World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
10196
World Ranking
3904
National Ranking
523

Overview

Dong Wang is affiliated with Shanghai Jiao Tong University in China and has a primary focus in the field of Engineering, with extensive contributions across several key subfields. Their research output spans Control and Systems Engineering, Mechanical Engineering, Electrical and Electronic Engineering, Civil and Structural Engineering, and Mechanics of Materials.

The scientist's main research topics include:

  • Machine Fault Diagnosis Techniques
  • Fault Detection and Control Systems
  • Gear and Bearing Dynamics Analysis
  • Non-Destructive Testing Techniques
  • Reliability and Maintenance Optimization
  • Structural Health Monitoring Techniques
  • Advanced machining processes and optimization

Notable recent papers authored or coauthored by Dong Wang feature work in machine health monitoring, fault diagnosis, and battery lifespan prediction. These include:

  • The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring, 2020, Mechanical Systems and Signal Processing
  • Multi-scale deep intra-class transfer learning for bearing fault diagnosis, 2020, Reliability Engineering & System Safety
  • Image recognition of wind turbine blade damage based on a deep learning model with transfer learning and an ensemble learning classifier, 2020, Renewable Energy
  • Lifespan prediction of lithium-ion batteries based on various extracted features and gradient boosting regression tree model, 2020, Journal of Power Sources
  • Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis Under Unseen Conditions, 2021, IEEE Transactions on Industrial Informatics

Dong Wang frequently publishes in the following venues:

  • Mechanical Systems and Signal Processing
  • IEEE Transactions on Instrumentation and Measurement
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Journal of Physics Conference Series

Collaborative research partnerships include frequent coauthors such as Zhike Peng, Tangbin Xia, Lifeng Xi, Changqing Shen, and Tongtong Yan, reflecting a pattern of sustained academic collaboration.

In addition to journal articles, Dong Wang has contributed to book publications, including a title in the Springer series in reliability engineering: Advances in Reliability and Maintainability Methods and Engineering Applications (2023).

Best Publications

  • An enhanced Kurtogram method for fault diagnosis of rolling element bearings

    Dong Wang;Peter W. Tse;Kwok Leung Tsui

  • Prognostics and Health Management: A Review of Vibration Based Bearing and Gear Health Indicators

    Dong Wang;Kwok-Leung Tsui;Qiang Miao

  • Combined CNN-LSTM Network for State-of-Charge Estimation of Lithium-Ion Batteries

    Xiangbao Song;Fangfang Yang;Dong Wang;Kwok-Leung Tsui

  • The design of a new sparsogram for fast bearing fault diagnosis: Part 1 of the two related manuscripts that have a joint title as “Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement – Parts 1 and 2”

    Peter W. Tse;Dong Wang

  • Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Spherical Cubature Particle Filter

    Dong Wang;Fangfang Yang;Kwok-Leung Tsui;Qiang Zhou

  • Multi-scale deep intra-class transfer learning for bearing fault diagnosis

    Xu Wang;Changqing Shen;Min Xia;Dong Wang

  • Fault diagnosis of rotating machinery based on the statistical parameters of wavelet packet paving and a generic support vector regressive classifier

    Changqing Shen;Changqing Shen;Dong Wang;Fanrang Kong;Peter W. Tse

  • Sparsity guided empirical wavelet transform for fault diagnosis of rolling element bearings

    Dong Wang;Yang Zhao;Cai Yi;Cai Yi;Kwok-Leung Tsui

  • Stacked Sparse Autoencoder-Based Deep Network for Fault Diagnosis of Rotating Machinery

    Yumei Qi;Changqing Shen;Dong Wang;Juanjuan Shi

  • Some further thoughts about spectral kurtosis, spectral L2/L1 norm, spectral smoothness index and spectral Gini index for characterizing repetitive transients

    Dong Wang

  • A comparative study of three model-based algorithms for estimating state-of-charge of lithium-ion batteries under a new combined dynamic loading profile

    Fangfang Yang;Yinjiao Xing;Dong Wang;Kwok-Leung Tsui

  • Adversarial domain-invariant generalization: a generic domain-regressive framework for bearing fault diagnosis under unseen conditions

    Liang Chen;Qi Li;Changqing Shen;Jun Zhu

  • Lifespan prediction of lithium-ion batteries based on various extracted features and gradient boosting regression tree model

    Fangfang Yang;Dong Wang;Fan Xu;Zhelin Huang

  • The sum of weighted normalized square envelope: A unified framework for kurtosis, negative entropy, Gini index and smoothness index for machine health monitoring

    Dong Wang;Zhike Peng;Lifeng Xi

  • Voltage-temperature health feature extraction to improve prognostics and health management of lithium-ion batteries

    Jin-zhen Kong;Fangfang Yang;Xi Zhang;Ershun Pan

  • K-nearest neighbors based methods for identification of different gear crack levels under different motor speeds and loads: Revisited

    Dong Wang

  • Spectral L2 / L1 norm: A new perspective for spectral kurtosis for characterizing non-stationary signals

    Dong Wang

  • Robust health evaluation of gearbox subject to tooth failure with wavelet decomposition

    Dong Wang;Qiang Miao;Rui Kang

  • A simple and fast guideline for generating enhanced/squared envelope spectra from spectral coherence for bearing fault diagnosis

    Dong Wang;Dong Wang;Xuejun Zhao;Lin-Lin Kou;Yong Qin

  • Robustness Evaluation of Extended and Unscented Kalman Filter for Battery State of Charge Estimation

    Chao Huang;Zhenhua Wang;Zihan Zhao;Long Wang

  • The automatic selection of an optimal wavelet filter and its enhancement by the new sparsogram for bearing fault detection Part 2 of the two related manuscripts that have a joint title as "Two automatic vibration-based fault diagnostic methods using the novel sparsity measurement—Parts 1 and 2"

    Peter W. Tse;Dong Wang

Frequent Co-Authors

Kwok-Leung Tsui
Kwok-Leung Tsui Virginia Tech
Peter W. Tse
Peter W. Tse City University of Hong Kong
Changqing Shen
Changqing Shen Soochow University
Yang Zhao
Yang Zhao Beijing Institute of Technology
Lifeng Xi
Lifeng Xi Shanghai Jiao Tong University
Zhongkui Zhu
Zhongkui Zhu Soochow University
Chuan Li
Chuan Li Chongqing Technology and Business University
Michael Pecht
Michael Pecht University of Maryland, College Park
Hong-Zhong Huang
Hong-Zhong Huang University of Electronic Science and Technology of China
Qingbo He
Qingbo He Shanghai Jiao Tong University

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