Nuclear Reactor Heat Transfer Pump Rotordynamic Based Diagnostics and Field Data Model Reconciliation View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Juan Hidalgo , Ronald J. O’Brien

ABSTRACT

This paper presents a systematic methodology to diagnose of real life problems thru a combination of traditional vibration analysis and rotordynamic modeling. Additionally, also presents a consistent approach to find reliable solutions and validate them. It addresses the diagnostic of one of four Nuclear Reactor Primary Heat Transfer Pump (PHT) that has been experiencing abnormal vibration over the years. The implemented methodology to diagnostic the high vibrations in the PHT pump is based in a hybrid between measurements and modeling. The first step has been the measurement of vibrations level in the PHT pump when the reactor was in the detention process, which was the only opportunity because the pumps are isolated from the human access when the reactor is operative. In a second step, with the obtained measurement, was developed the FEA (Finite Element Analysis) model in a healthy condition using a proprietary finite element rotordynamic tool named “Heron”. Which is rotordynamic analysis software developed to model and diagnose rotating equipment. At last step, the healthy model was used to implement different kind of failure to reproduce the vibration condition measurement in the PHT pump with high level of vibration. The match between the model with failure and measurement of the PHT pump with high vibrations allows take a diagnostic of the pump. The presented case is an excellent example for the proposed approach due to the difficulty of accessing the pump in operation for measurement and need of a high level of confidence on its solution. More... »

PAGES

18-31

Book

TITLE

Proceedings of the 10th International Conference on Rotor Dynamics – IFToMM

ISBN

978-3-319-99267-9
978-3-319-99268-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-99268-6_2

DOI

http://dx.doi.org/10.1007/978-3-319-99268-6_2

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1106224172


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