Classification of Fatigue Damaging Segments Using Artificial Neural Network / M. F. M. Yunoh ...[et al.]
This paper focuses on the classification of the fatigue damaging segments datasets associated with the measurement of Variable Amplitude Loadings of strain signals from the coil springs of an automobile during road tests. The wavelet transform was used to extract high damaging segments of the fatigu...
Saved in:
Main Authors: | M. Yunoh, M. F. (Author), Abdullah, S. (Author), M. Saad, M. H. (Author), M. Nopiah, Z. (Author), Nuawi, M. Z. (Author), Ariffin, A. (Author) |
---|---|
Format: | Book |
Published: |
Faculty of Mechanical Engineering Universiti Teknologi MARA (UiTM),
2018.
|
Subjects: | |
Online Access: | Link Metadata |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Determining Damaging Fatigue Cycles under Influence of Random Loadings using the Root-Mean-Square Level / M. Mahmud ...[et al.]
by: Mahmud, M., et al.
Published: (2018) -
Effect of Stretchable Circuit Deformation on Its Electrical Performance for Automotive Lighting Application / M. F. M. Sharif...[et al.]
by: M. F., M. Sharif, et al.
Published: (2017) -
Observing the behaviour of reinforced magnesium alloy with carbon-nanotube and lead under 976 m/s projectile impact / M.F. Abdullah ...[et al.]
by: Abdullah, M.F, et al.
Published: (2018) -
Microscopic nuclei classification, segmentation, and detection with improved deep convolutional neural networks (DCNN)
by: Zahangir Alom, et al.
Published: (2022) -
Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.]
by: M. A., Hambali, et al.
Published: (2017)