Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique

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 metho...

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Main Authors: Li, Tongyang, Wang, Shaoping, Zio, Enrico, Shi, Jian, Hong, Wei
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2018
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Online Access:https://hdl.handle.net/10356/89038
http://hdl.handle.net/10220/44759
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-890382020-03-07T13:57:31Z Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique Li, Tongyang Wang, Shaoping Zio, Enrico Shi, Jian Hong, Wei School of Electrical and Electronic Engineering Aviation Hydraulic Pump Radial Magnetic Field 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. Published version 2018-05-09T02:13:03Z 2019-12-06T17:16:30Z 2018-05-09T02:13:03Z 2019-12-06T17:16:30Z 2018 Journal Article Li, T., Wang, S., Zio, E., Shi, J., & Hong, W. (2018). Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique. Sensors, 18(3), 866-. 1424-8220 https://hdl.handle.net/10356/89038 http://hdl.handle.net/10220/44759 10.3390/s18030866 en Sensors © 2018 by The Author(s). Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). 15 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Aviation Hydraulic Pump
Radial Magnetic Field
spellingShingle Aviation Hydraulic Pump
Radial Magnetic Field
Li, Tongyang
Wang, Shaoping
Zio, Enrico
Shi, Jian
Hong, Wei
Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
description 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.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Li, Tongyang
Wang, Shaoping
Zio, Enrico
Shi, Jian
Hong, Wei
format Article
author Li, Tongyang
Wang, Shaoping
Zio, Enrico
Shi, Jian
Hong, Wei
author_sort Li, Tongyang
title Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
title_short Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
title_full Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
title_fullStr Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
title_full_unstemmed Aliasing Signal Separation of Superimposed Abrasive Debris Based on Degenerate Unmixing Estimation Technique
title_sort aliasing signal separation of superimposed abrasive debris based on degenerate unmixing estimation technique
publishDate 2018
url https://hdl.handle.net/10356/89038
http://hdl.handle.net/10220/44759
_version_ 1681043535980134400