【24h】

An effective method for bearing faults diagnosis

机译:轴承故障诊断的有效方法

获取原文
获取原文并翻译 | 示例

摘要

The bearings are the most important mechanical elements of rotating machinery. They are employed to support and rotate the shafts in rotating machinery. An unexpected defect of the bearing may cause significant economic losses. For that reason, the condition monitoring of these bearings has become a fundamental axis of development and industrial research. The focus of this paper is to combine tow conventional methods: Hilbert Transform (HT) and Discrete Wavelet Transform (DWT) to develop a better method for detection and diagnosis the bearing faults. This new method applied on real measurement signals collected from an experimental vibration system. The monitoring results indicate that the proposed method improves the bearing faults diagnosis compared to other common techniques.
机译:轴承是旋转机械最重要的机械元件。它们用于支撑旋转机械中的轴并使其旋转。轴承的意外缺陷可能会导致重大的经济损失。因此,这些轴承的状态监控已成为发展和工业研究的基本轴。本文的重点是结合两种常规方法:希尔伯特变换(HT)和离散小波变换(DWT),以开发出一种更好的方法来检测和诊断轴承故障。这种新方法适用于从实验振动系统收集的真实测量信号。监测结果表明,与其他常用技术相比,该方法可以改善轴承的故障诊断。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号