Robotics in Power Systems: Enabling a More Reliable and Safe Grid

Menéndez, Oswaldo; Cheein, Fernando Auat; Pérez, Marcelo A.; Kouro, Samir

doi:10.1109/mie.2017.2686458

Cited by 75 publications

(49 citation statements)

References 59 publications

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“…Moreover, the external forces Q i of the Lagrangian dynamics of equation (1) comprises the actuator force f r , the wind force f w , and the sinusoidal force f s that cause the flexible line to oscillate along y-axis when the robot moves along the line. us, the complete dynamics of the robot under the influence of wind can be calculated by solving equation (1) using equations (17) and (18) as expressed in equation (19) to equation (21).…”

Section: Wind F W Robotmentioning

confidence: 99%

See 1 more Smart Citation

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Alhassan

Zhang

Shen

et al. 2019

Mathematical Problems in Engineering

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To efficiently transmit electric power to consumers, the power lines need to be inspected routinely for early fault detection. Thus, power line inspection robots are designed to replace the tedious and dangerous manual inspection using linemen or helicopters. However, most of the existing inspection robots are heavy, which make them slow and prone to external wind disturbance. This paper developed a lightweight dual-arm robot and investigates its robustness to wind disturbance on a lab-scale power line structure. The dynamic equations of the robot are derived using the Lagrangian equation for appropriate motor selection. Also, the components of the robot are designed to ensure low drag coefficient to wind flow, and the mechanism of the wind force on the robot-line coupled system is presented. To study the real-time impact of the wind, a wind speed of 4.5 m/s representing one of the windiest cities in China is considered as a case study. The experimental results for different wind directions, namely, 0°, 45°, and 90°, show that the maximum vibration is 8% higher than the normal vibration of the system in a controlled environment without wind. The results demonstrate that there is little influence of the wind on the system; hence, the robot has been successfully designed and can be applied for power line inspection.

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Section: Wind F W Robotmentioning

confidence: 99%

“…For a reliable transmission of electric power, the power transmission lines (PTLs) need regular inspections for early fault detection and maintenance. Recognition and localization of faults along the PTL equipment are essential as it helps the power transmission companies minimize maintenance cost and prevents unwanted power outages [1,2].…”

Section: Introductionmentioning

confidence: 99%

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Alhassan

Zhang

Shen

et al. 2019

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

“…Robotic platforms can be combined with embedded algorithms, using Internet of Things (IoT) it and artificial intelligence algorithms, like computer vision techniques or convolutional neural networks. That are a various mode of operation like visual inspection [5,6], infrared thermography [7,8,9] for hot spots detection and operation of the PV plants and Electroluminescence (EL), method capable of detected beyond soiling and achieve damage detection, but requires detailed analysis of each solar panel cell. In the work [10] provides a probabilistic methodology for identifying various types of damage for solar cells.…”

Section: Introductionmentioning

confidence: 99%

Application of A Computer Vision Method for Soiling Recognition in Photovoltaic Modules for Autonomous Cleaning Robots

Pivem¹,

Araujo²,

Araujo³

et al. 2019

SIPIJ

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It is well known that this soiling can reduce the generation efficiency in PV system. In some case according to the literature of loss of energy production in photovoltaic systems can reach up to 50%. In the industry there are various types of cleaning robots, they can substitute the human action, reducing cleaning cost, be used in places where access is difficult, and increasing significantly the gain of the systems. In this paper we present an application of computer vision method for soiling recognition in photovoltaic modules for autonomous cleaning robots. Our method extends classic CV algorithm such Region Growing and the Hough. Additionally, we adopt a pre-processing technique based on Top Hat and Edge detection filters. We have performed a set of experiments to test and validate this method. The article concludes that the developed method can bring more intelligence to photovoltaic cleaning robots.

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“…The future of the photovoltaic plant inspection is focused on the maintenance robotics with emphasis on robots able to detect and correct damaged electric equipment [2]. Nowadays, both autonomous robotics and tele-operated machines, despite being useful, have found only limited application because of payload capacity of platforms (mainly aerial platforms), limited access and rugged environments [3].…”

Section: Introductionmentioning

confidence: 99%

“…Robotic platforms can be combined with Internet of Things (IoT) and artificial intelligence algorithms, perform a variety of PV-related tasks such as visual inspection [2,4] (modules, wiring and/or other plant equipment), infrared thermography [5] (hot-spots detection) and vegetation…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic Modules Diagnosis Using Artificial Vision Techniques for Artifact Minimization

et al. 2018

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Abstract:The installed capacity of solar photovoltaics has increased over the past two decades worldwide, evolving from a few small scale applications to a daily power source. Such growth involves a great impact over operating processes and maintenance practices. The RGB (red, green and blue) and infra-red monitoring of photovoltaic modules is a non-invasive inspection method which provides information of possible failures, by relating thermal behaviour of the modules to the operational status of solar panels. An adequate thermal measurement module strongly depends on the proper camera angle selection relative to panel's surface, since reflections and external radiation sources are common causes of misleading results with the unnecessary maintenance work. In this work, we test a portable ground-based system capable of detecting and classifying hot-spots related to photovoltaic module failures. The system characterizes in 3D thermal information from the panels structure to detect and classify hot-spots. Unlike traditional systems, our proposal detects false hot-spots associated with people or device reflections, and from external radiation sources. Experimental results show that the proposed diagnostic approach can provide of an adequate thermal monitoring of photovoltaic modules and improve existing methods in 12% of effectiveness, with the corresponding financial impact.

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Robotics in Power Systems: Enabling a More Reliable and Safe Grid

Cited by 75 publications

References 59 publications

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Investigation of Aerodynamic Stability of a Lightweight Dual‐Arm Power Transmission Line Inspection Robot under the Influence of Wind

Application of A Computer Vision Method for Soiling Recognition in Photovoltaic Modules for Autonomous Cleaning Robots

Photovoltaic Modules Diagnosis Using Artificial Vision Techniques for Artifact Minimization

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