Search Results (17)

In high-voltage transmission lines, insulators subjected to prolonged electromechanical stress are prone to zero-value defects, leading to insulation failure and posing significant risks to power grid reliability. The conventional detection method of spark gap is vulnerable to environmental interference, while the emerging electric field distribution-based techniques require complex instrumentation, limiting its applications in scenes of complex structures and atop tower climbing. To address these challenges, this study proposes an electroluminescent sensing strategy for zero-value insulator identification based on the electroluminescence of ZnS:Cu. Based on the stimulation of electrical stress, real-time monitoring of the health status of insulators was achieved by applying the composite of epoxy and ZnS:Cu onto the connection area between the insulator steel cap and the shed. Experimental results demonstrate that healthy insulators exhibit characteristic luminescence, whereas zero-value insulators show no luminescence due to a reduced drop in electrical potential. Compared with conventional detection methods requiring access of electric signals, such non-contact optical detection method offers high fault-recognition accuracy and real-time response capability within milliseconds. This work establishes a novel intelligent sensing paradigm for visualized condition monitoring of electrical equipment, demonstrating significant potential for fault diagnosis in advanced power systems. Full article

To address the frequent cleaning requirements of casting molds in bridge tower construction, a wall-climbing cleaning robot based on negative pressure adsorption is designed to safely and efficiently replace manual labor for cleaning tasks. The primary focus of this paper is the establishment of a theoretical model for negative pressure adsorption, along with an analysis of potential adhesion hazards. Initially, the robot’s chassis was designed, followed by the development of a theoretical model for the rotational-flow suction unit that incorporates two critical parameters: the number of blades and their thickness. This model was validated through computational fluid dynamics (CFD) and experimental methods. The findings indicate that, with fewer blades, an increase in blade quantity significantly improves the distribution of nonlinear velocity in the z-plane, resulting in a substantial enhancement of suction force up to a certain limit. As the number of blades increases, the thickness of the blades primarily influences the volume of air within the rotating domain, thereby affecting the suction force; thinner blades are preferable. Moreover, this study reveals that square suction units provide greater suction force compared to circular ones, attributable to their superior negative pressure effect and larger adsorption area. The most critical adhesion risk identified is leakage at the edges of the suction unit. Full article

In order to ensure the safety of maintenance personnel during tower climbing and improve the efficiency of power maintenance work, this study designed an assistive hip joint exoskeleton robot and analyzed the kinematic data obtained from tower climbers during the climbing process. A neural-network-based assistive control algorithm for tower climbing was created, and a tower climbing experiment was conducted with volunteers. The surface electromyographic (sEMG) signals of four muscles, namely the biceps femoris (BF), gluteus maximus (GM), semimembranosus (SM), and semitendinosus (ST), were collected to evaluate the performance of the robot. The experimental results show that the exoskeleton robot could reduce the root mean square (RMS) values of the sEMG signals of the main force-generating muscles related to the hip joint. This suggests that the robot can effectively assist personnel in tower climbing operations. Full article

This paper aims to introduce robot technology to carry out the safety inspection of transmission towers in long-distance power transmission, so as to improve the safety and efficiency of inspection. However, aiming at the problem that the existing climbing robots are mainly used for large load applications, which leads to the large size and lack of flexibility of the robot, we propose an innovative solution. Firstly, a lightweight quadruped climbing robot is designed to improve portability and operational flexibility. Then, a one-dimensional force sensor is added at the end of each leg of the robot, and a special swing phase trajectory is designed. The robot can judge whether the electromagnetic adsorption is effective and avoid potential safety hazards. Finally, based on the principle of virtual model control (VMC), a foot-end force balancing algorithm is proposed to achieve uniform distribution and continuous change in force, and improve safety and load capacity. The experiments show that the scheme has a stable climbing ability in the environments of angle steel, vertical ferromagnetic plane and transmission tower. Full article

High-rise building machines (HBMs) play a crucial role in the construction of super-tall buildings, with their working states directly impacting safety, quality, and progress. Given their extensive floor coverage and complex internal structures, monitoring priorities should shift according to specific workflows. However, existing research has primarily focused on monitoring key HBM components during specific stages, neglecting the automated recognition of HBM workflows, which hinders adaptive monitoring strategies. This study investigates the critical states of HBM construction across various structural layers and proposes a method rooted in vibration signal analysis to determine the HBM’s working state. The method involves collecting vibration signals with a triaxial accelerometer, extracting five distinct vibration signal features, classifying these signals using a k-Nearest Neighbors (kNN) classifier, and finally, outputting the results through a classification rule that aligns with the actual workflow of the HBM. The method was implemented in super-high-rise buildings exceeding 350 m, achieving a measured accuracy of 97.4% in HBM working state recognition. This demonstrates its proficiency in accurately determining the construction state and facilitating timely feedback. Utilizing vibration signal analysis can enhance the efficiency and safety, with potential applications in monitoring large-scale formwork equipment construction processes. This approach provides a versatile solution for a wide range of climbing equipment used in the construction of super-tall buildings and towering structures. Full article

The inspection and maintenance of transmission systems are necessary for their proper functioning. In this way, among the line’s critical points are the insulator chains, which are responsible for providing insulation between conductors and structures. The accumulation of pollutants on the insulator surface can cause failures in the power system, leading to power supply interruptions. Currently, the cleaning of insulator chains is performed manually by operators who climb towers and use cloths, high-pressure washers, or even helicopters. The use of robots and drones is also under study, presenting challenges to be overcome. This paper presents the development of a drone–robot for cleaning insulator chains. The drone–robot was designed to identify insulators by camera and perform cleaning through a robotic module. This module is attached to the drone and carries a battery-powered portable washer, a reservoir for demineralized water, a depth camera, and an electronic control system. This paper includes a literature review on the state of the art related to strategies used for cleaning insulator chains. Based on this review, the justification for the construction of the proposed system is presented. The methodology used in the development of the drone–robot is then described. The system was validated in a controlled environment and in field experimental tests, with the ensuing discussions and conclusions formulated, along with suggestions for future work. Full article

The development of control technology on wind turbine application robots has played an integral role in facilitating the digitization of inspection and maintenance in the wind energy industry. This paper presents a wind-turbine-climbing robot that determines the service lifespan of the wind turbine components subject to its payload capacity. The model has four rubber wheels, as the driving mechanism for its locomotion is being supported by a Bowden cable as a winding mechanism for its adhesion. The design further incorporates an Arduino microcontroller, distance sensors, motors, and a step motor to form its electromechanical structure. The overall capability of the robot has been analyzed through its kinematics and dynamics. Practical indoor experiments using a wind turbine tower mockup have been conducted for the validation of the various speeds and payload capacity of the prototype. The results indicate the effectiveness of its driving and winding mechanism to climb at the various speeds and with or without a payload. The advantage of the operations of its mechanism conformed with the wind turbine application robots. Full article

With the development of robot technology and the extensive application of robots, the research on special robots for some complex working environments has gradually become a hot topic. As a special robot applied to transmission towers, the climbing robot can replace humans to work at high altitudes to complete bolt tightening, detection, and other tasks, which improves the efficiency of transmission tower maintenance and ensures personal safety. However, it is mostly the ability to autonomously locate in the complex environment of the transmission tower that limits the industrial applications of the transmission tower climbing robot. This paper proposes an intelligent positioning method that integrates the three-dimensional information model of transmission tower and visual sensor data, which can assist the robot in climbing and adjusting to the designated working area to guarantee the working accuracy of the climbing robots. The experimental results show that the positioning accuracy of the method is within 1 cm. Full article

The emergence of renewable energy offers opportunities for academia and the industry to conduct scientific research and innovative technological developments on wind turbine climbing robots. These robots were developed to carry out specialized application tasks, such as in-situ inspection and maintenance of wind turbine physical structure. This paper presents a scaled-down prototype design of a climbing robot for wind turbine maintenance and its kinematic modeling. The winding mechanism is the key feature for providing enough adhesion force to support the climbing robot and needs to adapt to the different diameters of the wind turbine tower, as it climbs through a circular truncated cone shape. A climbing model is then considered, using four mecanum wheels for maneuverability of the different movement states up-down, rotation, and spiral as it climbs the wind turbine tower. The design of the wind turbine climbing robot was modeled in SketchUp and the motion states were implemented in MATLAB for the climbing performance capabilities of the driving wheels of the robot. Based on the theoretical results of motion characteristics, the scaled-down prototype design of a climbing robot possesses maneuverability of motion and is able to predict the robot’s performance. The contribution of this paper is intended to provide a basis for the new transformative climbing robot design and effectiveness of the mecanum wheel for robot motion. Full article

The evolution of the wind turbine to generate carbon-free renewable energy is rapidly growing. Thus, performing maintenance and inspection tasks in high altitude environments or difficult to access places, and even bad weather conditions, poses a problem for the periodic inspection process of the wind turbine industry. This paper describes the design and development of a scaled-down prototype climbing robot for wind turbine maintenance to perform critical tower operations. Thus, the unique feature of this maintenance robot is the winding mechanism, which uses a tension force to grip on the tower surface without falling to the ground either in static or dynamic situations, with the locomotion to perform a straight up–down motion in a circular truncated cone and the stability to work at significant heights. The robot computer-aided design (CAD) model of the mechanical mechanism, force and structural analysis, and the testing of the prototype model, are addressed in this paper. The key hardware developments that were utilized to build a low-cost, reliable and compact climbing robot are the embedded microprocessors, brushed DC motors, stepper motors and steel rope. This paper concludes with a successful preliminary experiment of a scaled down prototype proving the functionality of the concept. The potential applications for this robot are industrial maintenance, inspection and exploration, security and surveillance, cleaning, painting, and welding at extreme height conditions. Full article

For decades, the osteogenic effect from different physical activities on bone in rodents remained uncertain. This literature review presents for the first time the effects on five exercise models (treadmill running, wheel running, swimming, resistance training and vibration modes) in three different experimental rat groups (males, females, osteopenic) on bone quality. The bone parameters presented are bone mineral density, micro-architectural and mechanical properties, and osteoblast/osteocyte and osteoclast parameters. This review shows that physical activities have a positive effect (65% of the results) on bone status, but we clearly observed a difference amongst the different protocols. Even if treadmill running is the most used protocol, the resistance training constitutes the first exercise model in term of osteogenic effects (87% of the whole results obtained on this model). The less osteogenic model is the vibration mode procedure (31%). It clearly appears that the gender plays a role on the bone response to swimming and wheel running exercises. Besides, we did not observe negative results in the osteopenic population with impact training, wheel running and vibration activities. Moreover, about osteoblast/osteocyte parameters, we conclude that high impact and resistance exercise (such jumps and tower climbing) seems to increase bone formation more than running or aerobic exercise. Among the different protocols, literature has shown that the treadmill running procedure mainly induces osteogenic effects on the viability of the osteocyte lineage in both males and females or ovariectomized rats; running in voluntary wheels contributes to a negative effect on bone metabolism in older male models; whole-body vertical vibration is not an osteogenic exercise in female and ovariectomized rats; whereas swimming provides controversial results in female models. For osteoclast parameters only, running in a voluntary wheel for old males, the treadmill running program at high intensity in ovariectomized rats, and the swimming program in a specific ovariectomy condition have detrimental consequences. Full article

The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future. Full article

Though there are exhaustive data about participation, performance trends, and sex differences in performance in different running disciplines and races, no study has analyzed these trends in stair climbing and tower running. The aim of the present study was therefore to investigate these trends in tower running. The data, consisting of 28,203 observations from 24,007 climbers between 2014 and 2019, were analyzed. The effects of sex and age, together with the tower characteristics (i.e., stairs and floors), were examined through a multivariable statistical model with random effects on intercept, at climber’s level, accounting for repeated measurements. Men were faster than women in each age group (p < 0.001 for ages ≤69 years, p = 0.003 for ages > 69 years), and the difference in performance stayed around 0.20 km/h, with a minimum of 0.17 at the oldest age. However, women were able to outperform men in specific situations: (i) in smaller buildings (<600 stairs), for ages between 30 and 59 years and >69 years; (ii) in higher buildings (>2200 stairs), for age groups <20 years and 60–69 years; and (iii) in buildings with 1600–2200 stairs, for ages >69 years. In summary, men were faster than women in this specific running discipline; however, women were able to outperform men in very specific situations (i.e., specific age groups and specific numbers of stairs). Full article

An automatic, fast, and accurate switching method between Global Positioning System and indoor positioning systems is crucial to achieve current user positioning, which is essential information for a variety of services installed on smart devices, e.g., location-based services (LBS), healthcare monitoring components, and seamless indoor/outdoor navigation and localization (SNAL). In this study, we proposed an approach to accurately detect the indoor/outdoor environment according to six different daily activities of users including walk, skip, jog, stay, climbing stairs up and down. We select a number of features for each activity and then apply ensemble learning methods such as Random Forest, and AdaBoost to classify the environment types. Extensive model evaluations and feature analysis indicate that the system can achieve a high detection rate with good adaptation for environment recognition. Empirical evaluation of the proposed method has been verified on the HASC-2016 public dataset, and results show 99% accuracy to detect environment types. The proposed method relies only on the daily life activities data and does not need any external facilities such as the signal cell tower or Wi-Fi access points. This implies the applicability of the proposed method for the upper layer applications. Full article

In recent decades, skyscrapers, as represented by the Burj Khalifa in Dubai and Shanghai Tower in Shanghai, have been built due to the improvements of construction technologies. Even in such newfangled skyscrapers, the façades are generally cleaned by humans. Wall climbing robots, which are capable of climbing up vertical surfaces, ceilings and roofs, are expected to replace the manual workforce in façade cleaning works, which is both hazardous and laborious work. Such tasks require these robotic platforms to possess high levels of adaptability and flexibility. This paper presents a detailed review of wall climbing robots categorizing them into six distinct classes based on the adhesive mechanism that they use. This paper concludes by expanding beyond adhesive mechanisms by discussing a set of desirable design attributes of an ideal glass façade cleaning robot towards facilitating targeted future research with clear technical goals and well-defined design trade-off boundaries. Full article