Heterogeneous multi-parameter feature-level fusion for multi-source power sensing terminals: fusion mode, fusion framework and scene verification

Yanzhi Sun; Yuming Liu; Feng Tian; Chen Cui; Chaoguang Li

doi:10.1117/12.2615162

15 October 2021 Heterogeneous multi-parameter feature-level fusion for multi-source power sensing terminals: fusion mode, fusion framework and scene verification

Yanzhi Sun, Yuming Liu, Feng Tian, Chen Cui, Chaoguang Li

Author Affiliations +

Proceedings Volume 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering; 1193318 (2021) https://doi.org/10.1117/12.2615162
Event: 2021 International Conference on Neural Networks, Information and Communication Engineering, 2021, Qingdao, China

Abstract

At present, with the construction and advancement of domestic basic power facilities, the Internet of Things technology is slowly being effectively integrated with the traditional power grid. The effective integration of heterogeneous and multi-parameters generated by multi-source power sensing terminals is the realization of current power The key technology of the Internet of Things. At present, the integration of domestic power Internet of Things parameters is mainly based on the integration of homogeneous multi-parameters and main decision-making parameters. There are large technical gaps in the integration of heterogeneous and multi-dimensional multi-source parameters, which cannot meet the current power Internet of Things. The need for deep integration of multiple heterogeneous terminal parameters. This article analyzes the current status of multi-source power sensing terminal parameter fusion, analyzes the current power feature fusion method, fusion framework and fusion business scenarios, and finally verifies the effect of feature fusion through related scenarios.

Citation Download Citation

Yanzhi Sun, Yuming Liu, Feng Tian, Chen Cui, and Chaoguang Li "Heterogeneous multi-parameter feature-level fusion for multi-source power sensing terminals: fusion mode, fusion framework and scene verification", Proc. SPIE 11933, 2021 International Conference on Neural Networks, Information and Communication Engineering, 1193318 (15 October 2021); https://doi.org/10.1117/12.2615162

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KEYWORDS

Data fusion

Fusion energy

Signal processing

Image fusion

Internet

Pollution

Feature extraction

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