Detection of bird species related to transmission line faults based on lightweight convolutional neural network

التفاصيل البيبلوغرافية
العنوان: Detection of bird species related to transmission line faults based on lightweight convolutional neural network
المؤلفون: Yanjun Kuang, Zhibin Qiu, Dazhai Shi, Caibo Liao, Yanglin Li, Xuan Zhu, Zhang Yu
المصدر: IET Generation, Transmission & Distribution, Vol 16, Iss 5, Pp 869-881 (2022)
بيانات النشر: Wiley, 2022.
سنة النشر: 2022
مصطلحات موضوعية: TK1001-1841, Distribution or transmission of electric power, Computer science, business.industry, Energy Engineering and Power Technology, Pattern recognition, TK3001-3521, Convolutional neural network, Production of electric energy or power. Powerplants. Central stations, Control and Systems Engineering, Transmission line, Artificial intelligence, Electrical and Electronic Engineering, business
الوصف: Efficient bird damage prevention of transmission lines is a long‐term challenge for power grid operation and maintenance. An approach combined lightweight convolutional neural network (CNN), image processing and object detection is presented in this paper to detect typical bird species related to transmission line faults. An image dataset of 20 bird species that threaten transmission line security is constructed. The YOLOv4‐tiny algorithm model is constructed and trained combining stage‐wise training, mosaic data enhancement, cosine annealing, and label smoothing. The mean average precision (mAP) can reach 92.04% on the test set by adjusting the parameters of the training process. Then, the validity of the proposed method is verified according to the test results and performance indexes by comparing with other methods, including Faster RCNN, SSD, YOLOv4 etc. Some image pre‐processing methods such as motion blur, defocus blur, contrast and brightness adjustment are used to simulate the scenarios in practical engineering applications. The proposed method can detect bird species perched around transmission lines with high‐efficiency, which is useful for differential prevention of bird‐related outages of power grids.
اللغة: English
تدمد: 1751-8687
1751-8695
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bffeb288e06d741152085ac408ff712
https://doaj.org/article/4b5c160334d94a9bac268326b9f5dc6c
حقوق: OPEN
رقم الأكسشن: edsair.doi.dedup.....1bffeb288e06d741152085ac408ff712
قاعدة البيانات: OpenAIRE