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
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
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.
| Birincil Dil | İngilizce |
|---|---|
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Şubat 2011 |
| IZ | https://izlik.org/JA26GE73RD |
| Yayımlandığı Sayı | Yıl 2011 Cilt: 7 Sayı: 1 |
Tarım Makinaları Bilimi Dergisi, Tarım Makinaları Derneği tarafından yayınlanan hakemli bilimsel bir dergidir. Dergi, 2026 yılından itibaren sürekli yayın modeline geçmiştir.