文献
J-GLOBAL ID:201902267444326949
整理番号:19A2116733
監視データの多特徴融合に基づくパイプラインシステムのための故障認識技術【JST・京大機械翻訳】
Fault Recognition Technology for Pipeline Systems Based on Multi-feature Fusion of Monitoring Data
著者 (6件):
Jiang Hongquan
(State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiao tong University, Xi’an, China)
,
Gao Jianmin
(State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiao tong University, Xi’an, China)
,
Xia Fengshe
(Shaanxi Special Equipment, Inspection and Testing Institute, Xi’an, China)
,
Zhang Xiaoming
(Shaanxi Special Equipment, Inspection and Testing Institute, Xi’an, China)
,
Zhou Tao
(State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiao tong University, Xi’an, China)
,
Liu Dongcheng
(State Key Laboratory for Manufacturing Systems Engineering, Xi’an Jiao tong University, Xi’an, China)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2019
号:
ICPHM
ページ:
1-7
発行年:
2019年
JST資料番号:
W2441A
資料種別:
会議録 (C)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)