World's Best Scientists 2026 revealed!

D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
36
Citations
4337
World Ranking
2571
National Ranking
313

Ningyun Lu 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 Ningyun Lu 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: 195 publications — 43rd percentile

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

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

Ningyun Lu 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 Ningyun Lu 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: 36 D-Index — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Best Publications

  • Sub‐PCA modeling and on‐line monitoring strategy for batch processes

    Ningyun Lu;Furong Gao;Fuli Wang

  • Stage-based soft-transition multiple PCA modeling and on-line monitoring strategy for batch processes

    Chunhui Zhao;Fuli Wang;Ningyun Lu;Mingxing Jia

  • A Descriptor System Approach for Estimation of Incipient Faults With Application to High-Speed Railway Traction Devices

    Yunkai Wu;Bin Jiang;Ningyun Lu

  • Deep PCA Based Real-Time Incipient Fault Detection and Diagnosis Methodology for Electrical Drive in High-Speed Trains

    Hongtian Chen;Bin Jiang;Ningyun Lu;Zehui Mao

  • Stage-based process analysis and quality prediction for batch processes

    Ningyun Lu;Furong Gao

  • Two-dimensional dynamic PCA for batch process monitoring

    Ningyun Lu;Yuan Yao;Furong Gao;Fuli Wang

  • An improved incipient fault detection method based on Kullback-Leibler divergence.

    Unknown

  • A Data-Driven Aero-Engine Degradation Prognostic Strategy

    Cunsong Wang;Ningyun Lu;Yuehua Cheng;Bin Jiang

  • Prediction Interval Estimation of Aeroengine Remaining Useful Life Based on Bidirectional Long Short-Term Memory Network

    Chuang Chen;Ningyun Lu;Bin Jiang;Yin Xing

  • A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance

    Chuang Chen;Ningyun Lu;Bin Jiang;Cunsong Wang

  • Dynamic Long Short-Term Memory Neural-Network- Based Indirect Remaining-Useful-Life Prognosis for Satellite Lithium-Ion Battery

    Unknown

  • Probability-Relevant Incipient Fault Detection and Diagnosis Methodology With Applications to Electric Drive Systems

    Hongtian Chen;Bin Jiang;Steven X. Ding;Ningyun Lu

  • Combination method of principal component and wavelet analysis for multivariate process monitoring and fault diagnosis

    Ningyun Lu;Fuli Wang;Furong Gao

  • Digital twin-assisted enhanced meta-transfer learning for rolling bearing fault diagnosis

    Unknown

  • Quality prediction based on phase-specific average trajectory for batch processes

    Chunhui Zhao;Fuli Wang;Zhizhong Mao;Ningyun Lu

  • Multirate dynamic inferential modeling for multivariable processes

    Ningyun Lu;Ningyun Lu;Yi Yang;Furong Gao;Fuli Wang

  • Model Fusion and Multiscale Feature Learning for Fault Diagnosis of Industrial Processes

    Unknown

  • A Newly Robust Fault Detection and Diagnosis Method for High-Speed Trains

    Hongtian Chen;Bin Jiang;Ningyun Lu

  • Adaptive Monitoring Based on Independent Component Analysis for Multiphase Batch Processes with Limited Modeling Data

    Chunhui Zhao;Fuli Wang;Zhizhong Mao;and Ningyun Lu

  • Data-driven and deep learning-based detection and diagnosis of incipient faults with application to electrical traction systems

    Hongtian Chen;Bin Jiang;Tianyi Zhang;Ningyun Lu

Frequent Co-Authors

Bin Jiang
Bin Jiang Nanjing University of Aeronautics and Astronautics
Donghua Zhou
Donghua Zhou Shandong University of Science and Technology

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Related Online Degrees & Career Pathways

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By carefully selecting suitable related online degrees, Mechanical and Aerospace Engineering graduates can diversify their skill sets and explore rewarding new career pathways.

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