World's Best Scientists 2026 revealed!

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Computer Science

D-Index
55
Citations
10371
World Ranking
4369
National Ranking
582

Overview

Chuan Li is affiliated with Chongqing Technology and Business University in China. Their research primarily falls within the field of Engineering, with significant contributions focused on Control and Systems Engineering, Mechanical Engineering, Electrical and Electronic Engineering, and Artificial Intelligence.

The main topics explored in their work include Machine Fault Diagnosis Techniques, Fault Detection and Control Systems, Gear and Bearing Dynamics Analysis, Industrial Vision Systems and Defect Detection, Anomaly Detection Techniques and Applications, Engineering Diagnostics and Reliability, and Climate Change and Health Impacts.

Chuan Li has published extensively in several venues, with a notable presence in:

  • SSRN Electronic Journal
  • Mechanical Systems and Signal Processing
  • Measurement
  • Measurement Science and Technology
  • arXiv (Cornell University)

Frequent collaborators in their work include Jianyu Long, Yun Bai, Diego Cabrera, Zhe Yang, and Shuai Yang.

Among Chuan Li's recent papers are:

  • "A systematic review of deep transfer learning for machinery fault diagnosis" (2020), published in Neurocomputing
  • "Attitude data-based deep hybrid learning architecture for intelligent fault diagnosis of multi-joint industrial robots" (2020), published in Journal of Manufacturing Systems
  • "Fully interpretable neural network for locating resonance frequency bands for machine condition monitoring" (2021), published in Mechanical Systems and Signal Processing
  • "A nearly end-to-end deep learning approach to fault diagnosis of wind turbine gearboxes under nonstationary conditions" (2022), published in Engineering Applications of Artificial Intelligence
  • "Box-Cox sparse measures: A new family of sparse measures constructed from kurtosis and negative entropy" (2021), published in Mechanical Systems and Signal Processing

Best Publications

  • Gearbox fault diagnosis based on deep random forest fusion of acoustic and vibratory signals

    Chuan Li;Chuan Li;René Vinicio Sanchez;Grover Zurita;Mariela Cerrada

  • State-of-charge estimation of lithium-ion batteries based on gated recurrent neural network

    Fangfang Yang;Fangfang Yang;Weihua Li;Chuan Li;Qiang Miao

  • Gearbox Fault Identification and Classification with Convolutional Neural Networks

    ZhiQiang Chen;Chuan Li;René-Vinicio Sanchez

  • A systematic review of deep transfer learning for machinery fault diagnosis

    Chuan Li;Shaohui Zhang;Yi Qin;Edgar Estupinan

  • Fault diagnosis in spur gears based on genetic algorithm and random forest

    Mariela Cerrada;Mariela Cerrada;Grover Zurita;Diego Cabrera;René Vinicio Sánchez

  • Air pollutants concentrations forecasting using back propagation neural network based on wavelet decomposition with meteorological conditions

    Yun Bai;Yong Li;Xiaoxue Wang;Jingjing Xie

  • Time-frequency signal analysis for gearbox fault diagnosis using a generalized synchrosqueezing transform

    Chuan Li;Chuan Li;Ming Liang

  • Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis

    Chuan Li;René-Vinicio Sanchez;Grover Zurita;Mariela Cerrada

  • Deep neural networks-based rolling bearing fault diagnosis

    Zhiqiang Chen;Shengcai Deng;Xudong Chen;Chuan Li

  • Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning.

    Chuan Li;René Vinicio Sánchez;Grover Zurita;Mariela Cerrada

  • A generalized synchrosqueezing transform for enhancing signal time-frequency representation

    Chuan Li;Ming Liang

  • Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models

    Yun Bai;Zhiqiang Chen;Jingjing Xie;Chuan Li

  • Forecasting the natural gas demand in China using a self-adapting intelligent grey model

    Bo Zeng;Chuan Li

  • Improving forecasting accuracy of daily enterprise electricity consumption using a random forest based on ensemble empirical mode decomposition

    Chuan Li;Chuan Li;Ying Tao;Wengang Ao;Shuai Yang

  • Evolving Deep Echo State Networks for Intelligent Fault Diagnosis

    Jianyu Long;Shaohui Zhang;Chuan Li

  • An ensemble long short-term memory neural network for hourly PM2.5 concentration forecasting.

    Yun Bai;Bo Zeng;Chuan Li;Jin Zhang

  • Improved multi-variable grey forecasting model with a dynamic background-value coefficient and its application

    Bo Zeng;Chuan Li

  • Criterion fusion for spectral segmentation and its application to optimal demodulation of bearing vibration signals

    Chuan Li;Chuan Li;Ming Liang;Tianyang Wang

  • Rolling element bearing defect detection using the generalized synchrosqueezing transform guided by time–frequency ridge enhancement

    Chuan Li;Chuan Li;Vinicio Sanchez;Grover Zurita;Mariela Cerrada Lozada

  • A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis

    Chuan Li;Jose Valente de Oliveira;Mariela Cerrada;Diego Cabrera

  • Development of an optimization method for the GM(1,N) model

    Bo Zeng;Chengming Luo;Sifeng Liu;Yun Bai

Frequent Co-Authors

Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Sifeng Liu
Sifeng Liu Nanjing University of Aeronautics and Astronautics
Michael Pecht
Michael Pecht University of Maryland, College Park
Panos M. Pardalos
Panos M. Pardalos University of Florida
Dong Wang
Dong Wang Peking University
Zhirong Zhang
Zhirong Zhang Sichuan University
Rui Xiong
Rui Xiong Beijing Institute of Technology
Jiuchun Jiang
Jiuchun Jiang Hubei University of Technology
Sheng-Nian Luo
Sheng-Nian Luo Southwest Jiaotong University
Minhao Zhu
Minhao Zhu Southwest Jiaotong University

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