Time series method for machine performance prediction using condition monitoring data

Accurate machine performance prediction is crucial to an effective maintenance strategy for improved reliability and to reduce total maintenance cost. In this study, a time series neural network based approach is introduced to achieve more accurate and reliable performance prediction of machine usin...

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Main Authors: Sarwar, U., Muhammad, M.B., Abdul Karim, Z.A.
Format: Conference or Workshop Item
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.31131 /
Published: Institute of Electrical and Electronics Engineers Inc. 2014
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925939871&doi=10.1109%2fI4CT.2014.6914212&partnerID=40&md5=746192e3b5d5801e5dee008f452deb03
http://eprints.utp.edu.my/31131/
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id utp-eprints.31131
recordtype eprints
spelling utp-eprints.311312022-03-25T09:00:30Z Time series method for machine performance prediction using condition monitoring data Sarwar, U. Muhammad, M.B. Abdul Karim, Z.A. Accurate machine performance prediction is crucial to an effective maintenance strategy for improved reliability and to reduce total maintenance cost. In this study, a time series neural network based approach is introduced to achieve more accurate and reliable performance prediction of machine using condition monitoring data source. The proposed time series model utilizes the various measured condition monitoring data at the current and previous inspection marks as the inputs, and the machine output performance as the targets for the model. To validate the model, it considers a two-shaft industrial gas turbine as a case study. The collected condition monitoring data are used to train and validate the proposed model. Results showed that the proposed time series method could predict the performance of the gas turbine power output with more accuracy and better results. © 2014 IEEE. Institute of Electrical and Electronics Engineers Inc. 2014 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925939871&doi=10.1109%2fI4CT.2014.6914212&partnerID=40&md5=746192e3b5d5801e5dee008f452deb03 Sarwar, U. and Muhammad, M.B. and Abdul Karim, Z.A. (2014) Time series method for machine performance prediction using condition monitoring data. In: UNSPECIFIED. http://eprints.utp.edu.my/31131/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Accurate machine performance prediction is crucial to an effective maintenance strategy for improved reliability and to reduce total maintenance cost. In this study, a time series neural network based approach is introduced to achieve more accurate and reliable performance prediction of machine using condition monitoring data source. The proposed time series model utilizes the various measured condition monitoring data at the current and previous inspection marks as the inputs, and the machine output performance as the targets for the model. To validate the model, it considers a two-shaft industrial gas turbine as a case study. The collected condition monitoring data are used to train and validate the proposed model. Results showed that the proposed time series method could predict the performance of the gas turbine power output with more accuracy and better results. © 2014 IEEE.
format Conference or Workshop Item
author Sarwar, U.
Muhammad, M.B.
Abdul Karim, Z.A.
spellingShingle Sarwar, U.
Muhammad, M.B.
Abdul Karim, Z.A.
Time series method for machine performance prediction using condition monitoring data
author_sort Sarwar, U.
title Time series method for machine performance prediction using condition monitoring data
title_short Time series method for machine performance prediction using condition monitoring data
title_full Time series method for machine performance prediction using condition monitoring data
title_fullStr Time series method for machine performance prediction using condition monitoring data
title_full_unstemmed Time series method for machine performance prediction using condition monitoring data
title_sort time series method for machine performance prediction using condition monitoring data
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2014
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84925939871&doi=10.1109%2fI4CT.2014.6914212&partnerID=40&md5=746192e3b5d5801e5dee008f452deb03
http://eprints.utp.edu.my/31131/
_version_ 1741197523851149312
score 11.62408

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