文献
J-GLOBAL ID:202002236069116256
整理番号:20A0492959
特徴選択フィードバックネットワークと改良D-S証拠融合に基づくベアリング故障診断法【JST・京大機械翻訳】
A Bearing Fault Diagnosis Method Based on Feature Selection Feedback Network and Improved D-S Evidence Fusion
著者 (6件):
Tang Xianghong
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
,
Gu Xin
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
,
Wang Jiachen
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
,
He Qiang
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
,
Zhang Fan
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
,
Lu Jianguang
(Key Laboratory of Advanced Manufacturing Technology, Ministry of Education, Guizhou University, Guiyang, China)
資料名:
IEEE Access
(IEEE Access)
巻:
8
ページ:
20523-20536
発行年:
2020年
JST資料番号:
W2422A
ISSN:
2169-3536
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)