Identification of the Electric Spark Electromagnetic Waveform Based on SVM

DOI

10.2991/eame-18.2018.6How to use a DOI?

Keywords

SVM; features of electromagnetic waveform; waveform identification

Abstract

Electromagnetic wave of electrical spark is a potential cause to eletrical equipment failure. This research focused on identificating and comparative analyzing the different types of electromagnetic waveform generated by eletrical equipment failure based on SVM. After analyzing and extracting the features the electromagnetic waveform, a model was built to identificate the type of the elctromagnetic waveform. The collected standard electromagnetic waveforms were used as the imput of the train model and the model accuracy was improved by adjusting training parameters afer analyzing the results, When inputting an unknown type of electromagnetic waveform, SVM may predict the output of the network according to the recognition rule. Then the types of electromagnetic waveforms were identificated by using adjusted models. The result shows that the electromagnetic waveform can be effectively and feasibly identificated based on SVM, which provides a theoretical support on prediction method of gas explosion caused by electrical sparks.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Tongtong Li
AU  - Ziyuan Tong
AU  - Shoufeng Tang
AU  - Xia Qin
AU  - Mingming Tong
AU  - Zhaoliang Xu
PY  - 2018/06
DA  - 2018/06
TI  - Identification of the Electric Spark Electromagnetic Waveform Based on SVM
BT  - Proceedings of the 2018 3rd International Conference on Electrical, Automation and Mechanical Engineering (EAME 2018)
PB  - Atlantis Press
SP  - 27
EP  - 29
SN  - 2352-5401
UR  - https://doi.org/10.2991/eame-18.2018.6
DO  - 10.2991/eame-18.2018.6
ID  - Li2018/06
ER  -