World's Best Scientists 2026 revealed!
Siliang Lu

Siliang Lu

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Rising Stars
2025

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Rising Stars 34 881 878 286 286 107 3798
Mechanical and Aerospace Engineering 36 2560 2397 310 309 117 4602

Siliang Lu publications per year

The chart shows the history of publications by Siliang Lu between 2000 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Siliang Lu published across 27 years, from 2000 to 2026, averaging 5.4 papers a year. Output peaked at 20 publications in 2016. 9 of the 145 publications appeared in the last two years.

No. of publications
5 10 15 20
Bar chart. Horizontal axis: year, 2000 to 2026. Vertical axis: number of publications, 0 to 20. Peak 20 publications in 2016. 2000: 1 publication 2001: 1 publication 2002: 0 publications 2003: 0 publications 2004: 1 publication 2005: 0 publications 2006: 1 publication 2007: 0 publications 2008: 0 publications 2009: 0 publications 2010: 0 publications 2011: 0 publications 2012: 0 publications 2013: 2 publications 2014: 5 publications 2015: 5 publications 2016: 20 publications 2017: 13 publications 2018: 7 publications 2019: 13 publications 2020: 13 publications 2021: 15 publications 2022: 13 publications 2023: 15 publications 2024: 11 publications 2025: 8 publications 2026: 1 publication
2000 2026

145 publications in total across all disciplines

View publications per year as a table
Siliang Lu: publications per year, 2000 to 2026
Year Publications
2000 1
2001 1
2002 0
2003 0
2004 1
2005 0
2006 1
2007 0
2008 0
2009 0
2010 0
2011 0
2012 0
2013 2
2014 5
2015 5
2016 20
2017 13
2018 7
2019 13
2020 13
2021 15
2022 13
2023 15
2024 11
2025 8
2026 1
Total 145
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Siliang 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 Siliang Lu sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 63 bars. Horizontal axis: publications, 47–56 to 659+. Vertical axis: number of scientists, 0 to 155. Most scientists, 155, have 147–156 publications. The last bar groups every scientist with 659 publications or more. The highlighted bar, 117–126 publications, is where this scientist sits. 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
47–56 publications 659+

This scientist: 117 publications — 12th percentile

12% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Mechanical and Aerospace Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
Publications Scientists This scientist
47–56 10
57–66 23
67–76 32
77–86 62
87–96 67
97–106 91
107–116 113
117–126 115 117
127–136 130
137–146 140
147–156 155
157–166 132
167–176 133
177–186 130
187–196 140
197–206 115
207–216 125
217–226 117
227–236 99
237–246 92
247–256 100
257–266 95
267–276 88
277–286 77
287–296 74
297–306 74
307–316 62
317–326 70
327–336 59
337–346 58
347–356 45
357–366 44
367–376 36
377–386 41
387–396 32
397–406 23
407–416 28
417–426 27
427–436 25
437–446 23
447–456 23
457–466 20
467–476 12
477–486 24
487–496 18
497–506 12
507–516 13
517–526 21
527–536 12
537–546 8
547–556 16
557–566 3
567–576 11
577–586 6
587–596 5
597–606 6
607–616 7
617–626 7
627–636 10
637–646 4
647–656 3
657–658 2
659+ 100
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Siliang 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 Siliang Lu sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 64 bars. Horizontal axis: D-Index, 30 to 93+. Vertical axis: number of scientists, 0 to 189. Most scientists, 189, have 34 D-Index. The last bar groups every scientist with 93 D-Index or more. The highlighted bar, 36 D-Index, is where this scientist sits. 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.

View D-Index distribution as a table
Number of Mechanical and Aerospace Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
D-Index Scientists This scientist
30 83
31 113
32 144
33 153
34 189
35 158
36 139 36
37 127
38 130
39 126
40 104
41 100
42 107
43 101
44 103
45 79
46 88
47 70
48 83
49 44
50 64
51 56
52 50
53 48
54 58
55 52
56 48
57 42
58 34
59 42
60 37
61 42
62 44
63 22
64 33
65 29
66 23
67 29
68 24
69 19
70 34
71 26
72 19
73 18
74 19
75 14
76 19
77 8
78 18
79 16
80 12
81 17
82 11
83 16
84 7
85 9
86 8
87 6
88 6
89 7
90 10
91 4
92 4
93+ 100
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Research.com Recognitions

  • 2025 - Research.com Rising Stars Award

Overview

Siliang Lu is affiliated with Anhui University in China and has contributed extensively to the field of engineering, particularly focusing on areas related to machine fault diagnosis and industrial systems. Their research spans multiple subfields including control and systems engineering, mechanical engineering, electrical and electronic engineering, civil and structural engineering, and industrial and manufacturing engineering.

The scientist's main research topics include:

  • Machine Fault Diagnosis Techniques
  • Non-Destructive Testing Techniques
  • Fault Detection and Control Systems
  • Gear and Bearing Dynamics Analysis
  • Industrial Vision Systems and Defect Detection
  • Structural Health Monitoring Techniques
  • Welding Techniques and Residual Stresses

Siliang Lu has published in several frequent venues, showing a focus on instrumentation and industrial informatics, as well as reliability and sensor technology. These venues include:

  • IEEE Transactions on Instrumentation and Measurement
  • IEEE Sensors Journal
  • IEEE Transactions on Industrial Informatics
  • Reliability Engineering & System Safety
  • IEEE Internet of Things Journal

The scientist's notable recent papers are:

  • Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review, 2023, IEEE Internet of Things Journal
  • Highly Efficient Fault Diagnosis of Rotating Machinery Under Time-Varying Speeds Using LSISMM and Small Infrared Thermal Images, 2022, IEEE Transactions on Systems Man and Cybernetics Systems
  • Hidden Markov Model based Stochastic Resonance and its Application to Bearing Fault Diagnosis, 2022, Journal of Sound and Vibration
  • Intelligent fault diagnosis of machinery using digital twin-assisted deep transfer learning, 2021, Reliability Engineering & System Safety
  • Efficient Data Reduction at the Edge of Industrial Internet of Things for PMSM Bearing Fault Diagnosis, 2021, IEEE Transactions on Instrumentation and Measurement

Frequent coauthors working with Siliang Lu reflect a collaboration network within their research areas. These include:

  • Xiaoxian Wang
  • Juncai Song
  • Yongbin Liu
  • Min Xia
  • Hui Wang

Best Publications

  • A review of stochastic resonance in rotating machine fault detection

    Siliang Lu;Qingbo He;Jun Wang

  • Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review

    Unknown

  • Tacholess Speed Estimation in Order Tracking: A Review With Application to Rotating Machine Fault Diagnosis

    Siliang Lu;Ruqiang Yan;Yongbin Liu;Qunjing Wang

  • Effects of underdamped step-varying second-order stochastic resonance for weak signal detection

    Siliang Lu;Qingbo He;Fanrang Kong

  • Stochastic resonance with Woods-Saxon potential for rolling element bearing fault diagnosis

    Siliang Lu;Qingbo He;Fanrang Kong

  • Fault diagnosis of motor bearing with speed fluctuation via angular resampling of transient sound signals

    Siliang Lu;Xiaoxian Wang;Qingbo He;Fang Liu

  • Online Fault Diagnosis of Motor Bearing via Stochastic-Resonance-Based Adaptive Filter in an Embedded System

    Siliang Lu;Qingbo He;Tao Yuan;Fanrang Kong

  • Bearing fault diagnosis of a permanent magnet synchronous motor via a fast and online order analysis method in an embedded system

    Siliang Lu;Qingbo He;Jiwen Zhao

  • Condition monitoring and fault diagnosis of motor bearings using undersampled vibration signals from a wireless sensor network

    Siliang Lu;Peng Zhou;Xiaoxian Wang;Yongbin Liu

  • Rotating machine fault diagnosis through enhanced stochastic resonance by full-wave signal construction

    Siliang Lu;Qingbo He;Haibin Zhang;Fanrang Kong

  • Optimal design of permanent magnet linear synchronous motors based on Taguchi method

    Juncai Song;Fei Dong;Jiwen Zhao;Siliang Lu

  • Sound-aided vibration weak signal enhancement for bearing fault detection by using adaptive stochastic resonance

    Siliang Lu;Ping Zheng;Yongbin Liu;Zheng Cao

  • Enhanced Rotating Machine Fault Diagnosis Based on Time-Delayed Feedback Stochastic Resonance

    Siliang Lu;Qingbo He;Haibin Zhang;Fanrang Kong

  • Edge Computing: A Promising Framework for Real-Time Fault Diagnosis and Dynamic Control of Rotating Machines Using Multi-Sensor Data

    Gang Qian;Siliang Lu;Donghui Pan;Huasong Tang

  • A novel weak-fault detection technique for rolling element bearing based on vibrational resonance

    Lei Xiao;Xinghui Zhang;Siliang Lu;Tangbin Xia

  • Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis

    Shangbin Zhang;Siliang Lu;Qingbo He;Fanrang Kong

  • A New Methodology to Estimate the Rotating Phase of a BLDC Motor With Its Application in Variable-Speed Bearing Fault Diagnosis

    Siliang Lu;Xiaoxian Wang

  • Novel synthetic index-based adaptive stochastic resonance method and its application in bearing fault diagnosis

    Peng Zhou;Siliang Lu;Fang Liu;Yongbin Liu

  • Feature fusion using kernel joint approximate diagonalization of eigen-matrices for rolling bearing fault identification

    Yongbin Liu;Bing He;Fang Liu;Siliang Lu

  • A Novel Contactless Angular Resampling Method for Motor Bearing Fault Diagnosis Under Variable Speed

    Siliang Lu;Jie Guo;Qingbo He;Fang Liu

  • Stochastic resonance in an underdamped system with FitzHug-Nagumo potential for weak signal detection

    Cristian López;Wei Zhong;Siliang Lu;Feiyun Cong

  • Efficient Data Reduction at the Edge of Industrial Internet of Things for PMSM Bearing Fault Diagnosis

    Xiaoxian Wang;Siliang Lu;Wenbin Huang;Qunjing Wang

  • IoT-Based Signal Enhancement and Compression Method for Efficient Motor Bearing Fault Diagnosis

    Huasong Tang;Siliang Lu;Gang Qian;Jianming Ding

Frequent Co-Authors

Qingbo He
Qingbo He Shanghai Jiao Tong University
Fang Liu
Fang Liu Beihang University
Fanrang Kong
Fanrang Kong University of Science and Technology of China
Clarence W. de Silva
Clarence W. de Silva University of British Columbia
Ruqiang Yan
Ruqiang Yan Xi'an Jiaotong University
Lifeng Xi
Lifeng Xi Shanghai Jiao Tong University
Wenping Cao
Wenping Cao Anhui University
Jérôme Antoni
Jérôme Antoni Institut National des Sciences Appliquées de Lyon
Changqing Shen
Changqing Shen Soochow University
Haidong Shao
Haidong Shao Hunan University

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