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Sensors 2014, 14(4), 6207-6228; doi:10.3390/s140406207
Article

Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth

1
, 1
 and 2,*
Received: 26 January 2014; in revised form: 11 March 2014 / Accepted: 13 March 2014 / Published: 28 March 2014
(This article belongs to the Section Physical Sensors)
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Abstract: Oil debris sensors are effective tools to monitor wear particles in lubricants. For in situ applications, surrounding noise and vibration interferences often distort the oil debris signature of the sensor. Hence extracting oil debris signatures from sensor signals is a challenging task for wear particle monitoring. In this paper we employ the maximal overlap discrete wavelet transform (MODWT) with optimal decomposition depth to enhance the wear particle monitoring capability. The sensor signal is decomposed by the MODWT into different depths for detecting the wear particle existence. To extract the authentic particle signature with minimal distortion, the root mean square deviation of kurtosis value of the segmented signal residue is adopted as a criterion to obtain the optimal decomposition depth for the MODWT. The proposed approach is evaluated using both simulated and experimental wear particles. The results show that the present method can improve the oil debris monitoring capability without structural upgrade requirements.
Keywords: wear particle; oil debris sensor; monitoring; wavelet transform; optimal decomposition depth wear particle; oil debris sensor; monitoring; wavelet transform; optimal decomposition depth
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Li, C.; Peng, J.; Liang, M. Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth. Sensors 2014, 14, 6207-6228.

AMA Style

Li C, Peng J, Liang M. Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth. Sensors. 2014; 14(4):6207-6228.

Chicago/Turabian Style

Li, Chuan; Peng, Juan; Liang, Ming. 2014. "Enhancement of the Wear Particle Monitoring Capability of Oil Debris Sensors Using a Maximal Overlap Discrete Wavelet Transform with Optimal Decomposition Depth." Sensors 14, no. 4: 6207-6228.


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