Defect identification in Concrete Sleepers and Slab Tracks.

Kurzbeschreibung / Ausgangslage/ Project Description.

Information regarding tracks are collected by SBB using a dedicated imaging system mounted on diagnostic vehicles. The resulting images are scanned for identification of non-conformities. A prototype model has been developed to identify cracks and spalling on concrete sleepers and slab tracks. Reliable information on the state of these assets is of importance for traffic safety and for maintenance planning.

Aufgabenstellung / Ziele / Objectives.

Improve/develop models to increase the identification performance of defects in concrete sleepers and slab tracks. Concretely, the project includes the use of supervised machine learning libraries, e.g. TensorFlow 2, to identify said defects in images.

Anforderungen /Requirements (Studienrichtung, Studiendauer).

Master student in Engineering, Machine Learning, Statistics, Mathematics, Physics

Machine Learning and/or Software development background.

Fachgebiet / Themen.

Ingenieurwesen / Technik

Ort.

Bern

Zeitraum.

4-6 Months

Sprachkenntnisse / Languages.

Deutsch, English

Kontaktadresse / Contact.

Lucian Ancu (I-VU-UEW-MUD-TEN), lucian-stefan.ancu@sbb.chLink öffnet in neuem Fenster.

Form der Bewerbung und gewünschte Dokumente / Application Documents.

Lebenslauf, Curriculum Vitae

Weiterführender Inhalt