Picture of a sphere with binary code

Making Strathclyde research discoverable to the world...

The Strathprints institutional repository is a digital archive of University of Strathclyde research outputs. It exposes Strathclyde's world leading Open Access research to many of the world's leading resource discovery tools, and from there onto the screens of researchers around the world.

Explore Strathclyde Open Access research content

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

[img]
Preview
PDF
JJAC_RELIAB.pdf - Submitted Version

Download (840kB) | Preview

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.