Deep learning based approaches for intelligent industrial machinery health management and fault diagnosis in resource-constrained environments
Quaid-i-Azam University · National University of Sciences and Technology · +1 more institution
Abstract
Industry 4.0 represents the fourth industrial revolution, which is characterized by the incorporation of digital technologies, the Internet of Things (IoT), artificial intelligence, big data, and other advanced technologies into industrial processes. Industrial Machinery Health Management (IMHM) is a crucial element, based on the Industrial Internet of Things (IIoT), which focuses on monitoring the health and condition of industrial machinery. The academic community has focused on various aspects of IMHM, such as prognostic maintenance, condition monitoring, estimation of remaining useful life (RUL), intelligent fault diagnosis (IFD), and architectures based on edge computing. Each of these categories holds…
Citation impact
- FWCI
- 57.08
- Percentile
- 100%
- References
- 188
Authors
6Topics & keywords
- Computer science
- Context (archaeology)
- Data science
- Industrial Internet
- Fault (geology)
- Resource (disambiguation)
- Big data
- Enhanced Data Rates for GSM Evolution