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Design and Application of a Fault Detection Method Based on Adaptive Filters and Rotational Speed Estimation for an Electro-Hydrostatic Actuator
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Spectral-Based Fault Detection Method in Marine Diesel Engine Operation.

Joško Radić1, Matko Šarić1, Ante Rubić1

  • 1Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split, University of Split, 21000 Split, Croatia.

Sensors (Basel, Switzerland)
|September 27, 2025
PubMed
Summary

This study introduces a novel method for detecting marine diesel engine malfunctions using acoustic and vibration signals. The approach achieves high accuracy, simplifying implementation for autonomous vessel development.

Keywords:
accelerometeracoustical microphonediesel enginefault detection

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Area of Science:

  • Marine engineering
  • Signal processing
  • Condition monitoring

Background:

  • Autonomous vessels are gaining interest, with diesel engines being common.
  • Detecting engine malfunctions is crucial for vessel reliability and safety.
  • Current methods may lack efficiency or require complex implementation.

Purpose of the Study:

  • To develop and validate a method for detecting marine diesel engine malfunctions.
  • To utilize acoustic and vibration signals for fault detection.
  • To simplify the implementation of engine malfunction detection systems.

Main Methods:

  • Signal analysis in the frequency domain using Discrete Fourier Transform (DFT).
  • Simultaneous analysis of acoustic data from microphones and vibration data from accelerometers.
  • Testing on a six-cylinder marine diesel engine with an emulated single-cylinder fault.

Main Results:

  • Achieved approximately 98.3% accuracy in detecting engine malfunctions under controlled conditions.
  • Demonstrated high average precision (>97%) and recall (>96%) across all sensors.
  • The method showed consistent performance across five different rotational speeds.

Conclusions:

  • The proposed signal analysis method effectively detects marine diesel engine malfunctions.
  • Identical processing of acoustic and vibration data simplifies system implementation.
  • Potential for enhanced detection accuracy through the integration of additional sensors.