Cover Image

Soft redundant instrument for metering station in gas transportation system

This study focuses on the development of a soft redundant instrument to replace secondary hard instrument for saving cost of installation. The model of the soft redundant instrument implements an artificial neural network (ANN) approach; providing the alternative for secondary measurement. Moreover,...

Full description

Saved in:
Bibliographic Details
Main Authors: Rosli, N.S., Ibrahim, R., Ismail, I.
Format: Conference or Workshop Item
Published: Institute of Electrical and Electronics Engineers Inc. 2015
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957673286&doi=10.1109%2fASCC.2015.7244536&partnerID=40&md5=6c48519fe586ffdfea1b6624c2724766
http://eprints.utp.edu.my/26214/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.26214
record_format eprints
spelling my.utp.eprints.262142021-08-30T08:54:29Z Soft redundant instrument for metering station in gas transportation system Rosli, N.S. Ibrahim, R. Ismail, I. This study focuses on the development of a soft redundant instrument to replace secondary hard instrument for saving cost of installation. The model of the soft redundant instrument implements an artificial neural network (ANN) approach; providing the alternative for secondary measurement. Moreover, the reliability and quality of the metering station play a crucial part in the gas transportation system as it affects the billing integrity between the gas supplier and their customers. In this work, the problem with a primary instrument was analysed to diagnose the faulty condition of measurement in metering station. Accordingly, different ANN algorithms were investigated and compared to select a prediction model that provides the best performance. This suggested prediction technique can be considered as an additional verification system to be compared to the hard instrument that is installed on the pipeline. Hence, in order to determine accuracy in the rate of measurement from the proposed model, it is required that variation in measurement between hard and soft instrument should not exceed 1. Based on this model, the ANN prediction model is able to reconstruct the unreliable data during faulty instrument. © 2015 IEEE. Institute of Electrical and Electronics Engineers Inc. 2015 Conference or Workshop Item NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957673286&doi=10.1109%2fASCC.2015.7244536&partnerID=40&md5=6c48519fe586ffdfea1b6624c2724766 Rosli, N.S. and Ibrahim, R. and Ismail, I. (2015) Soft redundant instrument for metering station in gas transportation system. In: UNSPECIFIED. http://eprints.utp.edu.my/26214/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description This study focuses on the development of a soft redundant instrument to replace secondary hard instrument for saving cost of installation. The model of the soft redundant instrument implements an artificial neural network (ANN) approach; providing the alternative for secondary measurement. Moreover, the reliability and quality of the metering station play a crucial part in the gas transportation system as it affects the billing integrity between the gas supplier and their customers. In this work, the problem with a primary instrument was analysed to diagnose the faulty condition of measurement in metering station. Accordingly, different ANN algorithms were investigated and compared to select a prediction model that provides the best performance. This suggested prediction technique can be considered as an additional verification system to be compared to the hard instrument that is installed on the pipeline. Hence, in order to determine accuracy in the rate of measurement from the proposed model, it is required that variation in measurement between hard and soft instrument should not exceed 1. Based on this model, the ANN prediction model is able to reconstruct the unreliable data during faulty instrument. © 2015 IEEE.
format Conference or Workshop Item
author Rosli, N.S.
Ibrahim, R.
Ismail, I.
spellingShingle Rosli, N.S.
Ibrahim, R.
Ismail, I.
Soft redundant instrument for metering station in gas transportation system
author_facet Rosli, N.S.
Ibrahim, R.
Ismail, I.
author_sort Rosli, N.S.
title Soft redundant instrument for metering station in gas transportation system
title_short Soft redundant instrument for metering station in gas transportation system
title_full Soft redundant instrument for metering station in gas transportation system
title_fullStr Soft redundant instrument for metering station in gas transportation system
title_full_unstemmed Soft redundant instrument for metering station in gas transportation system
title_sort soft redundant instrument for metering station in gas transportation system
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2015
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957673286&doi=10.1109%2fASCC.2015.7244536&partnerID=40&md5=6c48519fe586ffdfea1b6624c2724766
http://eprints.utp.edu.my/26214/
_version_ 1738656839934935040
score 13.211869

Similar Items