方位(导航)
轴
振动
状态监测
噪音(视频)
工程类
汽车工程
磁道(磁盘驱动器)
可靠性工程
信号(编程语言)
计算机科学
结构工程
机械工程
声学
物理
电气工程
人工智能
图像(数学)
程序设计语言
作者
Mani Entezami,Clive Roberts,Paul Weston,Edward Stewart,Arash Amini,Mayorkinos Papaelias
标识
DOI:10.1177/0954409719831822
摘要
Defects in railway axle bearings can affect operational efficiency, or cause in-service failures, damaging the track and train. Healthy bearings produce a certain level of vibration and noise, but a bearing with a defect causes substantial changes in the vibration and noise levels. It is possible to detect the bearing defects at an early stage of their development, allowing an operator to repair the damage before it becomes serious. When a vehicle is scheduled for maintenance, or due for overhaul, knowledge of bearing damage and severity is beneficial, resulting in fewer operational problems and optimised fleet availability. This paper is a review of the state of the art in condition monitoring systems for rolling element bearings, especially the axlebox bearings. This includes exploring the sensing technologies, summarising the main signal processing methods and condition monitoring techniques, i.e. wayside and on-board. Examples of commercially available systems and outputs of current research work are presented. The effectiveness of the current monitoring technologies is assessed and the p– f curve is presented. It is concluded that the research and practical tests on axlebox bearing monitoring are limited compared to the generic bearing applications.
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