A survey of intelligent transmission line inspection based on unmanned aerial vehicle

Luo, Yanhong; Xue, Yunfei; Yang, Dongsheng; Zhou, Bowen

doi:10.1007/s10462-022-10189-2

Cited by 68 publications

(28 citation statements)

References 120 publications

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“…[1,2] As pivotal components in smart grid systems, the transmission lines play a crucial role in long-distance energy delivery. [3] The traditional digital monitoring devices of the transmission lines mostly rely on chemical batteries for power supply. However, the drawbacks of frequent replacements, high operational costs, and environmental pollution associated with chemical batteries have become increasingly apparent.…”

Section: Introductionmentioning

confidence: 99%

Multi‐Mode Vibrational Triboelectric Nanogenerator for Broadband Energy Harvesting and Utilization in Smart Transmission Lines

Zhang,

Yu,

Xia

et al. 2023

Advanced Energy Materials

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The advantages of the triboelectric nanogenerator (TENG) in environmental energy harvesting and utilization determine that they have great development potential in the digital application of power grids. This work focuses on the harvesting and utilization of vibration energy from transmission lines, specifically in the context of breeze vibrations and sub‐span oscillations. To this end, this work proposes a novel multi‐mode vibrational triboelectric nanogenerator (MV‐TENG) and three smart transmission line application strategies based on the MV‐TENG. The MV‐TENG design consists of an S‐beam to broaden the frequency response range by reducing high‐order modal frequencies, and a pair of allegro electrodes to efficiently harvest horizontal and vertical vibration energy. The MV‐TENG demonstrates the capability to harvest vibration energy within a range of 1–3.5 Hz horizontally and 4 Hz, 9–60 Hz vertically, covering the occurrence range of breeze vibrations and sub‐span oscillations of transmission line effectively. Three application strategies include self‐powered tower obstacle alerting, temperature and humidity online monitoring, and high‐temperature wireless warning of transmission lines based on MV‐TENG. In summary, this work presents a comprehensive implementation scheme for digitally integrating TENGs into smart transmission lines, thereby facilitating the engineering development of TENG technology in grid systems.

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Section: Introductionmentioning

confidence: 99%

Multi‐Mode Vibrational Triboelectric Nanogenerator for Broadband Energy Harvesting and Utilization in Smart Transmission Lines

Zhang,

Yu,

Xia

et al. 2023

Advanced Energy Materials

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“…Accurately obtaining the spatial positions and dimensions of transmission towers is vital for power system operation and maintenance. However, traditional manual measurement methods are inefficient, and fail to meet the requirements for rapid and accurate data acquisition [2,3] . To address this problem, in recent years, researchers have proposed combining 3D reconstruction technology with automated measurement techniques to achieve accurate reconstruction of transmission towers [4,5] .The integration of these techniques enables accurate 3D modeling of transmission towers and facilitates rapid and accurate measurement of tower height [6] .…”

Section: Introductionmentioning

confidence: 99%

Automatic measurement of transmission tower height based on PointNet++ and support vector regression

Qin,

Chen,

et al. 2023

Second International Conference on Geographic Information and Remote Sensing Technology (GIRST 2023)

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“…Hence, it is crucial to detect bird nest defects in transmission lines. In traditional manual inspection, inspectors need to climb towers or use overhead equipment to inspect, which is a labour‐intensive, costly and safety‐risky method [5].…”

Section: Introductionmentioning

confidence: 99%

Bird's nest defect detection of transmission lines based on domain knowledge and occlusion reasoning

Dong,

Zhang,

Chen

et al. 2023

IET Generation Trans & Dist

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Bird's nest defect is an important cause of transmission line faults. To achieve accurate detection of bird nest defects in complex scenarios, a bird nest defect detection model for transmission lines was proposed that combines domain knowledge and occlusion reasoning networks. On the one hand, the model utilized the domain knowledge of the location of the bird's nest, using edge detection to obtain tower area information to constrain the location of candidate frames. This helps to reduce the false detection caused by complex backgrounds. On the other hand, on the basis of analyzing the occlusion characteristics of bird nests, the model employed occlusion reasoning networks that randomly erase features at the feature level to simulate the occlusion of bird nests in real scenes and improve the model's detection capability for occluded targets. Additionally, a multi‐scale feature fusion algorithm was designed in this paper to adapt the model to the scale variations of bird nests in aerial images. Experimental results demonstrate that the model outperforms advanced target detection models and other bird nest defect detection methods, with an AP50 of 78.8% and an AR10 of 72.4% for defect detection.

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A survey of intelligent transmission line inspection based on unmanned aerial vehicle

Cited by 68 publications

References 120 publications

Multi‐Mode Vibrational Triboelectric Nanogenerator for Broadband Energy Harvesting and Utilization in Smart Transmission Lines

Multi‐Mode Vibrational Triboelectric Nanogenerator for Broadband Energy Harvesting and Utilization in Smart Transmission Lines

Automatic measurement of transmission tower height based on PointNet++ and support vector regression

Bird's nest defect detection of transmission lines based on domain knowledge and occlusion reasoning

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