@inproceedings{b30a1d56afc544f7bfad9cb5f81abdb7,
title = "Harmonic identification based on RBF neural network",
abstract = "As one of the important equipment for vibration test, hydraulic shaking table can produce great vibration force and displacement of vibration, , widely applied in engineering field. In the test system of hydraulic shaking table, because of the existence of non-linearities, there exists higher harmonic in system response signal when the shaking table is excited by a sinusoidal signal, making the harmonic distortion of the system response. In view of harmonic distortion of response signal in the sine-vibration test, the paper adopts RBF neural network to study how to identify the amplitude and phase, which provides reliable data for harmonic suppression and elimination.",
keywords = "RBF, harmonic, identification",
author = "Jianjun Yao and Shuo Chen and Qingtao Niu and Le Zhang and Cheng Sun and Zhenshuai Wan",
note = "Publisher Copyright: {\textcopyright} 2016 TCCT.; 35th Chinese Control Conference, CCC 2016 ; Conference date: 27-07-2016 Through 29-07-2016",
year = "2016",
month = aug,
day = "26",
doi = "10.1109/ChiCC.2016.7553371",
language = "英语",
series = "Chinese Control Conference, CCC",
publisher = "IEEE Computer Society",
pages = "1897--1902",
editor = "Jie Chen and Qianchuan Zhao and Jie Chen",
booktitle = "Proceedings of the 35th Chinese Control Conference, CCC 2016",
address = "美国",
}