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Impact of the Temperature Sensor Malfunction on Diesel Engine Noise Emissions

  • 2025
  • OriginalPaper
  • Chapter
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Abstract

This study delves into the impact of temperature sensor malfunctions on diesel engine noise emissions, utilizing acoustic signal analysis and statistical parameters for early fault detection. The research methodology involves adjusting the coolant temperature sensor to simulate a fault and measuring the resulting engine noise at various speeds. Key findings include significant deviations in noise emissions when the temperature sensor fails, with higher noise levels observed at increased engine speeds. The study validates the use of acoustic metrics such as RMS, standard deviation, and kurtosis in identifying sensor faults. Additionally, it explores how these statistical measures vary with engine speed, providing insights into the nonlinearity of sensor fault impacts. The conclusion emphasizes the efficacy of acoustic analysis in predictive maintenance, offering a non-intrusive method for early fault detection. This approach not only enhances engine performance but also reduces maintenance costs and extends engine life. The research suggests future directions, including the application of machine learning algorithms for higher accuracy in fault classification and the potential use of this technique with other major engine sensors.

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Title
Impact of the Temperature Sensor Malfunction on Diesel Engine Noise Emissions
Authors
Ines Belkacem
Ali Helali
Raslen Nemer
Ayoub Missaoui
Copyright Year
2025
DOI
https://doi.org/10.1007/978-3-032-04742-7_57
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