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http://yadda.icm.edu.pl:80/baztech/element/bwmeta1.element.baztech-article-BUJ8-0003-0006

Czasopismo

Journal of KONES

Tytuł artykułu

Attempt to utilise histogram of vibration cepstrum of engine body for setting up the clearance model of the piston-cylinder assembly for PNN neural classifier

Autorzy Madej, H.  Czech, P. 
Treść / Zawartość
Warianty tytułu
Języki publikacji EN
Abstrakty
EN The paper presents an attempt to evaluate the wear of piston-cylinder assembly with the aid of vibration signal recorded on spark ignition (SI) engine body. The subject of the study was a four-cylinder combustion engine 1.2 dm3. Diagnosing combustion engines with vibration methods is specifically difficult due to the presence of multiple sources of vibration interfering with the symptoms of damages. Diagnosing engines with vibroacustic methods is difficult also due to the necessity to analyse non-stationary and transient signals [5]. Various methods for selection of usable signal are utilised in the diagnosing process. Changes of the engine technical condition resulting from early stages of wear are difficult to detect for the effect of mechanical defect masking by adaptive engine control systems [3]. According to the studies carried out, it is possible to utilise artificial neural networks for the evaluation of the clearance in piston-cylinder assembly. It was proven that it is possible to set up a properly operating neural classifier able to identify the degree of wear in the piston-cylinder assembly, based on the signal of vibration acceleration in the engine body. Faultless classification was successfully obtained with the use of probabilistic neural network with properly selected value of y coefficient. At the same time, based on the experiments carried out, the crucial role was confirmed for the selection of proper method for pre-treatment of data intended for neural network teaching.
Słowa kluczowe
EN diagnostics   combustion engines   artificial neural networks   vibration  
Wydawca Institute of Aviation
Czasopismo Journal of KONES
Rocznik 2008
Tom Vol. 15, No. 3
Strony 305--311
Opis fizyczny Bibliogr. 11 poz., rys.
Twórcy
autor Madej, H.
autor Czech, P.
  • Silesian University of Technology, Faculty of Transport Krasińskiego Street 8, 40-019 Katowice, Poland tel.: +48 32 6034107, fax: +48 32 6034108, henryk.madej@polsl.pl
Bibliografia
[1] Cempel, C., Vibro-accoustic diagnostics of machines, Pastwowe Wydawnictwo Naukowe, Warsaw 1989.
[2] Czech, P., Łazarz, B., Wojnar, G., Detection of local defects of gear teeth using artificial neural networks and genetic algorithms, Wydawnictwo ITE, Radom 2007.
[3] Dąbrowski, Z., Madej, H., Masking mechanical damages in the modern control systems of combustion engines, Journal of KONES, Vol. 13, No 3/2006.
[4] Gately, E., Neural networks. Financial forecasting and designing transaction systems, WIGPress, Warsaw 1999.
[5] Heywood, J. B., Internal combustion engines fundamentals, McGraw Hill Inc 1988.
[6] Isermann, R., Diagnosis methods for electronic controlled vehicles, Vehicle System Dynamics, Vol. 36, No. 2-3.
[7] Korbicz, J., Kościelny, J., Kowalczuk, Z., Cholewa, W., (collective work), Process diagnostics. Models, Methods for artificial intelligence, Applications, Wydawnictwa Naukowo-Techniczne, Warsaw 2002.
[8] Osowski, St., Neural networks for information processing, Oficyna Wydawnicza Politechniki Warszawskiej, Warsaw 2000.
[9] Tadeusiewicz, R., Neural networks, Akademicka Oficyna Wydawnicza, Warsaw 1993.
[10] Tadeusiewicz, R., Lula, P., Introductin to neural networks, StatSoft, Krakow 2001.
[11] Żółtowski, B., Cempel, C. (collective work), Machine diagnostics engineering, Biblioteka Problemów Eksploatacyjnych, Polskie Towarzystwo Diagnostyki Technicznej, Instytut Technologii Eksploatacji PIB Radom, Warszawa-Bydgoszcz-Radom 2004.
Kolekcja BazTech
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