Loughborough University
Leicestershire, UK
LE11 3TU
+44 (0)1509 263171
Loughborough University

Loughborough University Institutional Repository

Please use this identifier to cite or link to this item: https://dspace.lboro.ac.uk/2134/33916

Title: Reduction of impacts of oil and gas operations through intelligent maintenance solution
Authors: Eyoh, Jeremiah
Kalawsky, Roy S.
Keywords: Exhaust gas temperature
Gas flaring
Gas turbine engine
Incipient fault
Intelligent maintenance
Multi-class classification
Neural network
Oil and gas
Reliability
Thermocouple sensors
Issue Date: 2018
Publisher: © Association for Computing Machinery (ACM)
Citation: EYOH, J. and KALAWSKY, R.S., 2018. Reduction of impacts of oil and gas operations through intelligent maintenance solution. IN: Proceedings of the International Conference on Intelligent Science and Technology (ICIST 2018), London, UK, 30 June-2 July 2018, pp.67-71.
Abstract: Impacts of oil and gas production operations are always very obvious when there is imbalanced operation, uncontrolled stoppage or catastrophic failure of the system during normal operations. These impacts may range from high flaring and venting of associated petroleum gas, oil release or spillage, equipment damage, fire outbreak to even fatality. Possible causes of imbalanced operations or system failure are categorised into process upset, system degradation, ineffective operation and maintenance procedures and human errors. Effective maintenance strategy integrates major components of the system; people (human factors), operation and maintenance procedures (process) and production plant (technology) to develop an intelligent maintenance solution that is capable of monitoring and detecting fault in the system at incipient stage before operational integrity is compromised. This paper deploys data-based analytics technique to develop condition-based predictive maintenance system to monitor, predict and classify performance of gas processing system. Exhaust gas temperature (EGT) of Gas Turbine Engine (GTE) is one of the operating and control parameters associated with efficiency of the GTE operation. The EGT is measured using several thermocouples, temperature sensors spaced equidistant around the circumference of the exhaust duct of the GTE. Neural network technique of multisensory data fusion is integrated with intelligent maintenance system to monitor performance of GTE, detect fault and classify performance of GTE to optimal, average and abnormal performance.
Description: © ACM 2018. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in ICIST '18 Proceedings of the International Conference on Intelligent Science and Technology, http://dx.doi.org/10.1145/3233740.3233747.
Version: Accepted for publication
DOI: 10.1145/3233740.3233747
URI: https://dspace.lboro.ac.uk/2134/33916
Publisher Link: https://doi.org/10.1145/3233740.3233747
ISBN: 9781450364614
Appears in Collections:Conference Papers and Presentations (Mechanical, Electrical and Manufacturing Engineering)

Files associated with this item:

File Description SizeFormat
Reduction of impacts of oil and gas operations through intelligent maintenance solution - ICSMET 2018 - Eyoh JE - LU.pdfAccepted version750.22 kBAdobe PDFView/Open

 

SFX Query

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.