Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
1
School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China
2
Energy Department, Politecnico di Milano, Via La Masa 34, 20156 Milano, Italy
3
Chair on System Science and the Energy Challenge, Fondation Electricite’ de France (EDF), CentraleSupélec, Université Paris-Saclay, Grande Voie des Vignes, 92290 Chatenay-Malabry, France
4
School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(3), 866; https://doi.org/10.3390/s18030866
Received: 14 December 2017
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Revised: 23 February 2018
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Accepted: 10 March 2018
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Published: 15 March 2018
(This article belongs to the Special Issue Mechatronic Systems for Automatic Vehicles)
Leakage is the most important failure mode in aircraft hydraulic systems caused by wear and tear between friction pairs of components. The accurate detection of abrasive debris can reveal the wear condition and predict a system’s lifespan. The radial magnetic field (RMF)-based debris detection method provides an online solution for monitoring the wear condition intuitively, which potentially enables a more accurate diagnosis and prognosis on the aviation hydraulic system’s ongoing failures. To address the serious mixing of pipe abrasive debris, this paper focuses on the superimposed abrasive debris separation of an RMF abrasive sensor based on the degenerate unmixing estimation technique. Through accurately separating and calculating the morphology and amount of the abrasive debris, the RMF-based abrasive sensor can provide the system with wear trend and sizes estimation of the wear particles. A well-designed experiment was conducted and the result shows that the proposed method can effectively separate the mixed debris and give an accurate count of the debris based on RMF abrasive sensor detection.
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Keywords:
aviation hydraulic pump; radial magnetic field; aliasing signal separation; degenerate unmixing estimation technique; abrasive debris detection
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MDPI and ACS Style
Li, T.; Wang, S.; Zio, E.; Shi, J.; Hong, W. Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique. Sensors 2018, 18, 866. https://doi.org/10.3390/s18030866
AMA Style
Li T, Wang S, Zio E, Shi J, Hong W. Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique. Sensors. 2018; 18(3):866. https://doi.org/10.3390/s18030866
Chicago/Turabian StyleLi, Tongyang, Shaoping Wang, Enrico Zio, Jian Shi, and Wei Hong. 2018. "Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique" Sensors 18, no. 3: 866. https://doi.org/10.3390/s18030866
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