Pramod Bangalore

Doktorand at Department of Energy and Environment, Electric Power Engineering

Pramod Bangalore works as a PhD student in the department of Electric Power Engineering. His research focuses on Maintenance Management of wind turbines. The main aim of the project is to reduce the cost of maintenance in wind turbines using innovative strategies and failure prognosis algorithms. The focus will be on using SCADA alarms as indicators for impending failure. The results might be useful for wind power plant operators and owners. Reduction in maintenance cost will result in reduction of Life Cycle Cost of the wind power plants thereby making them more lucrative to the investors.

Source: chalmers.se

Projects

2015–2018

Development of mathematical optimization models and methods towards a successful integration of production and condition-based multi-component maintenance in the wind power industry

Michael Patriksson Department of Mathematical Sciences, Mathematics
Ann-Brith Strömberg Department of Mathematical Sciences, Mathematics
Pramod Bangalore Department of Energy and Environment, Electric Power Engineering
Quanjiang Yu Unknown organization
Swedish Research Council (VR)

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Publications

2017

An artificial neural network based condition monitoring method for wind turbines, with application to the monitoring of the gearbox

Pramod Bangalore, Simon Letzgus, Daniel Karlsson et al
Wind Energy
Scientific journal article - peer reviewed
2017

An artificial neural network based condition monitoring method for wind turbines, with application to the monitoring of the gearbox

Pramod Bangalore, Michael Patriksson, Simon Letzgus et al
Wind Energy
Scientific journal article - peer reviewed
2016

Analysis of SCADA data for early fault detection with application to the maintenance management of wind turbines

Pramod Bangalore, Michael Patriksson, Lina Bertling Tjernberg et al
Cigre Session 46
Conference paper - peer reviewed
2016

Load and risk based maintenance management of wind turbines

Pramod Bangalore,
Doctoral thesis
2015

An Artificial Neural Network Approach for Early Fault Detection of Gearbox Bearings

Pramod Bangalore, Lina Bertling,
IEEE Transactions on Smart Grid. Vol. 6 (2), p. 980-987
Scientific journal article - peer reviewed
2014

Self Evolving Neural Network Based Algorithm for Fault Prognosis in Wind Turbines : A Case Study

Pramod Bangalore, Lina Bertling Tjernberg,
2014 International Conference on Probabilistic Methods Applied to Power Systems (Pmaps)
Conference paper - peer reviewed
2014

Cost Efficient Maintenance Strategies for Wind Power Systems Using LCC

Gloria Puglia, Pramod Bangalore, Lina Bertling Tjernberg et al
2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014; Durham; United Kingdom; 7 July 2014 through 10 July 2014, p. Art. no. 6960591
Conference paper - peer reviewed
2014

Load and Risk Based Maintenance Management of Wind Turbines

Pramod Bangalore,
Licentiate thesis
2013

An Approach for Self Evolving Neural Network Based Algorithm for Fault Prognosis in Wind Turbine

Pramod Bangalore, Lina Bertling,
IEEE Grenoble Conference PowerTech, POWERTECH 2013; Grenoble; France, p. (article no 6652218)
Conference paper - peer reviewed
2011

Extension of Test System for Distribution System Reliability Analysis with Integration of Electric Vehicles in the Distribution System

Pramod Bangalore, Lina Bertling,
IEEE PES Innovative Smart Grid Technologies Conference Europe. 2nd IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies, ISGT Europe 2011, Manchester, 5 - 7 December 2011, p. Art. no. 6162763
Conference paper - peer reviewed
2011

On the use of reliability test systems: A literature survey

Lina Bertling, Pramod Bangalore, Tuan Le et al
2011 IEEE Power & Energy Society General Meeting, 24 – 28 July 2011, Detroit, Michigan, USA.
Conference paper - peer reviewed