Hongchao Wang

Control and Systems Engineering · 2019

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hongchao Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Haidong Shao
  2. Charles R. Farrar
  3. Zhuyun Chen

Papers from Hongchao Wang's perspective

Ordered by how strongly the researchers Hongchao Wang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Deep Learning
  2. A sparse auto-encoder-based deep neural network approach for induction motor faults classification
  3. Bearing Health Monitoring Based on Hilbert–Huang Transform, Support Vector Machine, and Regression (IEEE Transactions on Instrumentation and Measurement)
  4. Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks (IEEE transactions on industrial electronics (1982. Print))
  5. Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data
  6. An enhancement deep feature fusion method for rotating machinery fault diagnosis
  7. Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network
  8. A novel bearing fault diagnosis model integrated permutation entropy, ensemble empirical mode decomposition and optimized SVM
  9. Diagnosis of Bearing Faults in Induction Machines by Vibration or Current Signals: A Critical Comparison (IEEE transactions on industry applications)
  10. Deep learning and its applications to machine health monitoring (Mechanical systems and signal processing)

Their papers