Tractor Engine Fault Detection System Based on Vibration and Acoustic Monitoring

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

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