Structural Health Monitoring (SHM), Artificial Intelligence (AI), and Advanced Data Analytics are transforming design, operation, and maintenance. To control costs, improve operational reliability, and enhance system availability, AI-driven analytics, in combination with SHM data, enable the transition from scheduled to predictive maintenance, improve asset utilization and contribute to long-term sustainability.
Your role
As a graduate student in structural analysis and machine learning, you will be part of the Environmental Engineering section and have close contact with the teams working with structural mechanics analysis of our radar systems. In this forum you will receive support with software and general working method, as well as be part of our community and team activities. Your own drive will be important to get ahead with the thesis as the technology in subject is a new field for us.
Description of the master thesis
The use of piezoelectric (PZT) sensors as a Structural Health Monitoring (SHM) system is an effective technique to safely monitor defects and damages before they become detrimental and compromise safety. Many studies show that Lamb waves, that are being generated and sensed with piezoelectric transducers (PZT), can be used for damage detection in a SHM system.
A SHM based on Machine Learning is a powerful tool for detection and prediction of damage in composite structures. The aim of the thesis work is to develop a modelling methodology for damage quantification in a composite structure using machine learning and hybrid training.
The master thesis work is divided into three parts: (1) using finite element model to simulate damage scenarios; (2) perform experiment and modify the finite element model with experimental data; (3) using combined numerical and experimental data for machine training.
Your profile
This master thesis is suitable for two students with interest in Applied Mechanics and Machine learning.
This Master Thesis is suitable for two students with interest in Structural analysis in composites, structural health monitoring and machine learning.
You are at the end of your technical master’s education in Applied Mechanics, Engineering Mathematics or similar and about to start your Master Thesis work for 30 HP. Courses in Finite Element Method, Composite Materials and Machine Learning are meriting, as well as practical experience in material testing.
The thesis work will be performed on the section of environmental analysis. The section of environmental analysis is responsible for environmental engineering analysis within structural analysis, thermal analysis and EMC analysis. Our mission is to be a support function to ensure safe and reliable products regarding electronics, mechanics and system structures.
The section is involved from early concept design through defining necessary requirements, perform detail design and structural analysis and finally verify the final product.
This position requires that you pass a security vetting based on the current regulations around/of security protection. For positions requiring security clearance additional obligations on citizenship may apply.
What you will be a part of
Explore a wealth of possibilities. Take on challenges, create smart inventions, and grow beyond. This is a place for curious minds, brave pioneers, and everyone in between. Together, we achieve the extraordinary, each bringing our unique perspectives. Your part matters.
Saab is a leading defence and security company with an enduring mission, to help nations keep their people and society safe. Empowered by its 26,000 talented people, Saab constantly pushes the boundaries of technology to create a safer and more sustainable world.
Saab designs, manufactures and maintains advanced systems in aeronautics, weapons, command and control, sensors and underwater systems. Saab is headquartered in Sweden. It has major operations all over the world and is part of the domestic defence capability of several nations. Read more about us here