| Issue |
E3S Web Conf.
Volume 185, 2020
2020 International Conference on Energy, Environment and Bioengineering (ICEEB 2020)
|
|
|---|---|---|
| Article Number | 01063 | |
| Number of page(s) | 6 | |
| Section | Energy Engineering and Power System | |
| DOI | https://doi.org/10.1051/e3sconf/202018501063 | |
| Published online | 01 September 2020 | |
Design and Application of Transmission Line Intelligent Monitoring System
Beijing Smartchip Microelectronics Technology Company Limited, Beijing 100080, China
* Corresponding author: xingzengqiang@163.com
This paper presents a design method of intelligent monitoring system for transmission lines based on artificial intelligence technology. In this design method, a low-power artificial intelligence chip - LieYing A101 is used to design an intelligent recognition module to realize real-time target recognition on a terminal device. In order to solve the problem that the original image and the input image resolution of the intelligent recognition module do not match, this paper uses a sliding window and convolutional neural network design method, which solves the image resolution mismatch problem and improves the recognition accuracy. Finally, for the problem of excessive network model size, feature channel weight pruning and 8-bit quantization methods are used to compress the network model to less than 10M, and the recognition accuracy is not sharply reduced. After the test set test and actual scene use, the external force destruction target recognition accuracy of the transmission line channel is high; this meets the application needs of customers.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.