A Maintenance Alarm for Alternators Based on Eigensolutions

  • Antoine Kuczkowiak
  • Scott Cogan
  • Morvan Ouisse
  • Emmanuel Foltête
  • Mathieu Corus
Conference paper

Abstract

The complex structural dynamic behaviour of turbo-alternators and their sub-assemblies must be well understood in order to insure their reliable and safe operation. In practice, important variations in response behaviours are observed in a population of otherwise nominally identical installations due to numerous and significant sources of variability: construction differences, manufacturing and assembly tolerances, variable thermal and nonlinear effects, and so on. These physical variations can sometimes lead to unexpectedly high response levels in the stator and a decision indicator is sought to signal the need for special maintenance procedures. Ideally, measurements in operation would be performed to obtain the necessary information but, for technical reasons, this is not currently possible. Meanwhile, the machines are generally disassembled for standard maintenance every five years. In this article, a maintenance alarm is formulated based on modal tests performed on the stator with the rotor removed. The objective is to usefully bound the stator response in operation based on the identified eigensolutions obtained on the stator alone. However, it is known that thermal and nonlinear mechanical effects of the functioning alternator modify the associated eigenparameters. Since these effects are not well known, an info-gap robustness analysis is performed to investigate the impact of this lack of knowledge on the response levels of interest. A stator assembly must be able to tolerate reasonable levels of uncertainty without exceeding a critical response level or it will require maintenance and repair. The proposed methodology is illustrated on a simplified numerical model of a stator.

Keywords

Modal Basis Response Level Structural Health Monitoring Robustness Analysis Assembly Tolerance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Antoine Kuczkowiak
    • 1
    • 2
  • Scott Cogan
    • 1
  • Morvan Ouisse
    • 1
  • Emmanuel Foltête
    • 1
  • Mathieu Corus
    • 2
  1. 1.Applied Mechanics DepartmentFEMTO-ST InstituteBesançonFrance
  2. 2.Department of Mechanic and Acoustic AnalysisÉlectricité de France R&DClamartFrance

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