"Deep Learning-Based Feature Extraction of Acoustic Emission Signals for ..."

D. González et al. (2022)

> Home

Details and statistics

DOI: 10.3390/S22186911

access: open

type: Journal Article

metadata version: 2023-02-10

- view
  - electronic edition via DOI (open access)
  authority control:
- export record
  dblp key:
  - journals/sensors/GonzalezASGP22
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/sensors/GonzalezASGP22
D. González, Jorge Álvarez, José Antonio Sánchez, Leire Godino, Iñigo Pombo:
Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels. Sensors 22(18): 6911 (2022)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.