A Novel Time–Frequency Feature Fusion Approach for Robust Fault Detection in a Marine Main Engine

A Novel Time–Frequency Feature Fusion Approach for Robust Fault Detection in a Marine Main Engine

Ensuring operational reliability in machinery requires accurate fault detection. While time-domain vibration pulsation signals are intuitive for pattern recognition and feature extraction, downsampling can reduce analytical complexity, but may result in low-precision data, affecting fault detection...

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Bibliographic Details
Main Authors: Hong Je-Gal, Seung-Jin Lee, Jeong-Hyun Yoon, Hyun-Suk Lee, Jung-Hee Yang, Sewon Kim
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Journal of Marine Science and Engineering
Subjects:
fault detection
marine main engine
deep neural network
predictive maintenance
time–frequency feature fusion
Online Access:https://www.mdpi.com/2077-1312/11/8/1577

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