Journal Bearing Fault Detection Based on Daubechies Wavelet
Journal bearings are widely used to support the shafts in industrial machinery involving heavy loads, such as compressors, turbines and centrifugal pumps. The major problem that could arise in journal bearings is catastrophic failure due to corrosion or erosion and fatigue, which results in economic...
Saved in:
| Main Authors: | Narendiranath Babu THAMBA, Himamshu H S, Prabin Kumar NAYAK, Rama Prabha D, Nishant CHILUAR |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute of Fundamental Technological Research Polish Academy of Sciences
2017-07-01
|
| Series: | Archives of Acoustics |
| Subjects: | |
| Online Access: | https://acoustics.ippt.pan.pl/index.php/aa/article/view/1918 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Automatic Fault Classification for Journal Bearings Using ANN and DNN
by: Narendiranath Babu THAMBA, et al.
Published: (2018-10-01) -
Application of EMD, ANN and DNN for Self-Aligning Bearing Fault Diagnosis
by: Narendiranath Babu THAMBA, et al.
Published: (2018-01-01) -
Fault detection of taper roller bearings using tunable Q-factor wavelet transform and fault classification using long–short-term memory network
by: A. Anwarsha, et al.
Published: (2025-03-01) -
Daubechies Wavelet Charts to Control and Monitor Individual Observations
by: Sarah Bahrooz Ameen, et al.
Published: (2025-06-01) -
Locomotive Bearing Fault Diagnosis Using Empirical Wavelet Transform
by: Renjie XU
Published: (2019-09-01)