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Analysis and prediction of vibro-acoustic characteristics of parallel propulsion systems for large-scale marine ships

  • Jianghai Xu
  • , Xueliang Liu
  • , Zhongliang Xie
  • , Chunxiao Jiao
  • , Na Ta
  • , Zhushi Rao
  • Nanjing University of Science and Technology
  • Shanghai Jiao Tong University
  • Tianjin Navigation Instruments Research Institute

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

The parallel power propulsion system is the preferred option for large-scale ships. The improper configuration of multidimensional power parameters is a significant factor contributing to the vibration and noise generated by the system. This study examines the sensitivity and dependence of the vibro-acoustic characteristics of the system on various power parameters through theoretical and experimental methods, and reveals the evolution mechanism of the dynamic behaviors under the coupling effect of multidimensional power parameters. Firstly, the nonlinear dynamic model considering the lateral–torsional–axial coupling of the propulsion system is established and the effects of different combinations of power parameters on the vibration response and system stability are investigated. Secondly, an experimental platform of the parallel propulsion system is constructed, and the comprehensive description of the effects of multidimensional power parameters on the vibration and noise of the system under asymmetrical input power is further provided. Finally, the radial basis function (RBF) neural network is innovatively employed to predict and approximate the vibro-acoustic characteristics of the system under the combined influence of rotating speed, torque ratio, and drag current. The research results are of significant theoretical and practical importance in breaking through the technical bottleneck related to reducing the vibration and noise of such parallel propulsion systems.

Original languageEnglish
Article number103863
JournalApplied Ocean Research
Volume143
DOIs
StatePublished - Feb 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

Keywords

  • Multidimensional power parameters
  • Parallel propulsion system
  • RBF neural network
  • Time-vary and nonlinear system
  • Vibro-acoustic characteristics

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