Strain measurements in model Francis turbine

Objectives:
To conduct strain measurement and pressure pulsations study in model Francis turbine for different operating conditions at laboratory.
To find and quantify the discrepancy in structural response of healthy and faulty Francis model runner.
To use data from sensors into suitable machine-learning algorithm to build a robust program for early fault detection.

Expected Outcomes:
The study will aid in the condition monitoring of hydraulic turbines, which is still a hot topic of research. The structural response of the runner will be evaluated under different operating conditions by using a strain gauge. This will help to understand the response of the runner, especially in off-design conditions and during flow excitations. Along with this, a series of experiments will be performed on the healthy and defective Francis runner models to differentiate their strain signals. Apart from the strain, pressure will also be measured to analyze its correlation with the structural health of the turbine. Additionally, a machine-learning tool will be developed by feeding a normal and anomalous signal to the algorithm,
which will help to give the live health status of the runner and warn about an impending fault.

Supervisors from host and Partner Universities

Hari Prasad Neopane, Ph.D. Prof. Kathmandu University
Sailesh Chitrakar, Ph.D. Asst. Prof. Kathmandu University
Ole Gunnar Dahlhaug, Ph.D. Prof. Norwegian University of Science and Technology

Aaditya Karna
Masters Candidate
Karnaaaditya8@gmail.com
Batch:2023

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