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13 - Electrical and Electronic Engineering, Metallurgy and Materials

University of Strathclyde

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Output 24 of 236 in the submission

Article title

An agent-based implementation of hidden Markov models for gas turbine condition monitoring

Type

D - Journal article

DOI

10.1109/TSMC.2013.2251539

Title of journal

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Article number

Volume number

n/a

Issue number

n/a

First page of article

n/a

ISSN of journal

2168-2216

Year of publication

2013

URL

http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5326

Number of additional authors

Additional information

This paper presents an approach to dynamic monitoring of gas turbines using relatively low-frequency data. Traditional monitoring requires 10-minute averaged data for steady-state monitoring, and high-frequency vibration data for dynamic monitoring. The paper's industrial co-author [Scottish and Southern Energy (SSE), john.twiddle@sse.com] contributes a case study of data from in-service turbines, showing a successful side-by-side comparison of the new technique against SSEs current monitoring system. This work led directly to follow-on funding [SSE Research Partnership, £64.7k, 2010-2011] for researcher time to develop an online prototype system for dynamic gas turbine monitoring.

Interdisciplinary

Cross-referral requested

Research group

E - Institute for Energy and Environment (InstEE)

Proposed double-weighted

Double-weighted statement

Reserve for a double-weighted output

Non-English

English abstract