Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4206
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Michail, Konstantinos | - |
dc.contributor.author | Tzafestas, Spyros G. | - |
dc.contributor.author | Zolotas, Argyrios C. | - |
dc.contributor.author | Deliparaschos, Kyriakos M. | - |
dc.date.accessioned | 2013-10-30T16:17:33Z | - |
dc.date.accessioned | 2015-12-09T12:01:40Z | - |
dc.date.available | 2013-10-30T16:17:33Z | - |
dc.date.available | 2015-12-09T12:01:40Z | - |
dc.date.issued | 2013 | - |
dc.identifier.citation | 21st Mediterranean Conference on Control & Automation (MED) , pp.1127,1132, 25-28 June 2013 | en_US |
dc.identifier.isbn | 978-1-4799-0995-7 | - |
dc.description.abstract | A low computational power method is proposed for detecting actuators/sensors faults. Typical model-based fault detection units for multiple sensor faults, require a bank of observers (these can be either conventional observers of artificial intelligence based). The proposed control scheme uses an artificial intelligence approach for the development of the fault detection unit abbreviated as `iFD'. In contrast with the bank-of-estimators approach, the proposed iFD unit employs a single estimator for multiple sensor fault detection. The efficacy of the scheme is illustrated on an Electromagnetic Suspension system example with a number of sensor fault scenaria. | en_US |
dc.format | en_US | |
dc.language.iso | en | en_US |
dc.rights | IEEE Xplore | en_US |
dc.subject | Artificial intelligence | en_US |
dc.subject | Electromagnetic actuators | en_US |
dc.subject | Fault diagnosis | en_US |
dc.subject | Magnetic levitation | en_US |
dc.subject | Neural nets | en_US |
dc.subject | Observers | en_US |
dc.subject | Suspensions (mechanical components) | en_US |
dc.title | AI-based low computational power actuator/sensor fault detection applied on a MAGLEV suspension | en_US |
dc.type | Conference Papers | en_US |
dc.link | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6608862&isnumber=6608682 | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | National and Kapodistrian University of Athens | en_US |
dc.collaboration | University of Sussex | en_US |
dc.subject.category | Mechanical Engineering | en_US |
dc.country | Cyprus | en_US |
dc.country | Greece | en_US |
dc.country | United Kingdom | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.relation.conference | Mediterranean Conference on Control & Automation (MED) | en_US |
dc.identifier.doi | 10.1109/MED.2013.6608862 | en_US |
dc.dept.handle | 123456789/134 | en |
cut.common.academicyear | 2012-2013 | en_US |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_c94f | - |
item.openairetype | conferenceObject | - |
item.cerifentitytype | Publications | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0003-0618-5846 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
AI-based.pdf | 500.74 kB | Adobe PDF | View/Open |
CORE Recommender
SCOPUSTM
Citations
3
checked on Nov 6, 2023
Page view(s)
482
Last Week
10
10
Last month
4
4
checked on Feb 17, 2025
Download(s)
186
checked on Feb 17, 2025
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.