A novel method for condition monitoring of rotating machinery based on statistical linguistic analysis and weighted similarity measures

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• 作者：Jinshan Lin^a ; ^{jslinmec@hotmail.com} ; Chunhong Dou^b
• 关键词：Condition monitoring ; Binary symbolic sequence ; Word frequency sequence ; Statistical linguistic analysis ; Weighted similarity measure ; Rotating machinery
• 刊名：Journal of Sound and Vibration
• 出版年：2017
• 出版时间：3 March 2017
• 年：2017
• 卷：390
• 期：Complete
• 页码：272-288
• 全文大小：2946 K
• 卷排序：390

文摘

Develop a new tool to adaptively map machine vibration data to symbolic sequences. Pioneer SLA in exploring dynamics hidden in binary symbolic sequences. Define a weighted similarity measure(WSM) to detect a change of machine conditions. Propose a novel method for condition monitoring of machines based on SLA and WSM.