An Inductive Sensor Based Multi-Least-Mean-Square Adaptive Weighting Filtering for Debris Feature Extraction

Monitoring the wear debris in lubricant systems is an effective method of reflecting the health of mechanical equipment. With the advantages of being simply structured, noninvasive, and insensitive to oil quality, inductive sensors are often deployed for debris detection. However, induced voltages g...

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Bibliographic Details
Published in:IEEE transactions on industrial electronics (1982) 2023-03, Vol.70 (3), p.3115-3125
Main Authors: Luo, Jiufei, Li, Jing, Wang, Xinyu, Feng, Song
Format: Article
Language:English
Subjects:
Adaptive filters
Algorithms
Coils
Component reliability
Correlation
Debris
Debris detection
Feature extraction
Filtration
Harmonic analysis
Inductive sensing devices
inductive sensor
least-mean-square (LMS)
Lubricants
noise canceling
Noise reduction
Power harmonic filters
Reference signals
Robustness
Sensors
System effectiveness
Time-domain analysis
Wear particles
Weighting
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Summary:Monitoring the wear debris in lubricant systems is an effective method of reflecting the health of mechanical equipment. With the advantages of being simply structured, noninvasive, and insensitive to oil quality, inductive sensors are often deployed for debris detection. However, induced voltages generated by wear debris are usually contaminated by noise and other undesired components, thereby limiting the reliability and availability of the sensors. In this article, a new debris-detection framework is proposed based on an inductive sensor with parallel dual coils. With the aid of a reference signal, a multi-least-mean-square adaptive weighting filtering method was developed, and good noise suppression was achieved with little violation of the debris signatures. The algorithm is illustrated through numerical simulations, and the effectiveness of the proposed framework was verified by an oil experiment. Two traditional denoising algorithms were also analyzed for comparison. The experimental results demonstrated that the proposed strategy had an excellent capability for extracting and identifying debris features.
ISSN:0278-0046
1557-9948
DOI:10.1109/TIE.2022.3169720