Self-tuning routine alarm analysis of vibration signals in steam turbine generators

Costello, Jason and West, Graeme and McArthur, Stephen and Campbell, Graeme (2012) Self-tuning routine alarm analysis of vibration signals in steam turbine generators. IEEE Transactions on Reliability, 61 (3). pp. 731-740. ISSN 0018-9529 (https://doi.org/10.1109/TR.2012.2209257)

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Abstract

This paper presents a self-tuning framework for knowledge-based diagnosis of routine alarms in steam turbine generators. The techniques provide a novel basis for initialising and updating time series feature extraction parameters used in the automated decision support of vibration events due to operational transients. The data-driven nature of the algorithms allows for machine specific characteristics of individual turbines to be learned and reasoned about. The paper provides a case study illustrating the routine alarm paradigm and the applicability of systems using such techniques.

ORCID iDs

Costello, Jason ORCID: https://orcid.org/0000-0002-9935-7549

West, Graeme ORCID: https://orcid.org/0000-0003-0884-6070

McArthur, Stephen ORCID: https://orcid.org/0000-0003-1312-8874

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• Item metadata

  Item type:	Article
  ID code:	41099
  Dates:	Date Event September 2012 Published
  Subjects:	Technology > Electrical engineering. Electronics Nuclear engineering
  Department:	Faculty of Engineering > Electronic and Electrical Engineering
  Depositing user:	Pure Administrator
  Date deposited:	12 Sep 2012 08:57
  Last modified:	11 Nov 2024 10:06
  URI:	https://strathprints.strath.ac.uk/id/eprint/41099