PANNALA KRISHNA MURTHY
@scitr.edu.in
PRINCIPAL
Sri Chaitanya Institute of Technology and Research
Prof. Pannala Krishna Murthy has a Doctorate Degree in Electrical Engineering from JNTU, Hyderabad. Over 55 International Publications to his credit. Two Research Scholars received Ph.D from JNTUH, Hyderabad and SSSUTMS, Sehore M.P. and four Ph.D scholars registered with Universities of Telangana, and Tamilnadu are working under his supervision. He guided more than 43 UG projects and 31 PG projects. He is a Fellow Member IE India, J.Cs.
and Senior Member IEEE, Life member, APSMS, ISTE, New Delhi and also Member IRC Scientific and Technical Committee & Editorial Review Board on Electrical and Computer Engineering (WASET).
He took over as Principal, SBIT, Khammam from 1.1.2013 to 4.5.2019. Now, working as Principal, SCIT, Khammam formerly known w.e.f. 01.07.2019.
He R&D activities in association with the industries as Advisor, CANORX® Software Services Pvt. Ltd., since 25th March, 2020.
EDUCATION
PhD: Power Electronics & Power systems from, JNTUH, Hyderabad 2010
PG - M.Tech.: ITPE, JNTUCE, Hyderabad. 2003
UG - BE: EEE, SSGMCE, Shegaon. Amaravathi University, Maharashtra, 1999
RESEARCH, TEACHING, or OTHER INTERESTS
Electrical and Electronic Engineering, Computer Engineering, Multidisciplinary
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Shrikant S. Mopari, D.S. More, A.S. Bhalchandra, Pannala Krishna Murthy, K.M. Jadhav, and R.C. Kamble
Elsevier BV
Shrikant S. Mopari, More D S, Bhalchandra A S, Pannala Krishna Murthy, and Jadhav K M
Seventh Sense Research Group Journals
- The Oil-Impregnated Paper (OIP) insulation is commonly utilized as the foremost insulation type in the case of a converter transformer, which is constantly and unavoidably affected by elevated temperature and different stresses arising during the mode of operation. It causes a safety risk to the insulation system of the converter transformer. Because of this, the present study examines the effect on OIP insulation using the FDS technique as a function of frequency and elevated temperature. The Frequency Domain Spectroscopy (FDS) and Atomic Force Microscopy (AFM) techniques were carried out for condition evaluation and surface morphological changes of OIP insulation. The experimental results show that elevated temperature viz 30°C, 50°C, 70°C, 90°C, 110°C and 130°C produces irreversible damage to the surface of OIP, which can lead to morphological changes. The frequency-dependent permittivity studies also confirm the deterioration of OIP insulation as permittivity decreases with increased frequency. However, the synergistic effect generated on the OIP insulation can also be analyzed by image processing-based evaluation methods dependent on the average of four local areas of AFM images. One disk of a valve side star winding single phase converter transformer is developed in MATLAB Simulink. An impulse of 20kV, 1.2/50µsec is applied to study the correlation among insulation degradation across the turn by considering elevated temperature and frequency dependence of OIP insulating material by wavelet transform. The energy of the wavelet coefficient is utilized to analyze the insulation degradation of insulation of the converter transformer. Thus the effectiveness of the FDS study revealed the condition monitoring of converter transformer insulation, and the presented results agree with the published work.
Shrikant S. Mopari, D. S. More, Pannala Krishna Murthy, and M. P. S. Chawla
IEEE
The converter transformers are key equipment in DC power transmission systems. The power system security is greatly influenced by converter transformer insulation. As compared to conventional transformers, electric field distribution is more complex in converter transformers. Hence electric field and its distribution play a crucial role for optimal design and manufacturing process of converter transformer. In this paper a single phase converter transformer equivalent circuit model with dual winding has been established. The electric field simulation is carried out with the help of 2D finite element method (FEM). The insulation strength can be tested by conducting a DC test on valve side winding. Also, ANSYS Maxwell simulation platform is used for calculating converter transformer winding parameters. The present approach permits a faster and more precious method for modeling of converter transformer winding.
S. Neelima, N. Satyanarayana, and P. Krishna Murthy
IEEE
Discovering interesting rules has become a basis for proficient decision making from past decades. Numbers of mining techniques are used for generating association rules. Apriori is one of the mining techniques for discovering association rules. Optimization of rules has become an important task as apriori generates plenty of rules. In this paper, Multi Objective Adaptive Weight Firefly (MOAWF) algorithm is proposed for association rule optimization and the proposed algorithm is applied on the rules generated using apriori. Here association rule mining is viewed as a multi-objective problem instead of single objective. Confidence, support and comprehensibility are considered for measuring multi-objective. The performance of proposed algorithm is better when compared to the existing algorithms.
S. Neelima, N. Satyanarayana, and P. Krishna Murthy
IEEE
One of the major tasks of data mining is association rule mining, which is used for finding the interesting relationships among the items in itemsets of huge database. Aproiri is the familiar algorithm of association rule mining for generating frequent itemsets. Apriori uses minimum support threshold to find frequent items. In this paper, an algorithm called hybridization of ABC with BAT algorithm is proposed which is used for optimization of association rules. Instead of onlooker bee phase of ABC, random walk of BAT is used in order to increase the exploration. Hybridized ABC with BAT algorithm is applied on the rules generated from apriori algorithm, for optimizing association rules. The experiments are performed on datasets taken from UCI repository which show the proposed work performance and proposed methodology can effectively optimize association rules when compared to the existing algorithms. In the paper, we also proved that the rules generated using proposed work are simple and comprehensible.
Pannala Krishna Murthy, J. Amarnath, S. Kamakshiah, and B.P. Singh
IEEE
Wavelet transform has received greater attention in fault analysis due to its ability in analyzing the travelling waves than conventional methods of analysis. In this paper, the method using wavelet transforms for detecting a HVDC transmission line faults is proposed after simulating the HVDC system for various faults. The simulation results show that the application of wavelet technique leads to a more reliable solution for recognition of faults and provides a good basis for the new protection scheme for the HVDC lines.
Sarabu Neelima, Nallamothu Satyanarayana, and Pannala Krishna Murthy
Springer Singapore