Intelligent patrol terminal of transmission line based on AI chip accelerated calculation
With the rapid development of artificial intelligence and information recognition technology, the edge intelligent terminal based on AI chip provides a new way for power patrol. AI chips have become one of the most important components in edge intelligent terminals. However, there are many types of...
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Published in: | Energy reports Vol. 9; pp. 190 - 198 |
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Main Authors: | , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
Elsevier Ltd
01-04-2023
Elsevier |
Subjects: | |
Online Access: | Get full text |
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Summary: | With the rapid development of artificial intelligence and information recognition technology, the edge intelligent terminal based on AI chip provides a new way for power patrol. AI chips have become one of the most important components in edge intelligent terminals. However, there are many types of AI chips, and it is particularly important to select appropriate AI chips for application scenarios. Due to the limited computing power of the edge side AI chip, to ensure the real-time performance of the patrol task, it is necessary to research the edge side inference acceleration processing technology. First of all, the parameters and characteristics of various AI chips are analyzed in detail to provide reference for chip selection in different application scenarios. Secondly, a basic framework of power intelligent patrol terminal based on AI chip is proposed, which includes hardware component and software component. Then, in order to transplant the neural network model on the server side to the intelligent patrol terminal, the edge side inference acceleration processing technology is analyzed in detail, specifically the neural network acceleration and compression method and the inference acceleration technology based on TensorRT. Finally, in order to prove the feasibility and effectiveness of the whole scheme, an intelligent patrol terminal applied to the visual defect recognition for transmission lines has been developed and tested. |
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ISSN: | 2352-4847 2352-4847 |
DOI: | 10.1016/j.egyr.2023.02.075 |