文献
J-GLOBAL ID:202102257987870992
整理番号:21A0673133
重み付き2D故障特徴抽出とマルチレベル情報融合に基づく機械故障診断【JST・京大機械翻訳】
Machinery Fault Diagnosis Based on Weighted 2D Fault Feature Extraction and Multi-level Information Fusion
著者 (6件):
Luo Ziao
(Chongqing University of Posts and Telecommunications,School of Advanced Manufacturing Engineering,Chongqing,China,400065)
,
Su Zuqiang
(Chongqing University of Posts and Telecommunications,School of Advanced Manufacturing Engineering,Chongqing,China,400065)
,
Tan Feng
(Chongqing University of Posts and Telecommunications,School of Advanced Manufacturing Engineering,Chongqing,China,400065)
,
Ruixing Hu
(The 44th Research Institute of CETC,Chongqing,China,400065)
,
Hu Xiaolin
(Chongqing Innovation Center of Industrial Big-Data Co. Ltd National Engineering Laboratory for Industrial Big-data Application Technology,Chongqing,China,400065)
,
Xing Bin
(Chongqing Innovation Center of Industrial Big-Data Co. Ltd National Engineering Laboratory for Industrial Big-data Application Technology,Chongqing,China,400065)
資料名:
IEEE Conference Proceedings
(IEEE Conference Proceedings)
巻:
2020
号:
SDPC
ページ:
296-302
発行年:
2020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)