Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item DQ modeling of induction motor for virtual flux measurement(2010) Sushma, P.; Rajalakshmi Samaga, R.; Vittal, K.P.Three phase induction motors are continuing to remain as work horses in industrial applications. The accurate behavioral modeling of induction motor helps in designing controller for the machine and also useful in detection of faults in machines. Almost all faults in the induction motor affect the flux in the air gap. These fluxes can be measured virtually using dq model of induction motor by feeding voltage and current values extracted in real time and stored. In this paper, DQ model is developed in stator reference frame using MATLAB-SIMULINK platform and a data acquisition system supported with LabVIEW is used to obtain motor terminal voltage and current signals which are useful in estimation of flux in an actual machine. ©2010 IEEE.Item Air gap mixed eccentricity severity detection in an induction motor(2011) Rajalakshmi Samaga, R.; Vittal, K.P.Non invasive fault detection unit for an induction motor has become an integral part of industrial drives. As the current is the primary quantity to get affected by the non uniform air gap flux, Motor Current Signature Analysis is preferred as compared to vibration analysis for mixed eccentricity fault detection in an induction motor. In this paper, Power Spectral Density analysis is performed on the stator current data samples obtained from modeling and simulation of the induction motor. An Eccentricity Severity Factor is defined and is shown that this factor increases with increase of air gap eccentricity in the machine. Hence it can be used as a measure to assess the degree of eccentricity in the machine. © 2011 IEEE.Item Hydrological modeling of stream flow over netravathi river basin(Springer Science and Business Media Deutschland GmbH, 2021) Ashish, S.; Kundapura, S.; Kaliveeran, V.Riverine resources which are the basis of life are being transformed through urbanization. This has to be analyzed effectively in order to rejuvenate riverine ecosystems. The effects of land-use dynamics are a factor to be analyzed, and using hydrological modeling which is adopted in this study aids for the same. Soil and Water Assessment Tool (SWAT) is used as an effective tool in modeling the river basin due to its ability to quantify the alternate input data provided to the model. 14-year daily data was simulated in the model provided; the warm-up period for the model is 2 years. Coefficient of determination value of 0.74 and Nash–Sutcliffe efficiency (NSE) to be 0.71 were obtained from the analysis which indicate that the simulated values fall within a good range. The parameters which influence most are found to be curve number, available water capacity in the soil, groundwater delay, Manning’s n and plant uptake compensation. The fitted range was obtained, and this was used to increase the accuracy in SWAT Calibration and Uncertainty Procedures (SWAT-CUP). Sequential Uncertainty Fitting ver.2 (SUFI2) was found to be effective because of its uncertainty consideration criteria, and it accounts for all uncertainties that may occur in the mode. Hydrological modeling of a river basin can help us to assess the impact of alternative input data on the stream flow. © Springer Nature Singapore Pte Ltd 2021.Item A Review on Application of Soft Computing Techniques in Geotechnical Engineering(Springer Science and Business Media Deutschland GmbH, 2024) Thotakura, T.V.; Sireesha, M.; Sunil, B.M.; Alisha, S.S.Numerous test results, mathematical relationships, and in-the-moment analysis and design are all components of geotechnical issues. Additionally, due to smart infrastructure and materials, the research trend in engineering nowadays is shifting toward intelligent tools and their ability to tackle engineering problems. Artificial neural networks (ANN), support vector machines (SVM), genetic algorithms (GA), and particle swarm optimization algorithms (PSO), among other soft computing techniques, have made significant progress in recent years in solving geotechnical issues. Based on a review of more than 800 published research, this study discusses the applicability of soft computing techniques in the current environment. Traditional methods, such as regression analysis and trial-and-error techniques, take time and could be more effective. Additionally, most geotechnical designs require considerable experimental data and may require laborious work. A novel methodology for soft computing approaches has emerged to solve the problems mentioned above. This paper presents soil problems and geotechnical challenges while examining recent developments and the potential applications of soft computing. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.