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...
Saved in:
Main Authors: | , , , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/89038 http://hdl.handle.net/10220/44759 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-89038 |
---|---|
record_format |
dspace |
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 |