Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring

Yıl 2011, Cilt: 7 Sayı: 1, 1 - 6, 01.02.2011

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

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

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