Intelligent Diagnosis for Fuel Line Fault of Diesel Engine Based on Vibration Signatures

Sie sind hier: Homepage > Suche

Intelligent Diagnosis for Fuel Line Fault of Diesel Engine Based on Vibration Signatures

Mandke, Devendra / Dharmadhikari, Nitin / Chaudhari, Parag / Gangsar, Purushottam / Pawar, Sachin

Early fault detection is vital in maintaining system stability and to decrease the cost associated with maintenance. This paper presents an approach to identify the fuel line failure for a diesel engine based on vibration signals and machine learning. Vibration measurements are performed on the fuel line of the engine for both normal and faulty conditions for engine ramp up condition. After acquiring the time domain vibration signals, various features were extracted and have been analyzed in time and time-frequency domains. Based on the most effective feature, a machine learning model (i.e., support vector machine (SVM)) for fault diagnosis is developed. Results showed that the proposed SVM based model can detect the fuel line fault correctly. This study can be useful for early detection of this critical fault in diesel engine and take useful decision before any catastrophic failure happens because of this fault.

Zugriff

Zugriff prüfen

Verfügbarkeit in meiner Bibliothek prüfen

Bestellung bei Subito €

Exportieren, teilen und zitieren

Dokumentinformationen

Titel :

Intelligent Diagnosis for Fuel Line Fault of Diesel Engine Based on Vibration Signatures

Weitere Titelangaben:

Sae Technical Papers

Beteiligte:

Mandke, Devendra (Autor:in) / Dharmadhikari, Nitin (Autor:in) / Chaudhari, Parag (Autor:in) / Gangsar, Purushottam (Autor:in) / Pawar, Sachin (Autor:in)

Kongress:

Symposium on International Automotive Technology ; 2024

Erschienen in:

Sae Technical Paper Series

Erscheinungsdatum :

2024-01-16

ISSN :

2688-3627 , 0148-7191

DOI :

https://doi.org/10.4271/2024-26-0221

Medientyp :

Aufsatz (Konferenz)