Author(s): Sailesh Chitrakar; Hari Prasad Neopane

Linked Author(s):

Keywords: No Keywords

Abstract: This paper presents a part of the research works related to early stage fault detection and diagnosis of hydraulic turbines. The research works are currently focused on creating a database of the distinctive signals of the faults in the turbine through CFD investigations. The faults in the turbine are induced based on experience and literature review of the common sediment erosion patterns. In the case of Pelton turbines, erosion in the needle with ripple and groove shapes and wavy scales on the buckets are found to be the most common erosion patterns. This paper focuses on asymmetrical erosion patterns of buckets and the needle caused due to flow obstruction in nozzle and consequent misalignment of the jet. The partial blockage for CFD is modelled as a sector of an annulus distributed around the needle. Velocity, pressure, output torque and erosion rates on the needle and buckets are studied. By integrating the trend analysis with machine learning techniques, a real-time condition monitoring tool and procedure can be developed. Since a predictive maintenance of the turbines can be implemented, the outcomes of these research works can have a commercial value for sediment affected power plants globally.

DOI: https://doi.org/10.1088/1755-1315/1411/1/012007

Year: 2024