Jan Helsen

2.1k total citations
113 papers, 1.3k citations indexed

About

Jan Helsen is a scholar working on Control and Systems Engineering, Mechanical Engineering and Civil and Structural Engineering. According to data from OpenAlex, Jan Helsen has authored 113 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Control and Systems Engineering, 62 papers in Mechanical Engineering and 27 papers in Civil and Structural Engineering. Recurrent topics in Jan Helsen's work include Machine Fault Diagnosis Techniques (54 papers), Gear and Bearing Dynamics Analysis (45 papers) and Structural Health Monitoring Techniques (27 papers). Jan Helsen is often cited by papers focused on Machine Fault Diagnosis Techniques (54 papers), Gear and Bearing Dynamics Analysis (45 papers) and Structural Health Monitoring Techniques (27 papers). Jan Helsen collaborates with scholars based in Belgium, United States and France. Jan Helsen's co-authors include Cédric Peeters, Patrick Guillaume, Jérôme Antoni, Wim Desmet, Frederik Vanhollebeke, Dirk Vandepitte, Timothy Verstraeten, Ann Nowé, Quentin Leclère and Steven B. Leeb and has published in prestigious journals such as Renewable and Sustainable Energy Reviews, Scientific Reports and Applied Energy.

In The Last Decade

Jan Helsen

99 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jan Helsen Belgium 17 804 730 279 231 188 113 1.3k
W.Y. Liu China 14 753 0.9× 396 0.5× 223 0.8× 207 0.9× 206 1.1× 32 1.1k
Xuejun Li China 21 801 1.0× 773 1.1× 229 0.8× 384 1.7× 152 0.8× 134 1.5k
Zhinong Jiang China 22 1.1k 1.4× 819 1.1× 190 0.7× 430 1.9× 113 0.6× 78 1.5k
Shuangwen Sheng United States 19 797 1.0× 624 0.9× 201 0.7× 283 1.2× 240 1.3× 73 1.3k
Chul Ki Song South Korea 10 663 0.8× 359 0.5× 351 1.3× 131 0.6× 185 1.0× 31 1.0k
Zhencai Zhu China 21 981 1.2× 735 1.0× 153 0.5× 578 2.5× 93 0.5× 121 1.5k
Zhousuo Zhang China 17 790 1.0× 534 0.7× 316 1.1× 367 1.6× 77 0.4× 65 1.2k
Dezun Zhao China 21 1.1k 1.4× 692 0.9× 163 0.6× 336 1.5× 108 0.6× 47 1.4k
Eric Bechhoefer United States 22 1.3k 1.6× 920 1.3× 263 0.9× 333 1.4× 144 0.8× 98 1.7k
Dingguo Lu United States 11 824 1.0× 400 0.5× 216 0.8× 109 0.5× 319 1.7× 17 1.0k

Countries citing papers authored by Jan Helsen

Since Specialization
Citations

This map shows the geographic impact of Jan Helsen's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jan Helsen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jan Helsen more than expected).

Fields of papers citing papers by Jan Helsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jan Helsen. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jan Helsen. The network helps show where Jan Helsen may publish in the future.

Co-authorship network of co-authors of Jan Helsen

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Helsen. A scholar is included among the top collaborators of Jan Helsen based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jan Helsen. Jan Helsen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Peeters, Cédric, et al.. (2025). Enhancing instantaneous angular speed estimation with an adaptive Multi-Order Probabilistic Approach. Mechanical Systems and Signal Processing. 226. 112322–112322. 1 indexed citations
2.
Nejad, Amir R., et al.. (2025). Wind turbine blade root and blade bearing fatigue damage estimation based on field data. Forschung im Ingenieurwesen. 89(1).
3.
Verstraeten, Timothy, et al.. (2025). Scalable SCADA-driven failure prediction for offshore wind turbines using autoencoder-based NBM and fleet-median filtering. Wind energy science. 10(11). 2615–2637.
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6.
Antoni, Jérôme, et al.. (2024). On the design of Optimal Health Indicators for early fault detection and their statistical thresholds. Mechanical Systems and Signal Processing. 218. 111518–111518. 15 indexed citations
7.
Peeters, Cédric, et al.. (2024). Fatigue crack detection in planetary gears: Insights from the HUMS2023 data challenge. Mechanical Systems and Signal Processing. 212. 111292–111292. 7 indexed citations
8.
Verma, Amrit Shankar, et al.. (2024). Modeling of rain-induced erosion of wind turbine blades within an offshore wind cluster. Journal of Physics Conference Series. 2875(1). 12040–12040. 1 indexed citations
9.
Verstraeten, Timothy, et al.. (2023). Effect of curtailment scenarios on the loads and lifetime of offshore wind turbine generator support structures. Journal of Physics Conference Series. 2507(1). 12013–12013. 5 indexed citations
10.
Peeters, Cédric, Andreas Jakobsson, Jérôme Antoni, & Jan Helsen. (2023). Exploring the potential of sparse spectral estimation for vibration analysis. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
11.
Verstraeten, Timothy, et al.. (2023). Wind Power Prediction using Multi-Task Gaussian Process Regression with Lagged Inputs. Journal of Physics Conference Series. 2505(1). 12035–12035. 3 indexed citations
12.
Baere, Dieter De, et al.. (2023). Experimental evaluation of the metal powder particle flow on the melt pool during directed energy deposition. Journal of Laser Applications. 35(2). 4 indexed citations
13.
Verstraeten, Timothy, et al.. (2023). Overview of normal behavior modeling approaches for SCADA-based wind turbine condition monitoring demonstrated on data from operational wind farms. Wind energy science. 8(6). 893–924. 23 indexed citations
14.
Peeters, Cédric, et al.. (2022). Fleet-based early fault detection of wind turbine gearboxes using physics-informed deep learning based on cyclic spectral coherence. Mechanical Systems and Signal Processing. 185. 109760–109760. 46 indexed citations
15.
Peeters, Cédric, Jérôme Antoni, Quentin Leclère, Timothy Verstraeten, & Jan Helsen. (2021). Multi-harmonic phase demodulation method for instantaneous angular speed estimation using harmonic weighting. Mechanical Systems and Signal Processing. 167. 108533–108533. 36 indexed citations
16.
Helsen, Jan, Yi Guo, & Jonathan Keller. (2018). Gearbox high‐speed‐stage bearing slip induced by electric excitation in a test facility. Wind Energy. 21(11). 1191–1201. 5 indexed citations
17.
Peeters, Cédric, Patrick Guillaume, & Jan Helsen. (2016). Vibration-based bearing fault detection on experimental wind turbine gearbox data. PHM Society European Conference. 3(1). 2 indexed citations
18.
Helsen, Jan, et al.. (2011). Updated flexible multibody wind turbine drivetrain model to determine excitation inputs for acoustic calculations. Wind Energy. 1 indexed citations
19.
Helsen, Jan, Frederik Vanhollebeke, Dirk Vandepitte, & Wim Desmet. (2010). Optimized inclusion of flexibility in wind turbine gearbox multibody model in view of model updating on dynamic test rig. Lirias (KU Leuven). 4 indexed citations
20.
Helsen, Jan, et al.. (2010). Multibody modelling of varying complexity for modal behaviour analysis of Wind Turbine Gearboxes. Journal of Sound and Vibration. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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