...
首页> 外文期刊>Mechanical systems and signal processing >Prognosability study of ball screw degradation using systematic methodology
【24h】

Prognosability study of ball screw degradation using systematic methodology

机译:使用系统方法对滚珠丝杠降解的可预测性研究

获取原文
获取原文并翻译 | 示例
           

摘要

As a critical mechanical component that converts rotary motion to linear motion with high precision, the ball screw has drawn a lot of attention in the field of Prognostics and Health Management (PHM). However, prognosis of the ball screw degradation has not been fully discussed yet in the current literature. This paper first justifies the prognosability of a ball screw via experimental studies, then proposes a systematic methodology for ball screw prognosis to implement the fault diagnosis, early diagnosis, health assessment and remaining useful life (RUL) prediction. Meanwhile, sensor-less and sensor-rich strategies are investigated and benchmarked in the experimental studies. The results demonstrate that the ball screw degradation behavior is available for prognosis and the proposed methodology can effectively help users to implement PHM analysis. Besides, the benchmark studies between sensor-less and sensor-rich strategies also achieve several practical conclusions that are valuable for real-world applications.
机译:作为高精度将旋转运动转换为线性运动的重要机械部件,滚珠丝杠在预后和健康管理(PHM)领域引起了很多关注。然而,在当前文献中尚未充分讨论滚珠丝杠退化的预后。本文首先通过实验研究证明了滚珠丝杠的可预见性,然后提出了一种用于滚珠丝杠预后的系统方法,以实现故障诊断,早期诊断,健康评估和剩余使用寿命(RUL)预测。同时,在实验研究中对无传感器和富传感器策略进行了研究和基准测试。结果表明,滚珠丝杠的降解行为可用于预后,所提出的方法可以有效地帮助用户实施PHM分析。此外,无传感器策略和富传感器策略之间的基准研究也得出了一些实用的结论,这些结论对于实际应用是有价值的。

著录项

  • 来源
    《Mechanical systems and signal processing》 |2018年第9期|45-57|共13页
  • 作者单位

    NSF I/UCR Center for Intelligent Maintenance Systems, Department of Mechanical Engineering, University of Cincinnati;

    NSF I/UCR Center for Intelligent Maintenance Systems, Department of Mechanical Engineering, University of Cincinnati;

    NSF I/UCR Center for Intelligent Maintenance Systems, Department of Mechanical Engineering, University of Cincinnati;

    NSF I/UCR Center for Intelligent Maintenance Systems, Department of Mechanical Engineering, University of Cincinnati;

    ShanXi Engineering Laboratory for Transmissions and Controls, Northwestern Polytechnical University;

    HIWIN Technologies Corp;

    NSF I/UCR Center for Intelligent Maintenance Systems, Department of Mechanical Engineering, University of Cincinnati;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Prognosability; Prognosis and health management; Data quality; Ball screw; Sensor-less; Sensor-rich;

    机译:可预后性;预后和健康管理;数据质量;滚珠丝杠;无传感器;传感器丰富;

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