A Novel Method of Impeller Blade Monitoring Using Shaft Vibration Signal Processing.

algorithm diagnostics impeller blade monitoring signal processing steam turbine vibration

Journal

Sensors (Basel, Switzerland)
ISSN: 1424-8220
Titre abrégé: Sensors (Basel)
Pays: Switzerland
ID NLM: 101204366

Informations de publication

Date de publication:
29 Jun 2022
Historique:
received: 13 05 2022
revised: 26 06 2022
accepted: 28 06 2022
entrez: 9 7 2022
pubmed: 10 7 2022
medline: 14 7 2022
Statut: epublish

Résumé

The monitoring of impeller blade vibrations is an important task in the diagnosis of turbomachinery, especially in terms of steam turbines. Early detection of potential faults is the key to avoid the risk of turbine unexpected outages and to minimize profit loss. One of the ways to achieve this is long-term monitoring. However, existing monitoring systems for impeller blade long-term monitoring are quite expensive and also require special sensors to be installed. It is even common that the impeller blades are not monitored at all. In recent years, the authors of this paper developed a new method of impeller blade monitoring that is based on relative shaft vibration signal measurement and analysis. In this case, sensors that are already standardly installed in the bearing pedestal are used. This is a significant change in the accessibility of blade monitoring for a steam turbine operator in terms of expenditures. This article describes the developed algorithm for the relative shaft vibration signal analysis that is designed to run in a long-term perspective as a part of a remote monitoring system to track the natural blade frequency and its amplitude automatically.

Identifiants

pubmed: 35808417
pii: s22134932
doi: 10.3390/s22134932
pmc: PMC9269731
pii:
doi:

Substances chimiques

Steam 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : ERDF
ID : CZ.02.1.01/0.0/0.0/16_026/0008389

Auteurs

Jindrich Liska (J)

NTIS-New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 301 00 Plzen, Czech Republic.

Vojtech Vasicek (V)

NTIS-New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 301 00 Plzen, Czech Republic.

Jan Jakl (J)

NTIS-New Technologies for the Information Society, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 301 00 Plzen, Czech Republic.

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Classifications MeSH