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XJTU-DV: Open-source dynamic vision dataset for non-contact vibration measurement and fault diagnosis of mechanical systems

  • Xiang Li
  • , Shupeng Yu
  • , Xinrui Chen
  • , Yaguo Lei
  • , Bin Yang
  • , Naipeng Li
  • Xi'an Jiaotong University

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Vibration measurement is of great importance for fault diagnosis and prognosis of mechanical systems in the literature. Non-contact vibration measurement methods have been attracting growing attention in recent years. Dynamic vision is an emerging vision technology, which is developed with neuromorphic sensing principles. This paper introduces XJTU-DV, an open-source dynamic vision dataset for non-contact vibration measurement and fault diagnosis of mechanical systems. The XJTU-DV-Beam sub-dataset includes the dynamic vision data on a structural beam system, as well as the corresponding laser vibrometer data as ground truth. The XJTU-DV-Rotor and XJTU-DV-Pump sub-datasets include the dynamic vision data from a rotor and a pump test bench, respectively. The dynamic vision data are collected under different fault and operating conditions. XJTU-DV provides a data foundation for dynamic vision-based studies on vibration measurement and fault diagnosis, which may promote further development of the emerging vision algorithms for industrial applications. The dataset can be accessed at https://gr.xjtu.edu.cn/web/lixiang/xjtu-dv for detailed information.

Original languageEnglish
Article number100163
JournalChinese Journal of Mechanical Engineering (English Edition)
Volume39
DOIs
StatePublished - Jan 2026

Keywords

  • Dynamic vision
  • Event camera
  • Fault diagnosis
  • Non-contact measurement
  • Vibration measurement

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