Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring

Dimitrios Moshou; Athanasios Natsıs; Dimitrios Katerıs; İoannis Gravalos; Nader Sawalhı; İoannis Kalımanıs; Spyridon Loutrıdıs; Theodoros Gıalamas; Panayiotis Xyradakıs; Zisis Tsıropoulos

Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring

Öz

A tractor gearbox test rig has been used to collect signals from different types of bearing faults. For vibration monitoring accelerometers have been used to obtain vibtation data. For fuel injectors a Bearing Checker has been used in order to collect acoustic data. Least squares support vector machines (LS-SVM) are used for detecting faults when exposed to actual data from the system representing a yet unknown state. Feature extraction was performed using seven features. The feature vectors are then fed to the LS-SVM for training. LS-SVM classification gave promising results (more than 95% correct classification). The fusion of features from both the vertical and the horizontal accelerometer resulted in more accurate separation of classes regarding fault position. In the case of the fuel injectors the feasibility of using one-class SVM has been tested in the detection of signal deviations indicating failure with high detection performance.

Anahtar Kelimeler

Vibration,condition monitoring,SVM,bearing

Kaynakça

McFadden P. D., J. D. Smith, 1984. Vibration monitoring of rolling element bearings by the high-frequency resonance technique – A review. Tribology International, 17(1): 3–10.
Paya B. A., I. I. Esat, M. N. M. Badi, 1997. Artificial neural network based fault diagnostics of rotating machinery using wavelet transforms as a preprocessor. Mechanical Systems and Signal Processing, 11(5): 751–765.
Pelckmans K., J.A.K. Suykens, T. Van Gestel, J. De Brabanter, L. Lukas, B. Hamers, B. De Moor, J. Vandewalle, 2002. LS-SVMlab: a Matlab/C toolbox for Least Squares Support Vector Machines., Internal Report 02-44, ESAT-SISTA, K.U.Leuven (Leuven, Belgium).
Sawalhi N., 2007. Diagnostics, Prognostics and Fault Simulation for Rolling Element Bearings, PhD Thesis, University of New South Wales, Australia.
Scholkopf B., J. Platt, J. Shawe-Taylor, A. Smola, and R. Williamson, 2001. Estimating the support of a highdimensional distribution. Neural Computation, 13(7): 1443–1472.
Suykens J.A.K., J. Vandewalle, 1999. Least Squares Support Vector Machine Classifiers. Neural Processing Letters, 9: 293–300. Vapnik V.N., 1998. Statistical Learning Theory. New York: Wiley Interscience.
Vapnik V.N., 1999. The Nature of Statistical Learning Theory. New York: Springer-Verlag.
Xu Z, J. Xuan., T. Shi, B. Wu, Y. Hu, 2009. Application of a modified fuzzy ARTMAP with feature-weight learning for the fault diagnosis of bearing. Expert Systems with Applications, 36: 9961-9968.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

Araştırma Makalesi

Yazarlar

Dimitrios Moshou Bu kişi benim
Greece

Athanasios Natsıs Bu kişi benim
Greece

Dimitrios Katerıs Bu kişi benim
Greece

İoannis Gravalos Bu kişi benim
Greece

Nader Sawalhı Bu kişi benim
Greece

İoannis Kalımanıs Bu kişi benim
Greece

Spyridon Loutrıdıs Bu kişi benim
Greece

Theodoros Gıalamas Bu kişi benim
Greece

Panayiotis Xyradakıs Bu kişi benim
Greece

Zisis Tsıropoulos Bu kişi benim
Greece

Yayımlanma Tarihi

1 Şubat 2011

Gönderilme Tarihi

8 Mayıs 2011

Kabul Tarihi

10 Temmuz 2011

Yayımlandığı Sayı

Yıl 2011 Cilt: 7 Sayı: 1

IZ

https://izlik.org/JA26GE73RD

Kaynak Göster

RIS / Bibtex

APA

Moshou, D., Natsıs, A., Katerıs, D., Gravalos, İ., Sawalhı, N., Kalımanıs, İ., Loutrıdıs, S., Gıalamas, T., Xyradakıs, P., & Tsıropoulos, Z. (2011). Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring. Tarım Makinaları Bilimi Dergisi, 7(1), 1-6. https://izlik.org/JA26GE73RD

AMA

1.Moshou D, Natsıs A, Katerıs D, vd. Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring. JAMS. 2011;7(1):1-6. https://izlik.org/JA26GE73RD

Chicago

Moshou, Dimitrios, Athanasios Natsıs, Dimitrios Katerıs, vd. 2011. “Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring”. Tarım Makinaları Bilimi Dergisi 7 (1): 1-6. https://izlik.org/JA26GE73RD.

EndNote

Moshou D, Natsıs A, Katerıs D, Gravalos İ, Sawalhı N, Kalımanıs İ, Loutrıdıs S, Gıalamas T, Xyradakıs P, Tsıropoulos Z (01 Şubat 2011) Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring. Tarım Makinaları Bilimi Dergisi 7 1 1–6.

IEEE

[1]D. Moshou vd., “Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring”, JAMS, c. 7, sy 1, ss. 1–6, Şub. 2011, [çevrimiçi]. Erişim adresi: https://izlik.org/JA26GE73RD

ISNAD

Moshou, Dimitrios - Natsıs, Athanasios - Katerıs, Dimitrios - Gravalos, İoannis - Sawalhı, Nader - Kalımanıs, İoannis - Loutrıdıs, Spyridon - Gıalamas, Theodoros - Xyradakıs, Panayiotis - Tsıropoulos, Zisis. “Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring”. Tarım Makinaları Bilimi Dergisi 7/1 (01 Şubat 2011): 1-6. https://izlik.org/JA26GE73RD.

JAMA

1.Moshou D, Natsıs A, Katerıs D, Gravalos İ, Sawalhı N, Kalımanıs İ, Loutrıdıs S, Gıalamas T, Xyradakıs P, Tsıropoulos Z. Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring. JAMS. 2011;7:1–6.

MLA

Moshou, Dimitrios, vd. “Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring”. Tarım Makinaları Bilimi Dergisi, c. 7, sy 1, Şubat 2011, ss. 1-6, https://izlik.org/JA26GE73RD.

Vancouver

1.Dimitrios Moshou, Athanasios Natsıs, Dimitrios Katerıs, İoannis Gravalos, Nader Sawalhı, İoannis Kalımanıs, Spyridon Loutrıdıs, Theodoros Gıalamas, Panayiotis Xyradakıs, Zisis Tsıropoulos. Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring. JAMS [Internet]. 01 Şubat 2011;7(1):1-6. Erişim adresi: https://izlik.org/JA26GE73RD