About us
Espace utilisateur
INSTN offers more than 40 diplomas from operator level to post-graduate degree level. 30% of our students are international students.
Professionnal development
Professionnal development
Find a training course
INSTN delivers off-the-self or tailor-made training courses to support the operational excellence of your talents.
Human capital solutions
At INSTN, we are committed to providing our partners with the best human capital solutions to develop and deliver safe & sustainable projects.
Home   /   Thesis   /   Study and exploitation of Barkhausen noise spectral information for the characterization of steels

Study and exploitation of Barkhausen noise spectral information for the characterization of steels

Engineering sciences Factory of the future incl. robotics and non destructive testing Materials and applications Technological challenges


The use of magnetic Barkhausen noise (MBN) measurements for assessing the structural health of magnetic materials has become an important industrial technique the last years. The interest in the application of this technique stems from the strong dependence of the MBN signals on the material microstructure as well as its stress level and its chemical composition.
The development of robust and reliable analysis tools based on MBN signals is however greatly impeded by the complexity of the underline physics and its sensitivity upon the details of the microstructure. Although a number of models has been proposed in the last decades and significant progress has been reported in terms of the understanding of the phenomenon, a complete theory is still lacking.
Due to this lack of understanding and the complexity of the MBN signals, the current state of the art from the non-destructive testing (NDT) perspective is almost entirely based on the measurement and the analysis of the signal envelope. The spectral information although rich in content is ignored at this level. Yet, it has been demonstrated that the MBN spectrum can give rise to classification of the magnetic materials at different universality classes based on microstructural features, notably the degree of disorder.
The proposed Ph.D. aims to contribute in the use of spectrum measurements for the characterisation of magnetic materials, notably steels. Accurate MBN measurements obtained from different microstructures using a dedicated setup (developed in the context of the Ph.D. work) will be analysed and compared with theoretical simulations based on tools previously developed by the host institute in order to
• Validate and fine-tune the theoretical models
• Study the impact of the microstructure (grain size, dislocations) to the spectrum features
• Explore the classification of the considered microstructures in different classes
Starting from well-known model materials (FeSi and FeCo), for which a great amount of published results exist and hence can be used as reference, the study will be then focused on some important industrial steel grades like the interstitial-free (IF) and low-carbon (LC) steels.
The proposed Ph.D. thesis will be jointly directed and supervised by the French atomic and alternative energies commission (commissariat à l'énergie atomique et aux énergies alternatives, CEA) and the CEIT Institute. The main part of the work will be hosted at the CEA research centre at Saclay, France with possible stays at the CEIT institute in San Sebastian, Spain.
The sought candidate profile is compatible with physicists and engineers with a good background in solid-state physics and a solid understanding of electromagnetism. Basic metallurgical notions and a familiarisation with standard laboratory equipment is also expected. Basic programming knowledge will be helpful. The candidate is also assumed to have good communication skills in English.
The candidate will benefit from access to the experimental facilities of both centres, the central CEA library and the CEA transport network as well as the restaurant facilities.


Département d’Instrumentation Numérique
Service de Simulation et Intelligence Artificielle
Laboratoire de Simulation, Modélisation et Analyse
Top envelopegraduation-hatlicensebookuserusersmap-markercalendar-fullbubblecrossmenuarrow-down