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A Machine-Learning-Based Distributed System for Fault Diagnosis With Scalable Detection Quality in Industrial IoT

  • Published:2021-03-15 Issue:6 Volume:8 Page:4339-4352
  • ISSN:2327-4662
  • Container-title:IEEE Internet of Things Journal
  • language:
  • Short-container-title:IEEE Internet Things J.

Author:

Marino RodrigoORCID,Wisultschew Cristian,Otero AndresORCID,Lanza-Gutierrez Jose M.ORCID,Portilla JorgeORCID,Torre Eduardo de laORCID

Funder

Spanish Ministry (Ministerio de Economía y Competitividad) under the PLATINO Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Cited by 32 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Fault Diagnosis for Rotating Machine Utilizing Machine Learning with FFT-based Feature Extraction;2024 Tenth International Conference on Communications and Electronics (ICCE);2024-07-31

2. Hierarchical representation and interpretable learning for accelerated quality monitoring in machining process;CIRP Journal of Manufacturing Science and Technology;2024-06

3. Industrial Internet of Things embedded devices fault detection and classification. A case study;Internet of Things;2024-04

4. Edge-cloud collaborative transfer learning based on stacked sparse autoencoder with data regularization;Third International Conference on Advanced Manufacturing Technology and Electronic Information (AMTEI 2023);2024-04-01

5. DISNET: Distributed Micro-Split Deep Learning in Heterogeneous Dynamic IoT;IEEE Internet of Things Journal;2024-02-15
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