Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle

The degrading performance of actuators in small unmanned aerial Vehicle (UAV) is often left unnoticed because it is masked by autopilot control. The faulty actuator will only be detected when the actuator has been severely damaged. If it occurs during flight, the UAV will be lost, same goes with the...

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Main Authors: Sahwee Z., Rahman N.A., Sahari K.S.M., Mahmood A.S.
Other Authors: 55524079500
Format: Article
Published: American Scientific Publishers 2023
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Institution: Universiti Tenaga Nasional
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spelling my.uniten.dspace-234282023-05-29T14:40:25Z Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle Sahwee Z. Rahman N.A. Sahari K.S.M. Mahmood A.S. 55524079500 9338388000 57218170038 57193427529 The degrading performance of actuators in small unmanned aerial Vehicle (UAV) is often left unnoticed because it is masked by autopilot control. The faulty actuator will only be detected when the actuator has been severely damaged. If it occurs during flight, the UAV will be lost, same goes with the valuable data on the board. Usually, a pre-flight check is performed before each flight to ensure the overall condition of the UAV including the actuators. The actuator health deterioration is difficult to be recognized by visual inspection. This paper presents a method to detect the health of the actuator through the integration of Built-in Test System (BITE) using offline model estimation method. Least square regression estimation was performed on the healthy actuator for training data using fixed and increasing input signal. The fault is then simulated to test the training data accuracy in detecting actuator fault. An analysis is performed to show the advantage and disadvantage of each technique used. The estimation technique described was able to detect faulty actuator which could then be integrated with on-board health detection system in order to increase the reliability of the UAV. � 2017 American Scientific Publishers All rights reserved. Final 2023-05-29T06:40:25Z 2023-05-29T06:40:25Z 2017 Article 10.1166/asl.2017.7303 2-s2.0-85027851875 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027851875&doi=10.1166%2fasl.2017.7303&partnerID=40&md5=e83e7d767579e3393272267248856cd4 https://irepository.uniten.edu.my/handle/123456789/23428 23 6 5029 5033 American Scientific Publishers Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description The degrading performance of actuators in small unmanned aerial Vehicle (UAV) is often left unnoticed because it is masked by autopilot control. The faulty actuator will only be detected when the actuator has been severely damaged. If it occurs during flight, the UAV will be lost, same goes with the valuable data on the board. Usually, a pre-flight check is performed before each flight to ensure the overall condition of the UAV including the actuators. The actuator health deterioration is difficult to be recognized by visual inspection. This paper presents a method to detect the health of the actuator through the integration of Built-in Test System (BITE) using offline model estimation method. Least square regression estimation was performed on the healthy actuator for training data using fixed and increasing input signal. The fault is then simulated to test the training data accuracy in detecting actuator fault. An analysis is performed to show the advantage and disadvantage of each technique used. The estimation technique described was able to detect faulty actuator which could then be integrated with on-board health detection system in order to increase the reliability of the UAV. � 2017 American Scientific Publishers All rights reserved.
author2 55524079500
author_facet 55524079500
Sahwee Z.
Rahman N.A.
Sahari K.S.M.
Mahmood A.S.
format Article
author Sahwee Z.
Rahman N.A.
Sahari K.S.M.
Mahmood A.S.
spellingShingle Sahwee Z.
Rahman N.A.
Sahari K.S.M.
Mahmood A.S.
Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
author_sort Sahwee Z.
title Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
title_short Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
title_full Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
title_fullStr Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
title_full_unstemmed Health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
title_sort health estimation of servo actuator using linearized predictive time domain method to check developing fault for small unmanned aerial vehicle
publisher American Scientific Publishers
publishDate 2023
_version_ 1806428497559683072