Marjorie Hoegen

Software developer Jan 2022 -

Fundação CERTI

Working at an institute of science, research and innovation as a software developer. Currently collaborating in a project for Lenovo to develop a mobile application. Developing software using Flutter. Using Git for version control.

Research Assistant on R&D Project Nov 2019 - Oct 2021

Universidade Federal de Santa Catarina

Worked as a research team member in the project entitled: Non-Invasive Equipment for Fault Detection in Synchronous Generators through the External Magnetic Field.

• Researched, implemented and tested different anomaly detection techniques.
• Analysed a large amount of experimental and synthetic data from synchronous generators.
• Documented and presented main results.

Undergraduate Research Assistant Jan 2017 - Jul 2019

Universidade Federal de Santa Catarina

Worked on 3 projects on GRUCAD (Design and Analysis of Electromagnetic Devices Research Group).

1. Magneto-elastic behaviour modeling of ferromagnetic materials for the simulation of devices

• Researched about the microscopic structure of ferromagnetic materials.
• Reviewed and compared multiscale approaches for magneto-elastic behaviour modelling.
• Evaluated numerical models implemented in FreeFemm++ to describe the magneto-elastic behaviour of ferromagnetic materials.

2. Study of a feedback loop implemented in FPGA

• Assisted the design of an equipment for magnetic characterisation tests using an SoC FPGA.
• Implemented communication protocol in Verilog.
• Studied sliding mode control (SMC).
• Developed programs in C to run on an ARM embedded Linux communicating with the FPGA.
• Programmed a client-server model for communication between ARM and PC.

3.Study of synchronous machines and incipient faults detection

• Developed a Virtual Instrument (VI) in LabVIEW for magnetic field spectrum analysis of synchronous generators.
• Analysed data from fault imposition tests with an experimental test bench.

Universidade Federal de Santa Catarina 2019 - 2021

Field of study: Electrical Engineering
Degree: MsC

• Dissertation title: Strategies for Detecting Changes in the Behaviour of the External Magnetic Field of Synchronous Generators.
• Analysed the machine’s external magnetic field spectrum through statistical and machine learning techniques such as Kullback-Leibler divergence (KLD), principal component analysis (PCA), singular spectrum analysis (SSA) and neural networks. These different methods, implemented in Python, were compared and evaluated for its application in an online monitoring system.
• Modules: electromechanical energy conversion, electric and magnetic materials, finite element method (FEM) for 2D and 3D electromagnetic applications, FEM for electric machines.