climbing angle of the FPLIR reaches 29.1°.Compared with the constant pressing force of 30 N,the average value of slipping degree is 0.93°,increasing by 35%.The maximum and average values of robot's swing angle are reduced by 46%and 54%,respectively.By comparing with fuzzy control,the VUFC can provide a more reasonable pressing force while maintaining the walking stability of the FPLIR.The proposed walking mechanism and the VUFC method significantly improve the stability of the FPLIR,providing a reference for structural designs and stability controls of inspection robots.

High Precision Ultrasonic Guided Wave Technique for Inspection of Power Transmission Line

Due to the merits of high inspection speed and long detecting distance, Ultrasonic Guided Wave（UGW） method has been commonly applied to the on-line maintenance of power transmission line. However, the guided wave propagation in this structure is very complicated, leading to the unfavorable defect localization accuracy. Aiming at this situation, a high precision UGW technique for inspection of local surface defect in power transmission line is proposed. The technique is realized by adopting a novel segmental piezoelectric ring transducer and transducer mounting scheme, combining with the comprehensive characterization of wave propagation and circumferential defect positioning with multiple piezoelectric elements. Firstly, the propagation path of guided waves in the multi-wires of transmission line under the proposed technique condition is investigated experimentally. Next, the wave velocities are calculated by dispersion curves and experiment test respectively, and from comparing of the two results, the guided wave mode propagated in transmission line is confirmed to be F（1,1） mode. Finally, the axial and circumferential positioning of local defective wires in transmission line are both achieved, by using multiple piezoelectric elements to surround the stands and send elastic waves into every single wire. The proposed research can play a role of guiding the development of highly effective UGW method and detecting system for multi-wire transmission line.

Automated deep learning system for power line inspection image analysis and processing: architecture and design issues

The continuous growth in the scale of unmanned aerial vehicle (UAV) applications in transmission line inspection has resulted in a corresponding increase in the demand for UAV inspection image processing. Owing to its excellent performance in computer vision, deep learning has been applied to UAV inspection image processing tasks such as power line identification and insulator defect detection. Despite their excellent performance, electric power UAV inspection image processing models based on deep learning face several problems such as a small application scope, the need for constant retraining and optimization, and high R&D monetary and time costs due to the black-box and scene data-driven characteristics of deep learning. In this study, an automated deep learning system for electric power UAV inspection image analysis and processing is proposed as a solution to the aforementioned problems. This system design is based on the three critical design principles of generalizability, extensibility, and automation. Pre-trained models, fine-tuning (downstream task adaptation), and automated machine learning, which are closely related to these design principles, are reviewed. In addition, an automated deep learning system architecture for electric power UAV inspection image analysis and processing is presented. A prototype system was constructed and experiments were conducted on the two electric power UAV inspection image analysis and processing tasks of insulator self-detonation and bird nest recognition. The models constructed using the prototype system achieved 91.36% and 86.13% mAP for insulator self-detonation and bird nest recognition, respectively. This demonstrates that the system design concept is reasonable and the system architecture feasible .

Safety Distance Determination for 500 kV AC Transmission Line’s Helicopter Inspection

As an efficient and advanced line inspection method, helicopter line patrol is gradually more and more used in transmission lines inspection, promoting the elaborate operation of transmission lines and reducing the management cost. However, as a 'floating-potential conductor' near to a high-voltage transmission line, the helicopter would be at a high electric field region;and bring security risk to equipment and operating personnel. In this paper, the electric field strength near the cabin at locations of different distance from transmission lines is investigated by calculation, and the field in the helicopter cabin is also calculated with finite element method (FEM). The result indicates that the potential difference becomes higher with the decrease of the distance between the helicopter and transmission line. Considering the discharge energy and the guarantee of the persons’ safety, the safety distance is determined as d≥15 m.

Prototype Monitoring System for Power Line Inspection by Means of a PandaBoard

The national energy supplier （Eskom in South Africa） supplies electricity through thousands-of-kilometers of overhead power lines. The current methods of inspection of these overhead power lines are infrequent and expensive. In this paper, the authors present the development of a prototype monitoring system for power line inspection in South Africa. The developed prototype monitoring system collects data （information） from the overhead power lines, is remotely accessible and fits into a power line robot. The prototype monitoring system makes use ofa PandaBoard （SBC） with GPS receiver and 5 MP camera to collect data. Hardware fatigue is the biggest problem faced on the overhead power lines and is captured by means of the 5 MP camera and is displayed on a website hosted by the PandaBoard via Wi-Fi. The monitoring system has low power consumption, is light weight, compact and easily collects data. The data obtained from the prototype monitoring system was satisfactory and provides an improved solution for monitoring power lines for Eskom in South Africa.

Prototype Line Crawler for Power Line Inspection

In South Africa, electricity is supplied through thousands-of-kilometers of overhead power cables, which is owned by Eskom the national energy supplier. Currently monitoring of these overhead power cables are done by means of helicopter inspection flights and foot patrols, which are infrequent and expensive. In this paper, the authors present the design of a prototype power line crawler （inspection robot） for the monitoring of these overhead power lines in South Africa. The designed prototype power line crawler is capable of driving on the wire, balancing on the wire and is capable of maneuvering past certain obstacles found on the overhead power cables. The prototype power line crawler is designed to host a monitoring system that monitors the power line as the inspection robot drives on it. Various experimental tests were performed and are presented in this paper, showing the capability of performing these tasks. This prototype inspection robot ensures a platform for future development in this area.

基于图像感知的输电线路智能巡检综述

输电线路是电网建设的重要组成部分,定期巡检对于确保输电线路的稳定运行至关重要。文中围绕输电线路智能巡检需求,首先梳理了输电线路不同的巡检方法,介绍了智能巡检中所需的系统框架设备以及智能算法;重点总结了基于传统图像处理和深度学习的智能巡检方法;其次针对输电线路中存在的各种不同故障总结了相关的智能巡检方法,并且通过评价指标进行了对比分析;最后梳理了研究难点,对基于深度学习方法的输电线路巡检发展趋势进行了展望,所提出和总结的输电线路智能巡检方法具有多方面的指导意义。

基于多重注意力和特征对齐的销钉缺陷检测方法

电网规模的快速扩张对输电线路的检测维护提出更高的要求,智能高效的自动化电力巡检图像识别算法作为提高检测维护的手段,已经成为目前研究的重要方向之一。为实现巡检图像中销钉缺陷目标的准确识别,文章提出一种基于多重注意力和特征对齐的销钉缺陷检测方法。首先,构建基于可变形注意力的可变形检测变压器(deformable detection transformer,Deformable-DETR)框架,解决现有识别算法中无法通过卷积神经网络进行像素点轮廓-环境关系建模的问题;之后,提出区域注意力特征提取模块,解决由可变形注意力带来的特征粒度不足的问题;为丰富目标物体特征质量,提出基于注意力的候选框特征对齐模块和约束函数;最后,选取华中地区某电力公司的航拍图像数据验证算法性能。结果表明,所提算法总体性能相比于现有的卷积算法提升5.4%,总体平均检测精度达到90.5%。

井下带式输送机智能巡检机器人结构的设计

为解决带式输送机采用传统人工检测故障效率低等问题,针对问题设计出一种适用于井下输送机故障自动巡检机器人系统,区别于其他带式输送机巡检机器人。该巡检机器人可以实现大坡度和大转弯半径的运动,首先利用ADAMS分析现在主流的巡检机器人模型,分析其优劣性;利用SOLIDWORKS软件建立巡检机器人的三维模型,提出了摩擦驱动与齿轮齿条驱动的两用机器人模型;再利用ANSYS软件对轨道和机架进行了有限元分析,仿真结果表明巡检轨道与机器人本体的应力小于许用应力,能够平稳地检测输送机的故障;最后再利用ADAMS软件对巡检机器人进行动力学分析,得出巡检机器人可以进行无障碍的水平和爬坡运动。

桁架式机器人视觉巡检系统设计

针对当前智能制造装备存在传感器监测盲区且人工点检效率低、易出错的现状,设计一套桁架式移动机器人视觉巡检系统,实现自动监测生产线设备上电气、机械关键部位易松动易错位等问题。该系统安装在生产线上方,具有可达范围广、无拍照死角、适用场景广和不影响生产线设备动作等优点,解决传统地面移动巡检机器人占用生产线空间、拍照角度受限、无法进入复杂生产线内部点检等缺点。在智能制造技术升级的背景下,该系统具有较高的实用价值及推广意义。

基于改进YOLOv8与语义知识融合的金具缺陷检测方法研究

针对输电线路螺栓金具缺陷检测任务中存在的缺陷样本类间分布不均、缺陷微小特征提取困难等问题,提出基于改进YOLOv8和语义知识融合的输电线路螺栓缺陷检测方法。首先,通过深入分析数据样本中螺栓金具缺陷种类与该螺栓承载金具种类之间的关系,完成语义关联构建工作;之后,在YOLOv8模型Neck部分引入BiFusion和RepBlock模块,增强模型的特征提取能力;其次,使用改进的融合语义知识校正权重的Loss函数,进一步提高训练模型的准确性,减少误检的发生;最后,分别完成基线选取实验、消融实验、超参数调整实验以及对比实验。实验结果表明,相较于Baseline模型,改进YOLOv8方法在平均精确率(mAP)上提升了4.0%,在关键少样本类精确率上提升了24.6%,可有效提高输电线路螺栓金具缺陷检测的效果,该语义关联构建及语义知识融合方法具有一定的泛用性,为输电线路无人机智能巡检领域提供了新的方法支持。

基于随机几何的输电场景中无人机信道建模

为了准确描述输电环境中巡检无人机与地面基站之间无线信道,采用随机几何建模法,提出一种基于随机几何的三维信道模型。在该模型中考虑输电线路环境中塔杆,输电线的影响,采用水平圆柱体描述输电设备和周围环境的散射体分布情况,为了防止输电线路产生的电磁场影响无人机巡检作业安全,在模型中设置安全飞行区域,保证巡检安全。针对提出的信道模型,推导并分析了了空-时相关函数,多普勒功率谱密度,电平交叉率和平均衰落时间等信道统计特性。研究了散射体分布情况,无人机运动状态对信道统计特性的影响。仿真结果表明,无人机运动速度大小、飞行方向,散射体分布情况对信道影响显著。理论结果和仿真结果吻合良好,验证了所提模型的正确性和有效性,可以为输电线路场景下巡检无人机与地面基站之间的无线通信系统设计提供理论参考。

融合外部注意力的扩散模型巡检图像去雾

为降低雾天对输电线路巡检图像造成的影响,针对目前主流去雾算法存在计算成本高、图像去雾后检测性能差和难以部署的问题,提出了一种雾天输电线路巡检图像去雾方法Diff-EaT。该方法采用融合Transformer的扩散模型结构,为降低体征提取模块中多头自注意力在ViT中的计算复杂度,使用多头外部注意力代替多头自注意力以减少计算负荷和增强特征学习。同时,设计了一个混合尺度门控前馈网络,在输入特征的深度可分离卷积之后集成了选通机制以改善局部信息捕获。在合成数据集和真实数据集上进行对比试验,定量指标和定量指标都证明其有效性,复原图像细节更加清晰。在去雾检测系统中,对真实巡检图像去雾后使用YOLOv7进行检测,mAP@0.5、召回率、查准率分别提升6.92%、9.58%、4.11%,本文方法去雾后有效提高检测置信度,去雾检测系统可应用于实际场景。同时在消融实验中,证明了改进的有效性。

高压输电线软体巡检机器人磁致动机制及PI滑模控制研究

为解决高压输电线刚性悬臂巡检机器人尺寸大、笨重、越障不灵活、效率低等问题,设计一种高压磁致动软体巡检机器人,利用载流线圈在高压直流环形磁场中受到的安培力驱动软体机器人以柔顺和蠕动方式高效灵活地跨越多种障碍物。对该机器人进行本体构型设计并分析其工作姿态,实现稳定巡检功能;对磁致动驱动器进行理论设计和分析,利用Comsol仿真软件对其所需驱动力进行仿真,验证理论的可实行性;通过拉格朗日法对高压磁致动软体巡检机器人进行动力学建模,构建系统动力学方程,获取机器人的关节角度、速度、加速度之间的关系;最后,通过MATLAB利用基于PI滑模控制法对简化后的高压磁致动软体巡检机器人动力学模型实行速度和角速度高精度追踪仿真。仿真结果表明:在滑模控制下,角度在1.5 s追踪上理想信号,角速度在0.3 s后追上理想信号,证明基于PI的滑模控制器能够实现对高压磁致动软体巡检机器人的有效控制。

基于多维感知与空天一体的输电线路智慧运维体系建设与实践

基于多维感知与空天一体技术,提出了一种输电线路的智慧运维体系。该体系通过卫星遥感、无人机巡检、智能安防以及多传感器集群等技术的协同应用,实现了输电线路的全方位实时监测与隐患排查。卫星遥感技术用于输电通道环境的宏观监控,精准评估自然灾害和外力破坏风险;无人机巡检技术则提供了高效的多场景应用,包括红外测温、风筝线隐患排查等,极大提升了巡检效率;智能安防系统通过多传感器联控感知,实现了对输电线路环境与设备的三维空间监控与智能预警。实践结果表明,该智慧运维体系大幅提升了输电线路的安全性、可靠性及巡检效率,推动了输电运维技术的革新。

基于深度学习和无人机图像的架空线路缺陷巡检综述

架空输电线路巡检是电网运维工作的一项重要内容,利用无人机进行线路巡视检测已成为运维人员完成电力巡检工作的重要手段。首先,文中概述无人机巡检任务中人机协同作业系统以及无人机智能自主作业系统的架构;其次,分析当前架空输电线路缺陷巡检领域数据集状况以及数据扩增技术;再次,综述基于深度学习的无人机图像缺陷检测典型方法以及评价指标,并对比总结各种方法的优缺点;然后,讨论无人机图像视觉检测方法中图像采集规范、数据集形式、缺陷检测算法专业化应用等对架空线路缺陷的检测效果,指出图像检测指标和类别定义在电力巡检专业化领域中的不足;最后,探讨基于深度学习的无人机图像缺陷巡检的未来发展方向。

激光雷达探测输电走廊安全风险研究现状

输电走廊环境监测和风险预警是电网防灾抗灾的重要研究内容。在激光雷达、物联网、无人机及计算机技术的发展与推动下,利用各种新型遥感监测与巡检手段进行输电走廊大范围、智能化巡检成为重要发展趋势。综合多种监测数据的线路安全风险评估与灾害预警,成为智能电网建设工作的研究热点之一。本文系统论述了应用激光雷达技术进行输电走廊安全风险探测的研究现状与发展趋势,分析了激光雷达在输电线路安全风险探测中的优缺点,讨论了激光雷达输电线路巡检和监测数据在输电线路安全风险评估预警中所面对的问题与挑战。