A Time-Distributed Spatiotemporal Feature Learning Method for Machine Health Monitoring with Multi-Sensor Time Series

Data-driven methods with multi-sensor time series data are the most promising approaches for monitoring machine health. Extracting fault-sensitive features from multi-sensor time series is a daunting task for both traditional data-driven methods and current deep learning models. A novel hybrid end-t...

Descripción completa

Detalles Bibliográficos
Autores principales: Qiao, Huihui, Wang, Taiyong, Wang, Peng, Qiao, Shibin, Zhang, Lan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164508/
https://www.ncbi.nlm.nih.gov/pubmed/30177670
http://dx.doi.org/10.3390/s18092932

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6164508/
https://www.ncbi.nlm.nih.gov/pubmed/30177670
http://dx.doi.org/10.3390/s18092932

Ejemplares similares