Student thesis: Master thesis (including HD thesis)

  • Dominik Marija Rebic
4. semester, Sustainable Energy Engineering, Master (Master Programme)
This Thesis investigates the application of Fault Detection and Diagnosis (FDD). Experiments were performed on the hydraulic crane setup at the Hydraulics Laboratory at the AAU Esbjerg Campus.
Hydraulic and mechanical models of the system in question were obtained. Simulated and experimental data were compared and mathematical non-linear model was validated.
System modeling and validation is done for the non-faulty system, later introduced with the faults, i.e. internal and external leakage.
Since the main objective of the Thesis is to detect said faults, Extended Kalman Filter (EKF) is applied in a form of State Augmented Extended Kalman Filter (SAEKF). Leakage coefficients are chosen for augmented states. Performance of the chosen method is investigated and discussed.
Publication date2019
Number of pages38
ID: 304810222