文献
J-GLOBAL ID:202102282825408215
整理番号:21A3384163
カスケードおよび双方向深層学習ネットワークに基づく風力タービンの状態監視と異常検出【JST・京大機械翻訳】
Condition monitoring and anomaly detection of wind turbine based on cascaded and bidirectional deep learning networks
著者 (5件):
Xiang Ling
(School of Mechanical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China)
,
Yang Xin
(School of Mechanical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China)
,
Hu Aijun
(School of Mechanical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China)
,
Su Hao
(School of Mechanical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China)
,
Wang Penghe
(School of Mechanical Engineering, North China Electric Power University, Baoding 071003, Hebei Province, China)
資料名:
Applied Energy
(Applied Energy)
巻:
305
ページ:
Null
発行年:
2022年
JST資料番号:
A0097A
ISSN:
0306-2619
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)