Acoustic Emission Signal Recognition of Different Rocks Using Wavelet Transform and Artificial Neural Network
Different types of rocks generate acoustic emission (AE) signals with various frequencies and amplitudes. How to determine rock types by their AE characteristics in field monitoring is also useful to understand their mechanical behaviors. Different types of rock specimens (granulite, granite, limest...
Saved in:
| Main Authors: | Xiangxin Liu, Zhengzhao Liang, Yanbo Zhang, Xianzhen Wu, Zhiyi Liao |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-01-01
|
| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2015/846308 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Denoising of acoustic emission signals from rock failure processes through ICEEMDAN combined with multiple criteria and wavelet transform
by: Tao Wang, et al.
Published: (2025-03-01) -
Lithology Recognition Research Based on Wavelet Transform and Artificial Intelligence
by: FANG Dazhi, et al.
Published: (2023-08-01) -
Interrupted Sampling Repeater Jamming Recognition Method Based on Wavelet Packet Transform
by: Zhong Qi, et al.
Published: (2025-01-01) -
Enhanced engine misfire diagnosis through integration of vibration and acoustic emission signals using artificial neural networks
by: Mohamed H. Abdelati, et al.
Published: (2025-08-01) -
Iris Recognition System Based on Wavelet Transform
by: Maha Hasso, et al.
Published: (2009-07-01)