Recognition Algorithm of AE Signal of Rock Fracture Based on Multiscale 1DCNN-BLSTM
Acoustic emission (AE) signals produced by different types of rocks have different characteristics of information. Determining the brittle mineral content of rock according to the acoustic emission characteristics of rock is helpful to understand the mechanical behavior of rock in field monitoring....
Saved in:
| Main Author: | Weihua Wang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2024-01-01
|
| Series: | Journal of Electrical and Computer Engineering |
| Online Access: | http://dx.doi.org/10.1155/2024/3717867 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Antinoise Fault Diagnosis Method Based on Multiscale 1DCNN
by: Jie Cao, et al.
Published: (2020-01-01) -
Machine learning-based state of charge estimation: A comparison between CatBoost model and C-BLSTM-AE model
by: Abderrahim Zilali, et al.
Published: (2025-06-01) -
Bangla Speech Emotion Recognition and Cross-Lingual Study Using Deep CNN and BLSTM Networks
by: Sadia Sultana, et al.
Published: (2022-01-01) -
BLSTM based night-time wildfire detection from video.
by: Ahmet K Agirman, et al.
Published: (2022-01-01) -
Anomaly Detection Based on 1DCNN Self-Attention Networks for Seismic Electric Signals
by: Wei Li, et al.
Published: (2025-07-01)