The characterisation of a drive train test rig to engineer a tidal stream turbine condition-based maintenance strategy

Rojo Zazueta, Edith 2022. The characterisation of a drive train test rig to engineer a tidal stream turbine condition-based maintenance strategy. PhD Thesis, Cardiff University. Item availability restricted.

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Abstract

This research examines the development and validation of a condition monitoring technique using a 1/20th turbine scaling drive train test rig. The capability of the test rig was assessed operating under steady and unsteady state simulations. The steady state turbine operation was developed by considering the theoretical mean values of previously validated Computer Fluid Dynamics of Horizontal Axis Tidal Turbine (HATT) models. The unsteady state turbine operation was obtained from a experimental test campaign conducted in a flume tank. A range of fluid time series were built in order to incorporate further complex tidal profile conditions. The work undertaken to demonstrate the test rig capability to emulate both steady state and unsteady state turbine operations was successful. The test rig was able to replicate the torque and rotational speed in both the rotor and the generator. The work then progressed in order to determine the test rig reliability to assess the CM algorithm effectiveness. The condition monitoring technique engineered in this research is a frequency signal processing tool. This is implemented in a range of tidal operating conditions and differing recorded time lengths. It was able to detect different scales of HATT rotor imbalance faults that occur. It was found that the presence of high turbulent flows and large length scales have a great impact on detecting rotor imbalance faults. A comparison of the detection of the rotor imbalance fault in both the rotor and the generator was considered, and it was shown that the generator side of the test rig can effectively detect different fault scales when a torque-fault time series was implemented. This demonstrates the CM algorithm effectiveness to detect rotor imbalance faults in the generator. This provides confidence in the energy sector to establish further condition monitoring practices that could allow turbine developers to prevent major HATT malfunctions.

Item Type:	Thesis (PhD)
Date Type:	Completion
Status:	Unpublished
Schools:	Engineering
Uncontrolled Keywords:	Tidal Energy Condition Monitoring Test Rig Experimental Analysis Rotor Imbalance Fault Generator Signals
Date of First Compliant Deposit:	6 September 2023
Last Modified:	06 Sep 2023 13:38
URI:	https://orca.cardiff.ac.uk/id/eprint/162260

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