Scientific Highlights in Q2-2021

Phd defenses

WP4.1 Savin Viswanathan (NTNU), defended on May 11.

WP3.5 Thilina Nuwan Weerasinghe, defended on May 25.

Link to all completed Phd defences

Accepted scientific publications

Journal Papers:

J5: Dipendra Subedi, Ilya Tyapin and Geir Hovland: ”Dynamic Modeling of Planar Multi-Link Flexible Manipulators”, MDPI Robotics, May 2021.

J6: Shanbhag, V. V., T. J. J. Meyer, L. W. Caspers and R. Schlanbusch (2021). Failure Monitoring and Predictive Maintenance of Hydraulic Cylinder – A State of Art Review. IEEE/ASME Transactions on Mechatronics. Published.

J7: Shanbhag, V. V., T. J. J. Meyer, L. W. Caspers and R. Schlanbusch (2021). Defining acoustic emission-based condition monitoring indicators for monitoring piston rod seal and bearing wear in hydraulic cylinders. The International Journal of Advanced Manufacturing Technology. Published.

J8: Falconer, S., E. Nordgård-Hansen and Geir Grasmo (2021). Remaining useful life estimation of HMPE rope through machine learning. To appear in Ocean Engineering. Accepted with comments.

J9: Joacim Dybedal and Geir Hovland, “CNN-based People Detection in Voxel Space using Intensity Measurements and Point Cluster Flattening”, Modeling, Identification and Control, 2021, Vol 42, No. 2, pp. 37-46.

J10: Savin Viswanathan, Christian Holden, Olav Egeland and Marilena Greco, “An Open-Source Python-Based Boundary-Element Method Code for the Three-Dimensional, Zero-Froude, Infinite-Depth, Water-Wave Diffraction-Radiation Problem”, Modeling, Identification and Control, 2021, Vol 42, No. 2, pp. 47-81.

Conference Papers:

C3: Kandukuri, S. T., V. V. Shanbhag, T. J. J. Meyer, L. W. Caspers, N. S. Noori, R. Schlanbusch (2021). Automated and Rapid Seal Wear Classification Based on Acoustic Emission and Support Vector Machine. PHM Society European Conference. Accepted.

Link to all publications in 2021

New dataset submitted to Dataverse.no

A new dataset was recently submitted to the SFI Offshore Mechatronics repository in Dataverse.no. Submitting data to a repository like Dataverse.no is an important effort towards Findable, Accessible, Interoperable and Reusable data. Datasets which are published in Dataverse.no gets a uniqe DOI reference which can be referenced in publications.

The dataset published was generated related to research in WP3. The data contains both the raw point cloud data from an outdoor test site, as well as generated images used for training. PhD fellow Joacim Dybedal used the data to train and test a classifier to detect people.

The research results based on the dataset are published in the paper “CNN-based People Detection in Voxel Space using Intensity Measurements and Point Cluster Flattening” (Joacim Dybedal and Geir Hovland, Modeling, Identification and Control, 2021, Vol 42, No. 2, pp. 37-46.).