Automated Author Profile
Vanoost, Dries
Associatie KU Leuven
0000-0002-7126-9758

Current S-Index

4.3

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

2.1

Average Dataset Index per dataset

Total Datasets

Total datasets for this author

Average FAIR Score

92.3%

Average FAIR Score per dataset

Total Citations

Total citations to the author's datasets

Total Mentions

Total mentions of the author's datasets

S-Index Interpretation

The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.

What it means:

A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
It provides a single number to track your research data impact over time

Current S-Index: 4.3 (sum of 2 datasets Dataset Index scores)

More information here.

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Electrical Signature Analysis Data of a Rotor-Eccentric 1.1 kW Induction Motor (Version: 1.1)

Datasets of time values, phase, ground, neutral and line voltages and current measurements of a modified 1.1 kW Cantoni 2SIEL 80-2B induction machine supplied using an Inverto IFC5.5-MP/460 frequency drive and measured using the Pqube 3 Travel power quality analyser. Faulty bearings and eccentric rotor positions are measured. The presence of broken rotor bars has been detected by motor inductance, resistance, and current analysis.

Authors

Desenfans, Philip ;
Vanoost, Dries ;
Pissoort, Davy

0 Citations0 Mentions92% FAIR2.3 Dataset Index

10.48804/d5mmtvJanuary 2024

Replication Data for: Modelling mechanical faults in induction motors using magnetic equivalent circuits and lumped-element shaft-bearing dynamics (Version: 1.0)

A magnetic equivalent circuit induction motor model is combined with a lumped-element rotor dynamics model. Their combination is analysed for (i) rotor position, (ii) rotor acceleration, (iii) unbalanced magnetic pull, (iv) bearing acceleration, and (v) stator currents in the presence of the following mechanical faults: (i) no-fault case, (ii) a stator outer race misalignment, (iii) a rotor mass unbalance, (iv) a bearing outer race spall fault, (v) a bearing inner race spall fault, (vi) a bearing ball spall fault. The dataset is stored as the complete state and input time-series of both models. Additionally, the dq-transformed stator currents are provided.