4.7 Review

Online oil debris monitoring of rotating machinery: A detailed review of more than three decades

Journal

MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 149, Issue -, Pages -

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2020.107341

Keywords

Oil debris monitoring; Rotating machinery; Wear debris sensor; Online health monitoring; Lubricating oil

Funding

  1. Key Technology Research and Development Program of Shandong [2019JZZY020313, 2019GSF108005]

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This paper provides a detailed survey and classification of the advances in oil debris monitoring for online health monitoring of rotating machinery. It systematically analyzes the detection mechanisms of various sensing technologies, reviews real applications, and points out future works required to address the challenges faced by online monitoring of rotating machinery. Some of these sensing technologies have already been commercialized, indicating their practicality beyond research activities.
Oil debris monitoring has played an irreplaceable role in ascertaining the health condition of rotating machinery (e.g. engine, gearbox). Although many sensing methods for detecting wear-generated particles of rotating elements have been presented, a comprehensive review paper on these technologies is still missing. To this end, this paper provides a detailed survey of the advances in oil debris monitoring for the online health monitoring of rotating machinery. According to the detection mechanism, these sensing technologies are classified under varying categories (magnetic: magnetic chip detectors and inductive sensors, electrical: resistive-capacitive sensors and electrostatic sensors, optical: photoelectric sensors and imaging sensors, acoustic). The systematic analysis and commentary on each sensing method are conducted, and real applications also be reviewed. These sensing technologies are not confined to research-related activities, of which some have already been patented and commercialized. Finally, future works are presented to meet the challenges faced by online monitoring of rotating machinery. (C) 2020 Elsevier Ltd. All rights reserved.

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