Blar i Faculty of Engineering and Science på forfatter "Kandukuri, Surya Teja"
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Assessment of synthetic winds through spectralmodeling and validation using FAST
Chougule, Abhijit; Kandukuri, Surya Teja; Beyer, Hans-Georg (Journal article; Peer reviewed, 2016)In this paper, we analyse the simulated and measured wind data with respect to their spectral characteristics and their effect on wind turbine loads. The synthetic data is generated from a stochastic full-field turbulent ... -
Automated and Rapid Seal Wear Classification Based on Acoustic Emission and Support Vector Machine
Kandukuri, Surya Teja; Shanbhag, Vignesh Vishnudas; Meyer, Thomas; Caspers, Leo; Noori, Nadia; Schlanbusch, Rune (Peer reviewed; Journal article, 2021)Seal wear in hydraulic cylinders results in fluid leakage, and instability of the piston rod movement. Therefore, regular inspection of seals is required using automated approaches to improve productivity and to reduce ... -
Automated and Rapid Seal Wear Classification Based on Acoustic Emission and Support Vector Machine
Kandukuri, Surya Teja; Shanbhag, Vignesh Vishnudas; Meyer, Thomas; Caspers, Leo; Noori, Nadia; Schlanbusch, Rune (Peer reviewed; Journal article, 2021) -
Data driven approach for the management of wind and solar energy integrated electrical distribution network with high penetration of electric vehicles
Mathew, Manuel Sathyajith; Kolhe, Mohan Lal; Kandukuri, Surya Teja; Omlin, Christian Walter Peter (Peer reviewed; Journal article, 2023)With the increased penetration of fluctuating renewables and growing population of contemporary loads such as electric vehicles, the uncertainties in the generation and demand in the electric power grids are increasing. ... -
Data Driven Seal Wear Classifications using Acoustic Emissions and Artificial Neural Networks
Noori, Nadia; Shanbhag, Vignesh Vishnudas; Kandukuri, Surya Teja; Schlanbusch, Rune (Peer reviewed; Journal article, 2022)The work presented in this paper is built on a series of experiments aiming to develop a data-driven and automated method for seal diagnostics using Acoustic Emission (AE) features. Seals in machineries operate in harsh ... -
Estimation of Wind Turbine Performance Degradation with Deep Neural Networks
Mathew, Manuel Sathyajith; Kandukuri, Surya Teja; Omlin, Christian Walter Peter (Journal article; Peer reviewed, 2022)In this paper, we estimate the age-related performance degradation of a wind turbine working under Norwegian environment, based on a deep neural network model. Ten years of high-resolution operational data from a 2 MW wind ... -
Rapid Diagnosis of Induction Motor Electrical Faults using Convolutional Autoencoder Feature Extraction
Husebø, Arild Bergesen; Kandukuri, Surya Teja; Klausen, Andreas; Huynh, Khang; Robbersmyr, Kjell Gunnar (Journal article; Peer reviewed, 2020) -
Sensitivity Analysis Of Online Oil Quality Monitoring For Early Detection Of Water Ingress In Marine Propulsion Systems
Klausen, Andreas; Kalaoja, Johannes; Kandukuri, Surya Teja; Robbersmyr, Kjell Gunnar (Peer reviewed; Journal article, 2020)Gearboxes are critical equipment in the vessel propulsion system. Lubrication contamination caused by water ingress or condensation is one of the major failure modes in marine gearboxes leading to accelerated aging of ... -
Towards farm-level health management of offshore wind farms for maintenance improvements
Kandukuri, Surya Teja; Robbersmyr, Kjell G; Karimi, Hamid Reza (Journal article; Peer reviewed, 2015)