Recognition of combustion process irregularities in small volume displacement diesel engines with the use of non-dimensional characteristics of the vibration signal
 
More details
Hide details
1
Faculty of Machines and Transport at Poznan University of Technology.
Publication date: 2017-05-01
 
Combustion Engines 2017,169(2), 18–23
 
KEYWORDS
ABSTRACT
The subject of the considerations described in the paper is the problem of early detection of abnormalities and damages during operation process of the turbo diesel engine with small volume displacement and direct fuel injection, which is used in modern LDV vehicles dedicated especially for urban areas, in the context of present and future requirements for a technical object diagnostics, taking into account the criteria of optimizing overall efficiency, toxic compound emission and safety of the object in real conditions of its operation. The paper presents the results of empirical research of vibroacoustic signal application to the diagnostic evaluation of correctness of short-time engine main processes. The evaluation of the combustion process variability from structural and operational abnormalities by using dimensionless estimates of a vibration process was conducted, and functional characteristics necessary to built the diagnostic algorithm in accordance with the requirements of on-board diagnostics were obtained.
 
REFERENCES (21)
1.
BARTELMUS, W., ZIMROZ, R. A new feature for monitoring the condition of gear- boxes in nonstationary operating conditions. Mechanical Systems and Signal Processing. 2009, 23, 1528-1534.
 
2.
CEMPEL, C. Vibroacoustic machines diagnostics. National Scientific Publishing Houses, Warsaw 1989.
 
3.
CZECH, P., ŁAZARZ, B., WOJNAR, G. Detection of local gears of gear wheel gear using artificial neural networks and genetic algorithms. ITE, 2007, Radom.
 
4.
CZECH, P., MADEJ, H. Application of cepstrum and spectrum histograms of vibration engine body for setting up the.
 
5.
clearance model of the piston-cylinder assembly for RBF neural classifier. Maintenance and Reliability. 2011, 4, 15-20.
 
6.
CZECH, P., WOJNAR, G., FOLĘGA, P. Vibroacoustic diagnosing of disturbances in the car ignition system by amplitude estimates. Scientific Journals of Silesian University of Technology. Series: Transport. 2014, 83, 1904, 59-64.
 
7.
DESBAZEILLE, M., RANDALL, R.B., GUILLET, F. et al. Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft. Mechanical Systems and Signal Processing. 2010, 5, 1529-1541.
 
8.
FIGLUS, T. Diagnosing the engine valve clearance, on the basis of the energy changes of the vibratory signal. Maintenance Problems. 2009, 1, 75-84.
 
9.
KORBICZ, J., KOŚCIELNY, J. Modeling, diagnostics, and mastering processes. DiaSter implementation. Scientific and Technical Publishing House. Warsaw 2010.
 
10.
KORBICZ, J., KOŚCIELNY, J.M., KOWALCZUK, Z., CHOLEWA, W. Process diagnostics. Science and Technology Publishing House. 2002, 3.
 
11.
MADEJ, H., CZECH, P. Discrete wavelet transform and probabilistic neural network in IC engine fault diagnosis.
 
12.
Maintenance and Reliability. 2010, 4, 47-54.
 
13.
MERKISZ, J., JACYNA, M., MERKISZ-GURANOWSKA, A., PIELECHA, J. The parameters of passenger cars engine in terms of real drive emission test. Archives of Transport. 2014,. 32(4), 43-50.
 
14.
PUŠKÁR, M., BIGOŠ, P., PUŠKÁROVÁ, P. Accurate measurements of output characteristics and detonations of motorbike high-speed racing engine and their optimization at actual atmospheric conditions and combusted mixture composition. Measurement. 2012, 45, 1067-1076.
 
15.
QINGHUA, W., YOUYUN, Z., LEI, C., YONG-SHENG, Z. Fault diagnosis for diesel valve trains based on nonnegative matrix factorization and neural network ensemble. Mechanical Systems and Signal Processing. 2009, 23, 1683-1695.
 
16.
SZYMAŃSKI, G.M., TOMASZEWSKI, F. Application of impact tests to diagnose internal combustion engines. Proceedings of the 17th International Congress on Sound and Vibration. 2010, 2, 1282-1289.
 
17.
Brüel & Kjær, www.bksv.com.
 
19.
Springer Fachmedien Wiesbaden GmbH, www.springerprofessional.de.
 
20.
YADAV, S.K., KALRA, P.K. Fault diagnosis of internal combustion engine using empirical mode decomposition. Proceedings of the IEEE 6th International Symposium on Image and Signal Processing and Analysis. ISPA 2009, 40-46.
 
21.
YILDIRIM, H., ÇINAR, A., SAYLI, O., KOYLU, H. Vibration and noise analysis of an engine fuelled with diesel and biodiesel blends. ICAME’15: International Conference on Advances in Mechanical Engineering. 13th–15th May 2015, Istambul.
 
eISSN:2658-1442
ISSN:2300-9896