Icing Effects on Power Lines and Anti-icing and De-icing Methods

Icing on power lines may lead to compromise safety and reliability of electric supply network. Prolong icing can lead to power breakdown and collapse of towers. Since power transmission lines are mostly overhead and could face the direct impact of icing, and it is one of the main challenges faced by power distribution companies in cold regions. When the ice accretion crosses the safety limit then deicing action can be carried out. We can find number of deicing methods that are used in different parts of the world. However, all of these deicing techniques have their own advantages and disadvantages on implementation. It is one of the most difficult as well as dangerous process to perform deicing on power lines. If a fault is detected and that has been occurred due to icing or during routine maintenance, extra care must be taken in order to ensure safety of the personals when performing de-icing of lines. However, as technology evolved, new ways and techniques are adopted with the help of sensors that give quick feedback to control room in the national grid via wireless communication network for real time action. In the thesis we have discussed atmospheric icing impacts on power lines in the cold regions across the world. A literature review has been done for anti-icing and deicing methods that are currently adopted in the power distribution network. Methods that are used against ice buildups have also been analyzed. This work also shows the impacts of icing and deicing techniques presently adopted, and also throws light on their pros and cons during maintenance operations. It provides an overview of the evolving technology trends that are practiced to ensure the availability of existing power transmission system in cold climate regions

Remote Sensing methods for power line corridor surveys

AbstractTo secure uninterrupted distribution of electricity, effective monitoring and maintenance of power lines are needed. This literature review article aims to give a wide overview of the possibilities provided by modern remote sensing sensors in power line corridor surveys and to discuss the potential and limitations of different approaches. Monitoring of both power line components and vegetation around them is included. Remotely sensed data sources discussed in the review include synthetic aperture radar (SAR) images, optical satellite and aerial images, thermal images, airborne laser scanner (ALS) data, land-based mobile mapping data, and unmanned aerial vehicle (UAV) data. The review shows that most previous studies have concentrated on the mapping and analysis of network components. In particular, automated extraction of power line conductors has achieved much attention, and promising results have been reported. For example, accuracy levels above 90% have been presented for the extraction of conductors from ALS data or aerial images. However, in many studies datasets have been small and numerical quality analyses have been omitted. Mapping of vegetation near power lines has been a less common research topic than mapping of the components, but several studies have also been carried out in this field, especially using optical aerial and satellite images. Based on the review we conclude that in future research more attention should be given to an integrated use of various data sources to benefit from the various techniques in an optimal way. Knowledge in related fields, such as vegetation monitoring from ALS, SAR and optical image data should be better exploited to develop useful monitoring approaches. Special attention should be given to rapidly developing remote sensing techniques such as UAVs and laser scanning from airborne and land-based platforms. To demonstrate and verify the capabilities of automated monitoring approaches, large tests in various environments and practical monitoring conditions are needed. These should include careful quality analyses and comparisons between different data sources, methods and individual algorithms

Dynamic Modeling, Design and Control of Wire-Borne Underactuated Brachiating Robots: Theory and Application

The ability of mobile robots to locomote safely in unstructured environments will be a cornerstone of robotics of the future. Introducing robots into fully unstructured environments is known to be a notoriously difficult problem in the robotics field. As a result, many of today's mobile robots are confined to prepared level surfaces in laboratory settings or relatively controlled environments only. One avenue for deploying mobile robots into unstructured settings is to utilize elevated wire networks. The research conducted under this thesis lays the groundwork for developing a new class of wire-borne underactuated robots that employs brachiation -- swinging like an ape -- as a means of locomotion on flexible cables. Executing safe brachiation maneuvers with a cable-suspended underactuated robot is a challenging problem due to the complications induced by the cable dynamics and vibrations. This thesis studies, from concept through experiments, the dynamic modeling techniques and control algorithms for wire-borne underactuated brachiating robots, to develop advanced locomotion strategies that enable the robots to perform energy-efficient and robust brachiation motions on flexible cables. High-fidelity and approximate dynamic models are derived for the robot-cable system, which provide the ability to model the interactions between the cable and the robot and to include the flexible cable dynamics in the control design. An optimal trajectory generation framework is presented in which the flexible cable dynamics are explicitly accounted for when designing the optimal swing trajectories. By employing a variety of control-theoretic methods such as robust and adaptive estimation, control Lyapunov and barrier functions, semidefinite programming and sum-of-squares optimization, a set of closed-loop control algorithms are proposed. A novel hardware brachiating robot design and embodiment are presented, which incorporate unique mechanical design features and provide a reliable testbed for experimental validation of the wire-borne underactuated brachiating robots. Extensive simulation results and hardware experiments demonstrate that the proposed multi-body dynamic models, trajectory optimization frameworks, and feedback control algorithms prove highly useful in real world settings and achieve reliable brachiation performance in the presence of uncertainties, disturbances, actuator limits and safety constraints.Ph.D

Vision-Based Control of Unmanned Aerial Vehicles for Automated Structural Monitoring and Geo-Structural Analysis of Civil Infrastructure Systems

The emergence of wireless sensors capable of sensing, embedded computing, and wireless communication has provided an affordable means of monitoring large-scale civil infrastructure systems with ease. To date, the majority of the existing monitoring systems, including those based on wireless sensors, are stationary with measurement nodes installed without an intention for relocation later. Many monitoring applications involving structural and geotechnical systems require a high density of sensors to provide sufficient spatial resolution to their assessment of system performance. While wireless sensors have made high density monitoring systems possible, an alternative approach would be to empower the mobility of the sensors themselves to transform wireless sensor networks (WSNs) into mobile sensor networks (MSNs). In doing so, many benefits would be derived including reducing the total number of sensors needed while introducing the ability to learn from the data obtained to improve the location of sensors installed. One approach to achieving MSNs is to integrate the use of unmanned aerial vehicles (UAVs) into the monitoring application. UAV-based MSNs have the potential to transform current monitoring practices by improving the speed and quality of data collected while reducing overall system costs. The efforts of this study have been chiefly focused upon using autonomous UAVs to deploy, operate, and reconfigure MSNs in a fully autonomous manner for field monitoring of civil infrastructure systems. This study aims to overcome two main challenges pertaining to UAV-enabled wireless monitoring: the need for high-precision localization methods for outdoor UAV navigation and facilitating modes of direct interaction between UAVs and their built or natural environments. A vision-aided UAV positioning algorithm is first introduced to augment traditional inertial sensing techniques to enhance the ability of UAVs to accurately localize themselves in a civil infrastructure system for placement of wireless sensors. Multi-resolution fiducial markers indicating sensor placement locations are applied to the surface of a structure, serving as navigation guides and precision landing targets for a UAV carrying a wireless sensor. Visual-inertial fusion is implemented via a discrete-time Kalman filter to further increase the robustness of the relative position estimation algorithm resulting in localization accuracies of 10 cm or smaller. The precision landing of UAVs that allows the MSN topology change is validated on a simple beam with the UAV-based MSN collecting ambient response data for extraction of global mode shapes of the structure. The work also explores the integration of a magnetic gripper with a UAV to drop defined weights from an elevation to provide a high energy seismic source for MSNs engaged in seismic monitoring applications. Leveraging tailored visual detection and precise position control techniques for UAVs, the work illustrates the ability of UAVs to—in a repeated and autonomous fashion—deploy wireless geophones and to introduce an impulsive seismic source for in situ shear wave velocity profiling using the spectral analysis of surface waves (SASW) method. The dispersion curve of the shear wave profile of the geotechnical system is shown nearly equal between the autonomous UAV-based MSN architecture and that taken by a traditional wired and manually operated SASW data collection system. The developments and proof-of-concept systems advanced in this study will extend the body of knowledge of robot-deployed MSN with the hope of extending the capabilities of monitoring systems while eradicating the need for human interventions in their design and use.PHDCivil EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169980/1/zhh_1.pd

ROBOTIC TECHNOLOGIES FOR MINIMIZING CREW MAINTENANCE REQUIREMENTS IN SPACE HABITATS

Gemstone Team ASTROThe International Space Station (ISS) is crewed continuously by astronauts conducting scientifc research in microgravity. However, their work is not limited to scientifc research alone; in fact, logistics, maintenance, and repair tasks on the ISS require more than 80% of available crew time, severely limiting opportunities for performing scientifc experiments and technological development. NASA is planning a new project known as Gateway (also referred to as the Lunar Orbital Platform-Gateway). This station will orbit the Moon and be uncrewed for 11 months per year. Astronauts will only be present in the outpost for a limited period of time and will not always be available for continuous repairs and maintenance, as is required for Gateway to operate. Therefore, robotic system(s) are necessary to regularly accomplish these tasks both in the absence and presence of astronauts. Throughout this project, Team ASTRO (Assessment of Space Technologies for Robotic Operations) explored the feasibility of integrating dexterous robotic systems in space habitat architectures to perform routine and contingency operational and maintenance tasks. Ultimately, this allows for astronauts, when present, to focus on exploration and scientifc discoveries. The team conducted this research through three approaches: Gateway component analog taskboard development and end e˙ector assessment, Cargo Transfer Bag (CTB) manipulation and logistics, and AprilTag situational awareness simulation development. Based on analyses and experimental results gained from this research, the team found that robotic systems are feasible alternatives for space habitat operation. Team ASTRO also determined that AprilTags can be used for optimization of the Gateway design to facilitate uncrewed operations and robotic servicing to improve crew productivity when present

Self-repair during continuous motion with modular robots

Through the use of multiple modules with the ability to reconfigure to form different morphologies, modular robots provide a potential method to develop more adaptable and resilient robots. Robots operating in challenging and hard-to-reach environments such as infrastructure inspection, post-disaster search-and-rescue under rubble and planetary surface exploration, could benefit from the capabilities modularity offers, especially the inherent fault tolerance which reconfigurability can provide. With self-reconfigurable modular robots self-repair, removing failed modules from a larger structure to replace them with operating modules, allows the functionality of the multi-robot organism as a whole to be recovered when modules are damaged. Previous self-repair work has, for the duration of self-repair procedures, paused group tasks in which the multi-robot organism was engaged, this thesis investigates Self-repair during continuous motion, ``Dynamic Self-repair", as a way to allow repair and group tasks to proceed concurrently. In this thesis a new modular robotic platform, Omni-Pi-tent, with capabilities for Dynamic Self-repair is developed. This platform provides a unique combination of genderless docking, omnidirectional locomotion, 3D reconfiguration possibilities and onboard sensing and autonomy. The platform is used in a series of simulated experiments to compare the performance of newly developed dynamic strategies for self-repair and self-assembly to adaptations of previous work, and in hardware demonstrations to explore their practical feasibility. Novel data structures for defining modular robotic structures, and the algorithms to process them for self-repair, are explained. It is concluded that self-repair during continuous motion can allow modular robots to complete tasks faster, and more effectively, than self-repair strategies which require collective tasks to be halted. The hardware and strategies developed in this thesis should provide valuable lessons for bringing modular robots closer to real-world applications