Image-Based Debris Detector With a Circular Channel for Lube Oil High-Throughput Monitoring

被引:0
|
作者
Feng, Song [1 ]
Yang, Jie [1 ]
Fan, Bin [2 ]
Xiao, Hong [1 ]
Su, Zuqiang [1 ]
Lu, Sheng [1 ]
机构
[1] Chongqing Univ Posts & Telecommun, Sch Adv Mfg Engn, Chongqing 400065, Peoples R China
[2] Inner Mongolia Agr Univ, Coll Mech & Elect Engn, Hohhot 010018, Peoples R China
关键词
Oils; Imaging; Detectors; Monitoring; Magnetic resonance imaging; Air gaps; Sensor phenomena and characterization; Debris image; denoising diffusion probabilistic model (DDPM); local defocus blur; oil debris sensor; WEAR PARTICLES; ONLINE; SYSTEM; GEARBOX;
D O I
10.1109/TIM.2024.3450070
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Image-based debris sensors are crucial for wear monitoring, but the narrow flow channel under oil debris microimaging conditions hinders high-throughput monitoring due to increased flow resistance and susceptibility to clogging. Also, a large-diameter image-based debris sensor was proposed. The sensor uses a rotationally symmetric high-gradient magnetic field (HGMF) to deposit wear debris on the inner wall of the circular channel. The resulting debris images exhibit local defocus blur. An automatic labeling dataset of the local defocus blur debris images (LDBDIs) was constructed, and a denoising diffusion probabilistic model (DDPM) was used to achieve high-quality restoration of the LDBDIs and to extend the depth of field (DOF) of wear debris microimaging on the cylindrical surface. The proposed sensor realizes large DOF imaging of wear debris under a high flow rate and can provide a new solution for the online monitoring of equipment wear.
引用
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页数:8
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