文章基本信息

标题：Mechatronics applications of condition monitoring using a statistical change detection method
本地全文：下载
作者：M. Mazzoleni ; M. Scandella ; L. Maurelli 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2020
卷号：53
期号：2
页码：92-97
DOI：10.1016/j.ifacol.2020.12.100
语种：English
出版社：Elsevier
摘要：AbstractIn this paper, we propose the use of a change detection strategy to perform condition monitoring of mechanical components. The method looks for statistical changes in the distribution of features extracted from raw measurements, such as Root Mean Square or Crest Factor indicators. The proposed method works in a batch fashion, comparing data from one experiment to another. When these distributions differ by a specified amount, a degradation score is increased. The approach is tested on three experimental applications: (i) an ElectroMechanical Actuator (EMA) employed in flight applications, where the focus of the monitoring is on the ballscrew transmission; (ii) a CNC workbench, where the focus is on the vertical shaft bearing, (iii) an industrial EMA with focus on the ballscrew bearing. All components have undergone a severe experimental degradation process, that ultimately led to their failure. Results show how the proposed method is able to assess component degradation prior to their failure.
关键词：KeywordsPredictive maintenancecondition monitoringactuatorsbearings