D-Index & Metrics Best Publications

D-Index & Metrics D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines.

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 42 Citations 6,363 155 World Ranking 5306 National Ranking 501

Overview

What is he best known for?

The fields of study he is best known for:

  • Mechanical engineering
  • Artificial intelligence
  • Machine learning

His main research concerns Artificial intelligence, Electronic engineering, Vibration, Pattern recognition and Signal processing. The concepts of his Artificial intelligence study are interwoven with issues in Time domain, Machine learning and Frequency domain. His study in Machine learning is interdisciplinary in nature, drawing from both Classifier, Data mining and Spur.

The Electronic engineering study combines topics in areas such as Rolling-element bearing, Acoustic emission and Sensor fusion. In his research, Random forest and Wavelet packet decomposition is intimately related to Fault detection and isolation, which falls under the overarching field of Vibration. Chuan Li has included themes like Instantaneous phase, Bearing and Time–frequency analysis in his Signal processing study.

His most cited work include:

  • A review on data-driven fault severity assessment in rolling bearings (193 citations)
  • Gearbox Fault Identification and Classification with Convolutional Neural Networks (178 citations)
  • Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis (177 citations)

What are the main themes of his work throughout his whole career to date?

Chuan Li mainly focuses on Artificial intelligence, Vibration, Pattern recognition, Data mining and Machine learning. Chuan Li interconnects Electronic engineering and Fault detection and isolation in the investigation of issues within Artificial intelligence. His Electronic engineering research is multidisciplinary, relying on both Rolling-element bearing, Bearing and Signal processing.

His Vibration research integrates issues from Energy harvesting, Bandwidth, Control theory and Spur. His Spur study integrates concerns from other disciplines, such as Random forest and Wavelet packet decomposition. His work investigates the relationship between Data mining and topics such as Mean absolute percentage error that intersect with problems in Feature learning.

He most often published in these fields:

  • Artificial intelligence (38.54%)
  • Vibration (31.25%)
  • Pattern recognition (21.35%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (38.54%)
  • Deep learning (10.94%)
  • Pattern recognition (21.35%)

In recent papers he was focusing on the following fields of study:

Chuan Li spends much of his time researching Artificial intelligence, Deep learning, Pattern recognition, Echo state network and Data mining. His Artificial intelligence study combines topics from a wide range of disciplines, such as Regression analysis and Machine learning. The study incorporates disciplines such as Supervised learning and Autoencoder in addition to Pattern recognition.

His research in Data mining tackles topics such as Cluster analysis which are related to areas like Support vector machine. As part of one scientific family, he deals mainly with the area of Support vector machine, narrowing it down to issues related to the Fault detection and isolation, and often Convolutional neural network. His work carried out in the field of Feature brings together such families of science as Vibration, State and Reliability.

Between 2019 and 2021, his most popular works were:

  • Evolving Deep Echo State Networks for Intelligent Fault Diagnosis (50 citations)
  • A Novel Sparse Echo Autoencoder Network for Data-Driven Fault Diagnosis of Delta 3-D Printers (32 citations)
  • Deep Fuzzy Echo State Networks for Machinery Fault Diagnosis (22 citations)

In his most recent research, the most cited papers focused on:

  • Mechanical engineering
  • Artificial intelligence
  • Machine learning

His scientific interests lie mostly in Artificial intelligence, Deep learning, Echo state network, Data mining and Pattern recognition. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Turbine and Reciprocating compressor, Gas compressor. His work deals with themes such as Vibration, Entropy, Fourier transform and Wavelet, which intersect with Turbine.

In his research on the topic of Deep learning, Systems engineering, Classifier and Embedding is strongly related with Transfer of learning. His research investigates the connection with Data mining and areas like Cluster analysis which intersect with concerns in Mean absolute percentage error, State and Feature. His biological study spans a wide range of topics, including Autoencoder, Echo, Fuzzy clustering, Data-driven and Robustness.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Gearbox Fault Identification and Classification with Convolutional Neural Networks

ZhiQiang Chen;Chuan Li;René-Vinicio Sanchez.
Shock and Vibration (2015)

346 Citations

Gearbox Fault Identification and Classification with Convolutional Neural Networks

ZhiQiang Chen;Chuan Li;René-Vinicio Sanchez.
Shock and Vibration (2015)

346 Citations

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.
Mechanical Systems and Signal Processing (2016)

345 Citations

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.
Mechanical Systems and Signal Processing (2016)

345 Citations

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

Yun Bai;Yong Li;Xiaoxue Wang;Jingjing Xie.
Atmospheric Pollution Research (2016)

267 Citations

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

Yun Bai;Yong Li;Xiaoxue Wang;Jingjing Xie.
Atmospheric Pollution Research (2016)

267 Citations

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

Chuan Li;Chuan Li;Ming Liang.
Mechanical Systems and Signal Processing (2012)

259 Citations

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

Chuan Li;Chuan Li;Ming Liang.
Mechanical Systems and Signal Processing (2012)

259 Citations

A review on data-driven fault severity assessment in rolling bearings

Mariela Cerrada;Mariela Cerrada;René-Vinicio Sánchez;Chuan Li;Fannia Pacheco.
Mechanical Systems and Signal Processing (2018)

258 Citations

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

Mariela Cerrada;Mariela Cerrada;Grover Zurita;Diego Cabrera;René Vinicio Sánchez.
Mechanical Systems and Signal Processing (2016)

256 Citations

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