World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
40
Citations
4893
World Ranking
2074
National Ranking
247

Dejie Yu publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Dejie Yu sits on this spectrum.

47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47 publications 659+

This scientist: 144 publications — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

Dejie Yu D-index placement in Mechanical and Aerospace Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Mechanical and Aerospace Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Dejie Yu sits on this spectrum.

30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 40 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

Overview

Dejie Yu is affiliated with Hunan University in China and has developed a research portfolio centered predominantly around engineering with a focus on various subfields including biomedical engineering, control and systems engineering, atomic and molecular physics and optics, mechanical engineering, and signal processing.

Their research interests span multiple main topics, particularly acoustic wave phenomena research, machine fault diagnosis techniques, topological materials and phenomena, gear and bearing dynamics analysis, speech and audio processing, underwater acoustics research, and ultrasonics and acoustic wave propagation.

Dejie Yu has published extensively in notable scientific journals. Frequent publication venues include:

  • SSRN Electronic Journal
  • Measurement
  • Journal of Sound and Vibration
  • Physical Review B
  • Applied Physics Letters

Recent papers authored or co-authored by Dejie Yu reflect key themes in intelligent fault diagnosis and acoustic metamaterials. These include:

  • Intelligent acoustic-based fault diagnosis of roller bearings using a deep graph convolutional network, 2020, Measurement
  • Semi-supervised graph convolutional network and its application in intelligent fault diagnosis of rotating machinery, 2021, Measurement
  • Observation of fractal higher-order topological states in acoustic metamaterials, 2022, Science Bulletin
  • Total variation on horizontal visibility graph and its application to rolling bearing fault diagnosis, 2020, Mechanism and Machine Theory
  • Intelligent fault diagnosis for rolling bearings based on graph shift regularization with directed graphs, 2021, Advanced Engineering Informatics

Their collaborative work often involves several frequent co-authors, contributing to interdisciplinary studies in the above domains. Notable frequent co-authors include Tinggui Chen, Baizhan Xia, Junrui Jiao, Yiyuan Gao, and Shengjie Zheng.

Best Publications

  • Application of EMD method and Hilbert spectrum to the fault diagnosis of roller bearings

    Dejie Yu;Junsheng Cheng;Yu Yang

  • A fault diagnosis approach for roller bearing based on IMF envelope spectrum and SVM

    Yu Yang;Dejie Yu;Junsheng Cheng

  • Elastic Higher-Order Topological Insulator with Topologically Protected Corner States.

    Haiyan Fan;Baizhan Xia;Liang Tong;Shengjie Zheng

  • Application of support vector regression machines to the processing of end effects of Hilbert Huang transform

    Junsheng Cheng;Dejie Yu;Yu Yang

  • Intelligent acoustic-based fault diagnosis of roller bearings using a deep graph convolutional network

    Dingcheng Zhang;Edward Stewart;Mani Entezami;Clive Roberts

  • Dynamic load identification for stochastic structures based on Gegenbauer polynomial approximation and regularization method

    Jie Liu;Xingsheng Sun;Xu Han;Chao Jiang

  • Application of frequency family separation method based upon EMD and local Hilbert energy spectrum method to gear fault diagnosis

    Junsheng Cheng;Dejie Yu;Jiashi Tang;Yu Yang

  • Application of time–frequency entropy method based on Hilbert–Huang transform to gear fault diagnosis

    Dejie Yu;Yu Yang;Junsheng Cheng

  • A research on intelligent fault diagnosis of wind turbines based on ontology and FMECA

    Unknown

  • Local rub-impact fault diagnosis of the rotor systems based on EMD

    Junsheng Cheng;Dejie Yu;Jiashi Tang;Yu Yang

  • Modified sub-interval perturbation finite element method for 2D acoustic field prediction with large uncertain-but-bounded parameters

    Baizhan Xia;Dejie Yu

  • A gear fault diagnosis using Hilbert spectrum based on MODWPT and a comparison with EMD approach

    Yu Yang;Yigang He;Junsheng Cheng;Dejie Yu

  • Application of SVM and SVD Technique Based on EMD to the Fault Diagnosis of the Rotating Machinery

    Junsheng Cheng;Dejie Yu;Jiashi Tang;Yu Yang

  • Sparse signal decomposition method based on multi-scale chirplet and its application to the fault diagnosis of gearboxes

    Fuqiang Peng;Dejie Yu;Jiesi Luo

  • Interval and subinterval perturbation methods for a structural-acoustic system with interval parameters

    Baizhan Xia;Dejie Yu;Jian Liu

  • The envelope order spectrum based on generalized demodulation time–frequency analysis and its application to gear fault diagnosis

    Junsheng Cheng;Yu Yang;Dejie Yu

  • Reliability-based design optimization of structural systems under hybrid probabilistic and interval model

    Baizhan Xia;Hui Lü;Dejie Yu;Chao Jiang

  • A kurtosis-guided adaptive demodulation technique for bearing fault detection based on tunable-Q wavelet transform

    Jiesi Luo;Jiesi Luo;Dejie Yu;Ming Liang

  • Interval analysis of acoustic field with uncertain-but-bounded parameters

    Baizhan Xia;Dejie Yu

  • A novel computational inverse technique for load identification using the shape function method of moving least square fitting

    Jie Liu;Xingsheng Sun;Xu Han;Chao Jiang

  • Semi-supervised graph convolutional network and its application in intelligent fault diagnosis of rotating machinery

    Yiyuan Gao;Yiyuan Gao;Mang Chen;Dejie Yu

  • A Fault Diagnosis Approach for Gears Based on IMF AR Model and SVM

    Junsheng Cheng;Dejie Yu;Yu Yang

  • Brake squeal reduction of vehicle disc brake system with interval parameters by uncertain optimization

    Hui Lü;Dejie Yu

  • Application of multi-scale chirplet path pursuit and fractional Fourier transform for gear fault detection in speed up and speed-down processes

    Jiesi Luo;Jiesi Luo;Dejie Yu;Dejie Yu;Ming Liang

  • Adaptive fault feature extraction from wayside acoustic signals from train bearings

    Dingcheng Zhang;Mani Entezami;Edward Stewart;Clive Roberts

  • Hybrid uncertain analysis for structural-acoustic problem with random and interval parameters

    Baizhan Xia;Dejie Yu;Jian Liu

  • Intelligent fault diagnosis for rolling bearings based on graph shift regularization with directed graphs

    Unknown

  • Multi-fault diagnosis of gearbox based on resonance-based signal sparse decomposition and comb filter

    Dingcheng Zhang;Dingcheng Zhang;Dejie Yu

  • A new rolling bearing fault diagnosis method based on GFT impulse component extraction

    Lu Ou;Dejie Yu;Hanjian Yang

  • Vehicle motion control under equality and inequality constraints: a diffeomorphism approach

    Hui Yin;Hui Yin;Ye-Hwa Chen;Dejie Yu

Frequent Co-Authors

Michael Beer
Michael Beer University of Liverpool
Junsheng Cheng
Junsheng Cheng Hunan University
Clive J. Roberts
Clive J. Roberts University of Nottingham
Ming Liang
Ming Liang University of Ottawa
Xu Han
Xu Han Hebei University of Technology
Zhen Luo
Zhen Luo University of Technology Sydney
Jie Liu
Jie Liu Hunan University
Guoliang Huang
Guoliang Huang University of Missouri
Chen Jiang
Chen Jiang Hunan University
Yaguo Lei
Yaguo Lei Xi'an Jiaotong University

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