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
13
Scopus Publications
216
Scholar Citations
7
Scholar h-index
4
Scholar i10-index
Scopus Publications
EXPLAINABLE HYBRID MACHINE LEARNING PARADIGM FOR TRUSTWORTHY ADVERSARIAL DEFENSE Journal of Theoretical and Applied Information Technology Journal of Theoretical and Applied Information Technology, 2026 The accuracy of user-generated suggestions is critical, especially in decision-making processes where AI systems play an important role. Explainable AI (XAI) plays a vital role in decision making process as a mechanism for assessing and verifying the validity of these inputs, ensuring that AI models stay correct and reliable. This focus concentrate on how to apply XAI approaches to determine if users provide correct suggestions or attempt to deceive the system, hence improving the accuracy of AI-driven decision-making. This paper recommends a novel hybrid model that incorporates numerous sophisticated techniques, including Noisy Student self-training, Generative Adversarial Networks (GANs), and XAI. The Noisy Student technique enhances model resilience by self-training on noisy data, whereas GANs provide genuine adversarial instances for data augmentation. Ensemble learning and robust optimization techniques improve model resilience, guaranteeing that it can withstand and respond appropriately to hostile inputs. Generally, XAI techniques contribute transparency, allowing for the discovery and mitigation of misleading inputs by clarifying model predictions. This hybrid method not only improves the robustness and accuracy of AI models, but it also sets a new bar for openness in AI systems, addressing both technical and ethical concerns in modern AI applications.
Performance aware algorithm design for elastic resource workflow management of cluster consolidation to handle enterprise big data Sarabu Neelima, Pannala Krishna Murthy, BJD Kalyani Iaes International Journal of Artificial Intelligence, 2024 <span lang="EN-US">Integration and deployment of big data and business analytics application with cloud computing are more attractive as a service and are trending practice. This hybrid workflow is rapidly increasing and will trigger a revolution for enterprise data handling, information retrieval and computing. This paper presents hybrid workflow management framework for big data and multi cloud computing systems in a two-step approach. Linear optimization-based resource assessment algorithm is planned in the first step. Cluster oriented elastic resource allocation and workflow management techniques are concentrated in the second step. This paper also focus on performance evaluation parameters includes execution time, through put with multi task work flow optimization model. The proposed framework is efficiently managed the implementation of hybrid workflows by finetuning the evaluation attributes and provides improvement in terms of response time an average of 6%.</span>
Analysis of converter transformer pressboard insulation degradation under surge using mathematical morphology Shrikant S. Mopari, Dagadu Shankar More, Anjali S. Bhalchandra, Pannala Krishna Murthy, K. M. Jadhav Indonesian Journal of Electrical Engineering and Computer Science, 2024 Nowadays, with the significant expansion of industrial growth, the bulk power requirement can only be satisfied through high-voltage direct current HVDC transmission. The converter transformer is the utmost vital part of the HVDC transmission. Pressboard insulation is most commonly used as inter-disc insulation in converter transformers. During working conditions due to elevated temperature and different operational stresses, insulation material gets deteriorated. It may cause a risk to the life of the converter transformer. The effects of elevated temperatures as well as frequency on pressboard insulation of the converter transformer are examined in this study. The condition evaluation and morphological changes in pressboard insulation at elevated temperatures can evaluate with the help of frequency domain spectroscopy (FDS) and atomic force microscopy (AFM) techniques. The impact of elevated temperatures on insulation material can be analyzed based on surface roughness and dielectric parameters. In MATLAB Simulink environment, a dual winding single-phase converter transformers valve side star winding 60 discs model is constructed for impulse test. Based upon arrival time and velocity of traveling wave, insulation degradation location can be identified by using mathematical morphology. The simulation results demonstrate that the suggested method can notably located degradation across disc winding.
Revolutionizing Thyroid Disease Forecasting with API Enhanced Convolutional Neural Networks International Journal of Intelligent Systems and Applications in Engineering, 2024
Health assessment of converter transformer pressboard insulation based on FDS and digital image processing Shrikant S. Mopari, D.S. More, A.S. Bhalchandra, Pannala Krishna Murthy, K.M. Jadhav, R.C. Kamble Measurement Sensors, 2023 The stable operation of the converter transformer is an essential task for power system operation reliability and security. Nowadays, Frequency domain spectroscopy (FDS) technology is prominently utilized for assessing oil-impregnated pressboard insulation. The present study examines the effect of the pressboard insulation material as a function of frequency and elevated temperature. The experimental analysis on oil-impregnated pressboard insulation is carried out at temperatures from 30 °C to 130 °C with an incremental rise of 20 °C intervals with frequency variation from 1Hz to 10MHz. The frequency-dependent permittivity, conductivity and loss tangent angle studies also confirm the deterioration of oil-impregnated pressboard insulation. The surface morphological changes inside the pressboard insulation are recorded with the help of scanning electron microscopy (SEM). The synergistic effect generated on pressboard insulation is examined by fiber width changeand image processing approach by randomly selecting the average of three local areas of SEM image.A canny operator is selected to extract the exact boundaries of images and more change is recorded in the edge detection count after 90 °C.The porosity and pore size distribution can be increased with elevated temperatures.A single-phase, 315 MVA valve side star winding with 60 discs of single-phase converter transformers model is developed in MATLAB Simulink. An impulse of 100kV, 1.2/50μsec is applied across the star winding to identify the pressboard insulation degradation derived from FDS data with the help of mathematical morphology and wavelet transform technique. The energy of the wavelet coefficient on the neutral current capture during the impulse test adds a significant contribution to analyzing pressboard insulation degradation. The results presented are in good agreement with the published work.
Degradation Assessment of Oil-Impregnated Paper Insulation for Converter Transformer Based on FDS using Digital Image Processing Shrikant S. Mopari, More D S, Bhalchandra A S, Pannala Krishna Murthy, Jadhav K M Ssrg International Journal of Electrical and Electronics Engineering, 2023 - 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.
Estimation of Inductance and Capacitance Parameters of Single Phase Dual Winding Converter Transformer with FEM Shrikant S. Mopari, D. S. More, Pannala Krishna Murthy, M. P. S. Chawla Proceedings 2022 IEEE 11th International Conference on Communication Systems and Network Technologies Csnt 2022, 2022 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.
A novel multi-objective firefly algorithm for optimization of association rules S. Neelima, N. Satyanarayana, P. Krishna Murthy Proceedings of the 2017 International Conference on Big Data Analytics and Computational Intelligence Icbdaci 2017, 2017 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.
Optimization of association rule mining using hybridized artificial bee colony (abc) with bat algorithm S. Neelima, N. Satyanarayana, P. Krishna Murthy Proceedings 7th IEEE International Advanced Computing Conference Iacc 2017, 2017 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.
Review-the identification and location of fault in VSC-HVDC transmission International Journal of Applied Engineering Research, 2015
A novel technique for the location of fault on a HVDC transmission line Journal of Engineering and Applied Sciences, 2011
EXPLAINABLE HYBRID MACHINE LEARNING PARADIGM FOR TRUSTWORTHY ADVERSARIAL DEFENSE BJD KALYANI, PK MURTHY, YL PRASANNA, M PADMAVATHI, ... Journal of Theoretical and Applied Information Technology 104 (1) , 2026 2026
Optimization of electric motor design using AI-based algorithm PK Murthy Nanotechnology Perceptions , 2025 2025 Citations: 2
Improved Power Transfer Capability of Micro-Grid Using Deep Learning Algorithms NNRSRA S. Venkateshwarlu, Pannala Krishna Murthy, A. Srujana Journal of Information Systems Engineering and Management 10 (20S), 581-600 , 2025 2025
Modeling and Control of Electric Vehicle Powertrains for Enhanced Efficiency SRHPKM Shrikant Shantaram Mopari Journal of Information Systems Engineering and Management 10 (3S), 284-299 , 2024 2024
Health assessment of converter transformer pressboard insulation based on FDS and digital image processing SS Mopari, DS More, AS Bhalchandra, PK Murthy, KM Jadhav, ... Measurement: Sensors 29, 100873 , 2023 2023 Citations: 3
Estimation of inductance and capacitance parameters of single phase dual winding converter transformer with FEM SS Mopari, DS More, PK Murthy, MPS Chawla 2022 IEEE 11th International Conference on Communication Systems and Network … , 2022 2022 Citations: 3
Estimation of Inductance and Capacitance Parameters of Single Phase Dual Winding Converter Transformer with FEM PKMMPSC S. S. Mopari, D. S. More 2022 IEEE 11th International Conference on Communication Systems and Network … , 2022 2022
Power System Stability Scanning and Security Assessment with Enhanced Feature Selection and Extraction Using Machine Learning PKMSN A.K.Srikanth Journal of Interdisciplinary Cycle Research 14 (1) , 2022 2022
Impact of Surges on Converter Transformer Insulation and Diagnostic Methods: A Survey SS Mopari, DS More, PK Murthy Design Engineering, 10806-10822 , 2021 2021
A Rectifier Topology for Low Power Harvesting Using Boost Converter SAPKM Shaik Rafi Ahmed 2nd International Conference on Engineering and Advancement in Technology … , 2021 2021
Enhancement of Power Quality by AI based Shunt Active DC Power Filter (SADPF) for Non Linear and Unbalanced Loads K Yaddanapudi, PK Murthy IJIEMR 10 (02) , 2021 2021
PERFORMANCE ANALYSIS OF FUZZY LOGIC CONTROLLED HYBRID ACTIVE DC FILTER (HADF) FOR 12-PULSE HVDC CONVERTER K YADDANAPUDI, PK MURTHY International Journal 9 (2) , 2021 2021 Citations: 4
Effect of Cost on Load Dispatch of Hybrid Power System aiming Economy P Sridevi, BR Reddy, PK Murthy 2020
Design and Analysis of Shunt Active Power Filter (SAPF) for Non Linear and Unbalanced Loads K Yaddanapudi, PK Murthy International Journal of Engineering and Advanced Technology (IJEAT), ISSN … , 2020 2020 Citations: 1
Design and Analysis of Shunt Active Power Filter (SAPF) for non-linear unbalanced loads Kiran Yaddanapudi and Pannala Krishna Murthy International Conference on Electrical, Electronics, Computers … , 2018 2018
Minimizing frequent itemsets using hybrid ABCBAT algorithm S Neelima, N Satyanarayana, P Krishna Murthy Data Engineering and Intelligent Computing: Proceedings of IC3T 2016, 91-97 , 2017 2017 Citations: 8
Analysis of power system faults in EHVAC line for varying fault time instances using wavelet transforms A Swetha, PK Murthy Journal of electrical systems and information technology 4 (1), 107-112 , 2017 2017 Citations: 7
A novel multi-objective firefly algorithm for optimization of association rules S Neelima, N Satyanarayana, PK Murthy 2017 International Conference on Big Data Analytics and Computational … , 2017 2017 Citations: 2
Optimization of association rule mining using hybridized artificial bee colony (ABC) with BAT algorithm S Neelima, N Satyanarayana, PK Murthy 2017 IEEE 7th international advance computing conference (IACC), 831-834 , 2017 2017 Citations: 4
A comprehensive survey on variants in artificial bee colony (ABC) S Neelima, N Satyanarayana, P Krishna Murthy International Journal of Computer Science and Information Technologies 7 (4 … , 2016 2016 Citations: 10
MOST CITED SCHOLAR PUBLICATIONS
Wavelet transform approach for detection and location of faults in HVDC system PK Murthy, J Amarnath, S Kamakshiah, BP Singh 2008 IEEE region 10 and the third international conference on industrial and … , 2008 2008.0 Citations: 107
A novel technique for the location of fault on a HVDC transmission line A Swetha, PK Murthy, N Sujatha, Y Kiran J. Eng. Appl. Sci 6 (11), 62-67 , 2011 2011.0 Citations: 20
A review on UPQC for power quality improvement in distribution system B Gopal, PK Murthy, GN Sreenivas Global Journal of Researches in Engineering Electrical and Electronics … , 2013 2013.0 Citations: 12
A comprehensive survey on variants in artificial bee colony (ABC) S Neelima, N Satyanarayana, P Krishna Murthy International Journal of Computer Science and Information Technologies 7 (4 … , 2016 2016.0 Citations: 10
A survey on approaches for mining frequent itemsets S Neelima, N Satyanarayana, PK Murthy IOSR Journal of Computer Engineering (IOSRJCE) 16 (4), 31-34 , 2014 2014.0 Citations: 9
Minimizing frequent itemsets using hybrid ABCBAT algorithm S Neelima, N Satyanarayana, P Krishna Murthy Data Engineering and Intelligent Computing: Proceedings of IC3T 2016, 91-97 , 2017 2017.0 Citations: 8
Analysis of power system faults in EHVAC line for varying fault time instances using wavelet transforms A Swetha, PK Murthy Journal of electrical systems and information technology 4 (1), 107-112 , 2017 2017.0 Citations: 7
Power quality improvement using UPQC integrated with distributed generation network B Gopal, PK Murthy, GN Sreenivas International Journal of Electrical and Computer Engineering 8 (7) , 2014 2014.0 Citations: 7
VSC-HVDC transmission system analysis using neural networks J Nandana, PK Murthy, S Durga International Journal of Engineering Science and Innovative Technology … , 2013 2013.0 Citations: 5
PERFORMANCE ANALYSIS OF FUZZY LOGIC CONTROLLED HYBRID ACTIVE DC FILTER (HADF) FOR 12-PULSE HVDC CONVERTER K YADDANAPUDI, PK MURTHY International Journal 9 (2) , 2021 2021.0 Citations: 4
Optimization of association rule mining using hybridized artificial bee colony (ABC) with BAT algorithm S Neelima, N Satyanarayana, PK Murthy 2017 IEEE 7th international advance computing conference (IACC), 831-834 , 2017 2017.0 Citations: 4
Health assessment of converter transformer pressboard insulation based on FDS and digital image processing SS Mopari, DS More, AS Bhalchandra, PK Murthy, KM Jadhav, ... Measurement: Sensors 29, 100873 , 2023 2023.0 Citations: 3
Estimation of inductance and capacitance parameters of single phase dual winding converter transformer with FEM SS Mopari, DS More, PK Murthy, MPS Chawla 2022 IEEE 11th International Conference on Communication Systems and Network … , 2022 2022.0 Citations: 3
Electrical measurements and measuring instruments S Kamakshaiah, PK Murthy, J Amarnath IK International Pvt Ltd , 2013 2013.0 Citations: 3
Power Quality Improvement using 24 pulse Bridge Rectifier for an Isolated Power Generation B Gopal, PK Murthy, GN Srinivas International Journal of Advanced and Innovative Research (IJAIR) 1 (3), 32-38 , 2012 2012.0 Citations: 3
Internal Fault Diagnosis of Hvdc Converter Transformer Using Wavelet Transform Technique PK Murthy, J Amarnath, S Kamakshaiah, BP Singh Proceedings of the 16th International Symposium on High Voltage Engineering … , 2009 2009.0 Citations: 3
Optimization of electric motor design using AI-based algorithm PK Murthy Nanotechnology Perceptions , 2025 2025.0 Citations: 2
A novel multi-objective firefly algorithm for optimization of association rules S Neelima, N Satyanarayana, PK Murthy 2017 International Conference on Big Data Analytics and Computational … , 2017 2017.0 Citations: 2
Integrating Blockchain and Machine Learning with 6G for Autonomous Vehicle Communication: Achieving Secure, Transparent, and Scalable V2X Networks PK Murthy, B Gopal, S Venkateshwarlu, A Srujana Citations: 2
Design and Analysis of Shunt Active Power Filter (SAPF) for Non Linear and Unbalanced Loads K Yaddanapudi, PK Murthy International Journal of Engineering and Advanced Technology (IJEAT), ISSN … , 2020 2020.0 Citations: 1
