tdEIT and Unet-based rapid imaging of redistributed wear particles in lubricating oil

Zhu, Ling; Wang, Yishou; Weixuan, Zhang; Xiangwen, Xiao; Liu, Yuan; Xue, Wendong

doi:10.1016/j.triboint.2022.107981

Cited by 4 publications

(1 citation statement)

References 23 publications

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“…This algorithm was specifically developed for imaging the accumulation area of wear particles in lubricating oil. The authors illustrated the algorithm's performance and results in Figure 7 [85]. This method entails the analysis of wear particle characteristics by examining the accumulation area of lubricant wear particles using an algorithm.…”

Section: Image Processing Sensormentioning

confidence: 99%

A Critical Review of On-Line Oil Wear Debris Particle Detection Sensors

Han,

Mu,

Liu

et al. 2023

JMSE

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In the field of marine engineering, the friction and wear experienced by rotating mechanisms are recognized as significant contributors to the failure of marine machinery. In order to enhance the safety and dependability of marine ship operations, the implementation of on-line oil wear debris particle detection sensors enables the on-line monitoring of oil and facilitates the rapid identification of abnormal wear locations. This paper provides a critical review of the recent research progress and development trends in the field of sensors for on-line detection of oil wear debris particles. According to the method of sensor detection, wear debris particle detection sensors can be classified into two distinct categories: electrical and non-electrical sensors. Electrical sensors encompass a range of types, including inductive, capacitive, and resistive sensors. Non-electrical sensors encompass a range of technologies, such as image processing sensors, optical sensors, and ultrasonic sensors. Finally, this review addresses the future research directions for wear debris particle detection sensors in light of the challenging problems currently faced by these sensors.

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Section: Image Processing Sensormentioning

confidence: 99%