Fuel Injection Fault Detection in a Diesel Engine Based on Vibration Signature Analysis

This paper presents a condition monitoring and fuel injection fault detection technique for a 12-cylinder 588 kW trainset diesel engine based on vibration signature analysis using Fast Fourier Transform (FFT). These type of engines are considered to be heart of passenger trainsets and their condition monitoring is crucial for reliable performance of the system. Most of the conventional fault diagnosis techniques in diesel engines are mainly based on analyzing the difference of vibration signals amplitude in time domain. In the present study, vibration signals were captured from both intake manifold and cylinder heads of the engine and were analyzed in time and frequency domains. In addition, experimental data of a 12-cylinder 588 kW diesel engine (of a trainset) are captured and the proposed method is verified via these data. Results show that power spectra of vibration signals in the low frequency range reliably distinguish between normal and faulty conditions. The experimental results verified that vibration signals acquired from intake manifold have more potential in fault detection.

Keywords:

Fault detection , Condition monitoring , Vibration signal , Trainset diesel engine