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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

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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.

Item type: Article
ID code: 41099
Keywords: knowledge based systems, nuclear power generation, self-tuning, time series analysis, Electrical engineering. Electronics Nuclear engineering, Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality
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: 24 Jul 2015 12:35

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