Cargando…
Multi-Sensor Fault Diagnosis of Underwater Thruster Propeller Based on Deep Learning
With the rapid development of unmanned surfaces and underwater vehicles, fault diagnoses for underwater thrusters are important to prevent sudden damage, which can cause huge losses. The propeller causes the most common type of thruster damage. Thus, it is important to monitor the propeller’s health...
Autores principales: | Tsai, Chia-Ming, Wang, Chiao-Sheng, Chung, Yu-Jen, Sun, Yung-Da, Perng, Jau-Woei |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8587634/ https://www.ncbi.nlm.nih.gov/pubmed/34770494 http://dx.doi.org/10.3390/s21217187 |
Ejemplares similares
-
Fault Diagnosis and Fault Frequency Determination of Permanent Magnet Synchronous Motor Based on Deep Learning
por: Wang, Chiao-Sheng, et al.
Publicado: (2021) -
A propellant-free superconducting solenoid thruster driven by geomagnetic field
por: Kuo, Heng-Wei, et al.
Publicado: (2020) -
MHz-Order Surface Acoustic Wave Thruster for Underwater Silent Propulsion
por: Zhang, Naiqing, et al.
Publicado: (2020) -
Multi-Dimensional Underwater Point Cloud Detection Based on Deep Learning
por: Tsai, Chia-Ming, et al.
Publicado: (2021) -
Preparation and Performance Evaluation of Platinum Barium Hexaaluminate Catalyst for Green Propellant Hydroxylamine Nitrate Thrusters
por: Kang, Shinjae, et al.
Publicado: (2021)