articleMeasurementApr 8, 2016Closed access

A sparse auto-encoder-based deep neural network approach for induction motor faults classification

WSWenjun SunSSSiyu ShaoRZRui ZhaoRYRuqiang YanXZXingwu Zhang

Southeast University · Nanyang Technological University · +1 more institution

Indexed incrossref

Abstract

No abstract available for this paper.

Citation impact

691
total citations
FWCI
57.49
Percentile
100%
References
42
Citations per year

Authors

6

Topics & keywords

Topics
Keywords
  • Autoencoder
  • Induction motor
  • Artificial neural network
  • Computer science
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Deep neural networks
  • Encoder
UN Sustainable Development Goals
  • Peace, Justice and strong institutions
No related works found for this paper.

Funding