Foreign Objects Identification of Transmission Line Based on Improved YOLOv7

Yu, Chenhui; Liu, Yakui; Zhang, Wanru; Zhang, Xue; Zhang, Yuhan; Jiang, Xiaoyu

doi:10.1109/access.2023.3277954

Cited by 8 publications

(5 citation statements)

References 48 publications

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“…We propose a target detection and tracking method that combines 360 • panoramic images with 3-axis gimbals mounted on a UAV. Our method has a larger field of view than other intrusion target detection methods [10,37].…”

Section: Intrusion Detection Model Experimentsmentioning

confidence: 99%

A Deep Learning Approach of Intrusion Detection and Tracking with UAV-Based 360° Camera and 3-Axis Gimbal

Xu,

Liu,

et al. 2024

Drones

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Intrusion detection is often used in scenarios such as airports and essential facilities. Based on UAVs equipped with optical payloads, intrusion detection from an aerial perspective can be realized. However, due to the limited field of view of the camera, it is difficult to achieve large-scale continuous tracking of intrusion targets. In this study, we proposed an intrusion target detection and tracking method based on the fusion of a 360° panoramic camera and a 3-axis gimbal, and designed a detection model covering five types of intrusion targets. During the research process, the multi-rotor UAV platform was built. Then, based on a field flight test, 3043 flight images taken by a 360° panoramic camera and a 3-axis gimbal in various environments were collected, and an intrusion data set was produced. Subsequently, considering the applicability of the YOLO model in intrusion target detection, this paper proposes an improved YOLOv5s-360ID model based on the original YOLOv5-s model. This model improved and optimized the anchor box of the YOLOv5-s model according to the characteristics of the intrusion target. It used the K-Means++ clustering algorithm to regain the anchor box that matches the small target detection task. It also introduced the EIoU loss function to replace the original CIoU loss function. The target bounding box regression loss function made the intrusion target detection model more efficient while ensuring high detection accuracy. The performance of the UAV platform was assessed using the detection model to complete the test flight verification in an actual scene. The experimental results showed that the mean average precision (mAP) of the YOLOv5s-360ID was 75.2%, which is better than the original YOLOv5-s model of 72.4%, and the real-time detection frame rate of the intrusion detection was 31 FPS, which validated the real-time performance of the detection model. The gimbal tracking control algorithm for intrusion targets is also validated. The experimental results demonstrate that the system can enhance intrusion targets’ detection and tracking range.

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Section: Intrusion Detection Model Experimentsmentioning

confidence: 99%

A Deep Learning Approach of Intrusion Detection and Tracking with UAV-Based 360° Camera and 3-Axis Gimbal

Xu,

Liu,

et al. 2024

Drones

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“…In addition, an attention mechanism based on coordinated attention (CA) was incorporated to effectively extract key feature information. Yu et al [21], based on the YOLOv7 algorithm, achieved hyperparameter optimization using the Genetic Algorithm (GA) by replacing the convolutional and pooling layers of YOLOv7 with Space to Depth (SPD) spatial-depth-transformed convolution to improve the accuracy of foreign object identification for aerial UAVs. Shao et al [22], based on the YOLOv7 Tiny algorithm, using the Focal-DIoU (Distance-Intersection over Union) loss function to effectively solve the problem of sample category imbalance and sample difficulty imbalance.…”

Section: Introductionmentioning

confidence: 99%

SOD-YOLO: A High-Precision Detection of Small Targets on High-Voltage Transmission Lines

Wu,

Chen,

et al. 2024

Electronics

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Wire clamps and vibration-proof hammers are key components of high-voltage transmission lines. The wire clips and vibration-proof hammers detected in Unmanned Aerial Vehicle (UAV) power inspections suffer from small size, scarce edge information, and low recognition accuracy. To address these problems, this paper proposes a small object detection (SOD) model based on the YOLOv8n, called SOD-YOLO. Firstly, an extra small target detection layer was added to YOLOv8, which significantly improves the small target detection accuracy. In addition, in order to enhance the detection speed of the model, the RepVGG/RepConv ShuffleNet (RCS) and a OneShot Aggregation of the RCS (RCSOSA) module were introduced to replace the C2f module in the model backbone and neck shallow networks. Finally, to address the excessive focus on low-quality sample bounding boxes during model training, we introduced Wise-CIoU loss instead of CIoU loss, which improved the detection accuracy of the model. The experimental results indicate that SOD-YOLO achieved a mean average precision of 90.1%, surpassing the YOLOv8n baseline model by 7.5% while maintaining a model parameter count of 3.4 M; the inference speed reached 88.7 frames/s, which meets the requirement of real-time recognition.

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“…Consequently, the amount of electrical energy that must be supplied to consumers also increases as energy demand increases. This situation corresponds to the increasing number of high-voltage transmission lines (HVTL) required to transport electricity from distant power plants [1]- [4]. The construction of HVTL requires careful consideration of environmental issues and avoiding potential damage to the HVTL network [3]- [6].…”

Section: Introductionmentioning

confidence: 99%

“…In the past, interference from kites on the conductor wire has been removed by crawling over it. This traditional approach is risky for safety, expensive, and time-consuming [4], [13], [15]. As a result, a novel, easy, and affordable kite-clearing technique needs to be created.…”

Section: Introductionmentioning

confidence: 99%

“…The unit is mounted on a UAV [16]- [18] and is remotely controlled via a transmitter and receiver module. The use of UAV is suggested in this study because it is more efficient, time-saving and cost-effective, especially for small-budget projects [4], [19]- [22]. The transceiver module (NRF24L01) provides connectivity between transmitter and receiver units.…”

Section: Introductionmentioning

confidence: 99%

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A flamethrower mounted on UAV for kite litter clearing on high voltage transmission line

Pratama,

Al Haqqi,

Sati’at

et al. 2024

IJEECS

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The high voltage transmission line (HVTL) is a part of the electric power transmission system that distributes high-capacity electricity. There were numerous interruptions to the transmission line, one of which was caused by the kite getting stuck in the conductor. In the past, interference from kites on the conductor wire has been removed by crawling over it. This conventional method poses safety risks, is high-cost, and is time-consuming. This article describes the development of a flamethrower mounted on an unmanned aerial vehicle (UAV) for kite litter clearing on a high-voltage transmission line is presented. The flamethrower is fitted on the UAV to achieve high-mounted wire. The UAV was controlled using a transmitter and a receiver based on an Arduino. The flamethrower was tested for clearing a kite on the transmission line. The effect of nozzle diameter on flame burst length and the time it takes to burn a kite has been investigated. According to the experiment results, the performance of the flamethrower is highly satisfactory. Based on the component prices and manufacturing costs, the flamethrower has been successfully assembled at a low cost for a total of below $55.

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Foreign Objects Identification of Transmission Line Based on Improved YOLOv7

Cited by 8 publications

References 48 publications

A Deep Learning Approach of Intrusion Detection and Tracking with UAV-Based 360° Camera and 3-Axis Gimbal

A Deep Learning Approach of Intrusion Detection and Tracking with UAV-Based 360° Camera and 3-Axis Gimbal

SOD-YOLO: A High-Precision Detection of Small Targets on High-Voltage Transmission Lines

A flamethrower mounted on UAV for kite litter clearing on high voltage transmission line

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