During my M.Sc. at the University of Tehran, I developed significant skills in various engineering topics, including vibration analysis, fluid-solid interaction, artificial neural networks, and computational fluid dynamics. I applied this knowledge to create advanced non-invasive fault detection and condition monitoring systems for turbomachinery and diesel engines used in trainsets.
My first project involved developing a novel fault detection method that combined vibration signature analysis from sensors installed on the casings of centrifuge pumps with computational fluid dynamics simulations for interpretation.
The second project was a collaboration between the Noise, Vibration, and Acoustics (NVA) Research Center at the University of Tehran and RAJA Rail Transportation Company in Iran. I co-applied for an external research grant, executed the research, developed the methodologies, and trained RAJA engineers and technicians in conducting fault detection for large trainset diesel engines.
