<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>As an important component of the fuel injection system, the fuel injector is crucial for ensuring the power, economy, and emissions for a whole ME (machine electronically-controlled) marine diesel engine. However, injectors are most prone to failures such as reduced pressure at the opening valve, clogged spray holes and worn needle valves, because of the harsh working conditions. The failure characteristics are non-stationary and non-linear. Therefore, to efficiently extract fault features, an improved refined composite multi-scale dispersion entropy (IRCMDE) is proposed, which uses the energy distribution of sampling points as weights for coarse-grained calculation, then fast correlation-based filter(FCBF) and support vector machine (SVM) are used for feature selection and fault classification, respectively. The experimental results from a MAN B&amp;W 6S35ME-B9 marine diesel engine show that the proposed algorithm can achieve 92.12% fault accuracy for injector faults, which is higher than multiscale dispersion entropy (MDE), refined composite multiscale dispersion entropy (RCMDE) and multiscale permutation entropy (MPE). Moreover, the experiment has also proved that, due to the double-walled structure of the high-pressure fuel pipe, the fuel injection pressure signal is more accurate than the vibration signal in reflecting the injector operating conditions.</p>
</abstract>

As an important component of the fuel injection system, the fuel injector is crucial for ensuring the power, economy, and emissions for a whole ME (machine electronically-controlled) marine diesel engine. However, injectors are most prone to failures such as reduced pressure at the opening valve, clogged spray holes and worn needle valves, because of the harsh working conditions. The failure characteristics are non-stationary and non-linear. Therefore, to efficiently extract fault features, an improved refined composite multi-scale dispersion entropy (IRCMDE) is proposed, which uses the energy distribution of sampling points as weights for coarse-grained calculation, then fast correlation-based filter(FCBF) and support vector machine (SVM) are used for feature selection and fault classification, respectively. The experimental results from a MAN B&W 6S35ME-B9 marine diesel engine show that the proposed algorithm can achieve 92.12% fault accuracy for injector faults, which is higher than multiscale dispersion entropy (MDE), refined composite multiscale dispersion entropy (RCMDE) and multiscale permutation entropy (MPE). Moreover, the experiment has also proved that, due to the double-walled structure of the high-pressure fuel pipe, the fuel injection pressure signal is more accurate than the vibration signal in reflecting the injector operating conditions.

Fault Diagnosis of ME Marine Diesel Engine Fuel Injector with Novel IRCMDE Method

Polish Maritime Research

This work is licensed under the Creative Commons Attribution 4.0 International License.

As an important component of the fuel injection system, the fuel injector is crucial for ensuring the power, economy, and emissions for a whole ME (machine...

Fault Diagnosis of ME Marine Diesel Engine Fuel Injector with Novel IRCMDE Method

Online veröffentlicht: 10. Okt. 2023

Seitenbereich: 96 - 110

DOI: https://doi.org/10.2478/pomr-2023-0043

Schlüsselwörter
marine diesel engine, fuel injector, improved refined composite multi-scale dispersion entropy, fault diagnosis

© 2023 Qingguo Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fault Diagnosis of ME Marine Diesel Engine Fuel Injector with Novel IRCMDE Method

Online veröffentlicht: 10. Okt. 2023

Seitenbereich: 96 - 110

DOI: https://doi.org/10.2478/pomr-2023-0043

Schlüsselwörtermarine diesel engine, fuel injector, improved refined composite multi-scale dispersion entropy, fault diagnosis

© 2023 Qingguo Shi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
marine diesel engine, fuel injector, improved refined composite multi-scale dispersion entropy, fault diagnosis