TRANSACTIONS OF THE KRYLOV STATE RESEARCH CENTRE

Science journal

 
ISSN (print) 2542-2324 /(online) 2618-8244


Articles of The Transactions of KSRC








Prediction methods for technical condition of shipboard power machinery



Full text article ( in russian)

Year

 
2018

Issue

 
386

Volume

 
4

Pages

 
117-132

Caption

 
Prediction methods for technical condition of shipboard power machinery

Authors

 
Myasnikov Yu.N., Nikitin V.S., Ravin A.A., Khrutsky O.V.

Keywords

 
shipboard power machinery, prediction of changes in technical condition, residual lifetime assessment

DOI

 
10.24937/2542-2324-2018-4-386-117-132

Summary

 
Object and purpose of research.This paper studies power generation machinery of ships. The purpose of research is to justify information support of applying an advanced strategy of equipment maintenance based on its actual technical condition.
Subject matter and methodsInput data for this study are scientific & technical information and experimental results dealing with efficiency analysis of prediction methods and algorithms for technical condition of equipment based on monitoring of its performance parameters, as well as on diagnostics of the units that restrict its operational reliability. The study also relies on personal findings of the authors and many years of their R&D experience in improvement of maintenance strategies and operational reliability enhancement for ship equipment.
Main results.This study analyzed specifics and functional capabilities of several methods used to predict technical condition of power & mechanical equipment and assess its residual lifetime, in order to justify selection of their application areas.
Conclusion.It is shown that advanced maintenance strategy for equipment based on its actual technical condition should always rely on damage assessment of its most loaded and important units and parts, as well as on prediction of their possible changes during the forthcoming operation period. The conclusion of the whole study is that monitoring of parameters describing quality, reliability and operability of equipment at all stages of its life cycle must be performed systematically. Integrated application of technical diagnostics methods and residual lifetime assessment algorithms reduces the number of failures and optimizes equipment maintenance.

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