• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2019, Vol. 55 ›› Issue (16): 1-6.doi: 10.3901/JME.2019.16.001

• 仪器科学与技术 •    下一篇


雷亚国1, 韩天宇1, 王彪1, 李乃鹏1, 闫涛1, 杨军2   

  1. 1. 西安交通大学现代设计及转子轴承系统教育部重点实验室 西安 710049;
    2. 浙江长兴昇阳科技有限公司 湖州 313100
  • 收稿日期:2019-04-26 修回日期:2019-07-03 出版日期:2019-08-20 发布日期:2019-08-20
  • 通讯作者: 雷亚国(通信作者),男,1979年出生,博士,教授,博士研究生导师。主要研究方向为大数据智能故障诊断与寿命预测、机械设备健康监测与智能维护、机械系统建模与动态信号处理。E-mail:yaguolei@mail.xjtu.edu.cn
  • 基金资助:

XJTU-SY Rolling Element Bearing Accelerated Life Test Datasets: A Tutorial

LEI Yaguo1, HAN Tianyu1, WANG Biao1, LI Naipeng1, YAN Tao1, YANG Jun2   

  1. 1. Key Laboratory of Education Ministry for Modern Design and Rotor-Bearing System, Xi'an Jiaotong University, Xi'an 710049;
    2. Zhejiang Changxing Sumyoung Technology Co., Ltd., Huzhou 313100
  • Received:2019-04-26 Revised:2019-07-03 Online:2019-08-20 Published:2019-08-20

摘要: 预测与健康管理对保障机械装备安全服役、提高生产效率、增加经济效益至关重要。高质量的全寿命周期数据是预测与健康管理领域的基础性资源,这些数据承载着反映装备服役性能完整退化过程与规律的关键信息。然而,由于数据获取成本高、存储与传输技术有待发展等原因,典型的全寿命周期数据极其匮乏,严重制约了机械装备预测与健康管理技术的理论研究与工程应用。为解决上述难题,西安交通大学机械工程学院雷亚国教授团队联合浙江长兴昇阳科技有限公司,选取工业场景中典型的关键部件——滚动轴承为试验对象,开展了历时两年的滚动轴承加速寿命试验,并将获取的试验数据——XJTU-SY滚动轴承加速寿命试验数据集面向全球学者公开发布。该数据集共包含3种工况下15个滚动轴承的全寿命周期振动信号,采样频率高、数据量大、失效类型丰富、记录信息详细,既可为预测与健康管理领域提供新鲜的"数据血液",推动故障诊断与剩余寿命预测等领域的算法研究,又可助力工业界智能化运维的"落地生根"。

关键词: 滚动轴承, 加速寿命试验, 预测与健康管理

Abstract: Prognostics and health management (PHM) is crucial for ensuring the safe operation of machinery, improving the productivity and increasing economic benefits. High-quality life-cycle data, as the basic resource in the field of PHM, are able to carry the key information which reflects the complete degradation processes of machinery. However, due to the high costs in data acquisition and insufficient development in storage and transmission technology, typical life-cycle data is extremely scarce, which limits the theoretical research and engineering application of PHM for machinery. In order to solve this dilemma, accelerated life tests of rolling element bearings are carried out by Prof. Yaguo Lei's research group from School of Mechanical Engineering, Xi'an Jiaotong University (XJTU) and the Changxing Sumyoung Technology Co., Ltd. (SY), Zhejiang. These tests lasted for two years and the acquired datasets, i.e., XJTU-SY bearing datasets, have been publicly released for all PHM researchers. The XJTU-SY bearing datasets contain run-to-failure vibration signals of 15 rolling element bearings under three different operating conditions. These datasets have high sampling frequency, large amount of data, abundant failure types and detailed recording information. Accordingly, these datasets not only provide fresh "data blood" for PHM and promote the research of fault diagnosis and remaining useful life prediction, but also are able to help to improve intelligent maintenance decision making in industry.

Key words: accelerated life tests, prognostics and health management, rolling element bearings