Title :
A vibration-based approach for diesel engine fault diagnosis
Author :
Chao Jin ; Wenyu Zhao ; Zongchang Liu ; Lee, Jay ; Xiao He
Author_Institution :
NSF Center for Intell. Maintenance Syst., Univ. of Cincinnati, Cincinnati, OH, USA
Abstract :
As diesel engines play a critical role in various applications, the ability for a health monitoring system to perform early fault diagnosis is of vital importance for the reliable functioning of a diesel engine throughout its service. In regard to the criticality of diesel engine fault diagnosis, an abundance of research efforts have been conducted by adopting injection-based, vibration-based, or instantaneous speed-based methods. The study presented in this paper discusses an integrated approach of diagnosing combustion faults and valve leakage, by combining vibration signal with cylinder pressure and revolution speed signals. Signal processing methods, including time frequency domain analysis such as wavelet decomposition are applied to extract features from data collected under different health conditions. The dimension of the feature set is further reduced based on discriminant analysis. Classification techniques are subsequently evaluated as fault diagnosis tools. The proposed approach is validated on a small-scale diesel engine test bed, and is to be applied in a real world health monitoring system.
Keywords :
condition monitoring; diesel engines; fault diagnosis; mechanical engineering computing; signal classification; time-frequency analysis; valves; vibrations; classification techniques; combustion faults; cylinder pressure; diesel engine fault diagnosis; discriminant analysis; fault diagnosis tools; health monitoring system; injection-based methods; instantaneous speed-based methods; research efforts; revolution speed signals; signal processing methods; small-scale diesel engine test bed; time frequency domain analysis; valve leakage; vibration signal; vibration-based approach; vibration-based methods; wavelet decomposition; Combustion; Diesel engines; Fault diagnosis; Feature extraction; Time-domain analysis; Time-frequency analysis; Vibrations; diesel engine combustion fault; fault diagnosis; feature extraction;
Conference_Titel :
Prognostics and Health Management (PHM), 2014 IEEE Conference on
Conference_Location :
Cheney, WA
DOI :
10.1109/ICPHM.2014.7036371