VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Application of predictive and machine learning models for mechatronic systems parameters prediction and fault classification“ prepared by VILNIUS TECH, Tadas Žvirblis. The dissertation was prepared in 2018–2022, supervisors – Assoc. Prof. Dr. Artūras Kilikevičius.
The dissertation was defended at the public meeting of the Dissertation Defense Council of Mechanical Engineering in the Senate Hall of Vilnius Gediminas Technical University at 9 a. m. on 13 June 2022.
„This dissertation presents statistical models for predicting ecological and energetic parameters of internal combustion engine and machine learning models for identifying failures of a mechatronic system. The presented models are based on vibration and sound pressure signals emitted by mechatronic systems. Machine learning models are applied to identify hypoid gear faults and conveyor belt load states, but the same algorithms can be applied to other rotating mechanisms.“
Doctoral dissertation readers can search via VILNIUS TECH Virtual Library