Browsing by Author "Rao, K."

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A Comparative Study between Prony and Eigensystem Realization Algorithm for Identification of Electromechanical Modes
(Institute of Electrical and Electronics Engineers Inc., 2018) Sarkar, N.; Rao, K.; Shubhanga, K.N.
Two measurement-based ring-down electromechanical mode identification algorithms, namely Prony and Eigensystem Realization Algorithm (ERA) are taken up for a comparative study. Since the number of excited modes might vary in a practical power system, it is not easy to determine the model order. This requires an iterative procedure in case of Prony whereas a Singular Value Decomposition (SVD)-based technique achieves this directly in case of ERA as demonstrated through two case studies. It is further shown that ERA estimates the signal better and generates less number of trivial modes as compared to Prony. Â© 2018 IEEE.
A comparison of power system signal detrending algorithms
(Institute of Electrical and Electronics Engineers Inc., 2018) Rao, K.; Shubhanga, K.N.
Wide Area Measurement Systems (WAMS) have facilitated tracking of oscillations in power system response signals. This has provided an impetus for application of signal measurement-based modal detection methods such as matrix pencil and Prony analysis. Detrending, which means removal of trend in a signal, is a pre-requisite for effective functioning of these modal detection methods. In this work, performance of three methods of detrending viz., Center-of-Inertia (COI)-based detrending, MATLAB function-based detrending and 'Zhou' detrending are compared with particular reference to power system signals. It is indicated that COI-based detrending is better suited to detection of modes from slip signals of generators. Â© 2017 IEEE.
A Comparison of SVD-Augmented Prony Algorithms for Noisy Power System Signals
(Institute of Electrical and Electronics Engineers Inc., 2023) Rao, K.; Shubhanga, K.N.
The conventional Prony algorithm, which is the most prominent power system ring-down mode identification method, fails if the test signal is noisy [with a signal-to-noise ratio (SNR) below 20 dB]. The performance of Prony algorithm can be improved through singular value decomposition (SVD)-based rank reduction of the data matrix. Principal eigenvector (PE)-Prony and total least squares (TLS)-Prony are two known formulations of SVD-augmented Prony algorithms. In both PE-Prony and TLS-Prony algorithms, the Toeplitz structure of the linear prediction data matrix is lost upon SVD-based noise filtering. On the other hand, structured total least squares (STLS)-Prony algorithm retains the Toeplitz structure even after SVD-based filtering and is hence expected to perform better. But a formulation of STLS-Prony algorithm for power systems is not available in the literature. Hence, the same is developed successfully in this paper. As a prelude to the formulation of STLS-Prony algorithm, PE-Prony and TLS-Prony analyses of power system signals are discussed in detail, bringing out their nuances. Further, case studies are carried out on some benchmark power systems to demonstrate that all the three algorithms work successfully even at an SNR of 1 dB when the test signal has only inter-area modes. It is also shown that the performance of STLS-Prony algorithm is superior when the test signal has a highly damped local mode. Further, it is illustrated that by virtue of structure-preserving property, STLS-Prony algorithm is endowed with a unique filtering attribute although it has a longer execution time. © 2013 IEEE.
A Low-Complexity Solution for Optimizing Binary Intelligent Reflecting Surfaces towards Wireless Communication
(Multidisciplinary Digital Publishing Institute (MDPI), 2024) Janawade, S.A.; Krishnan, P.; Kandasamy, K.; Holla, S.S.; Rao, K.; Chandrasekar, A.
Intelligent Reflecting Surfaces (IRSs) enable us to have a reconfigurable reflecting surface that can efficiently deflect the transmitted signal toward the receiver. The initial step in the IRS usually involves estimating the channel between a fixed transmitter and a stationary receiver. After estimating the channel, the problem of finding the most optimal IRS configuration is non-convex, and involves a huge search in the solution space. In this work, we propose a novel and customized technique which efficiently estimates the channel and configures the IRS with fixed transmit power, restricting the IRS coefficients to (Formula presented.). The results from our approach are numerically compared with existing optimization techniques.The key features of the linear system model under consideration include a Reconfigurable Intelligent Surface (RIS) setup consisting of 4096 RIS elements arranged in a 64 × 64 element array; the distance from RIS to the access point measures 107 m. NLOS users are located around 40 m away from the RIS element and 100 m from the access point. The estimated variance of noise (Formula presented.) is 3.1614 (Formula presented.). The proposed algorithm provides an overall data rate of 126.89 (MBits/s) for Line of Sight and 66.093 (MBits/s) for Non Line of Sight (NLOS) wireless communication. © 2024 by the authors.
An Exposition ofÂ Digital Taylor-Fourier Transform
(Springer Science and Business Media Deutschland GmbH, 2024) Rao, K.; Shubhanga, K.N.
Digital Taylor-Fourier Transform (DTFT) is a Taylor series-based extension to Discrete Fourier Transform. It is becoming popular due to its ability to estimate off-nominal frequency phasors accurately, which is lacking in DFT, the conventional technique used in Phasor Measurement Units (PMUs). In light of this, a lucid presentation of the mathematical formulation of DTFT is considered instructive and hence the same is attempted here. Further, the ability of DTFT filter to accurately estimate off-nominal frequency phasors, off-nominal frequency harmonics and exponentially varying sinusoids is illustrated and reasoned out. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2024.
A Comparative Study between Prony and Eigensystem Realization Algorithm for Identification of Electromechanical Modes
(2018) Sarkar, N.; Rao, K.; Shubhanga, K.N.
Two measurement-based ring-down electromechanical mode identification algorithms, namely Prony and Eigensystem Realization Algorithm (ERA) are taken up for a comparative study. Since the number of excited modes might vary in a practical power system, it is not easy to determine the model order. This requires an iterative procedure in case of Prony whereas a Singular Value Decomposition (SVD)-based technique achieves this directly in case of ERA as demonstrated through two case studies. It is further shown that ERA estimates the signal better and generates less number of trivial modes as compared to Prony. � 2018 IEEE.
A comparison of power system signal detrending algorithms
(2018) Rao, K.; Shubhanga, K.N.
Wide Area Measurement Systems (WAMS) have facilitated tracking of oscillations in power system response signals. This has provided an impetus for application of signal measurement-based modal detection methods such as matrix pencil and Prony analysis. Detrending, which means removal of trend in a signal, is a pre-requisite for effective functioning of these modal detection methods. In this work, performance of three methods of detrending viz., Center-of-Inertia (COI)-based detrending, MATLAB function-based detrending and 'Zhou' detrending are compared with particular reference to power system signals. It is indicated that COI-based detrending is better suited to detection of modes from slip signals of generators. � 2017 IEEE.
Equivalence of Matrix Pencil and HTLS Ring-Down Electromechanical Mode Identification Algorithms
(Institute of Electrical and Electronics Engineers Inc., 2023) Rao, K.; Shubhanga, K.N.
Matrix pencil and Hankel total least squares (HTLS) are two popular ring-down electro- mechanical mode identification algorithms. The appeal of these algorithms can be attributed to faster execution due to the non-iterative procedure of model order determination based on singular value decomposition of the data matrix. In this paper, these two algorithms are shown to be equivalent - the data matrix in one being the transpose of that in the other. Although this equivalence is proved in the context of power systems, it is valid for other areas of system identification as well. Further, the performance of these algorithms is examined as noise level in the signal increases, and it is shown that these work right down to an SNR of 1 dB provided the signal has only poorly damped modes. © 2013 IEEE.
Fabrication and characterization of thermal evaporated n-Si/ p-ZnTe thin film heterojunction diodes
(2013) Rao, K.; Bangera, K.V.; Shivakumar, G.K.
The paper reports the fabrication and detailed electrical characterization of thermal evaporated n-Si/p-ZnTe thin film heterojunction diodes. The heterojunction diodes were prepared by depositing ZnTe films on n-Si substrates. The conduction mechanism, barrier height, space charge density and width of the depletion region were determined by I-V and C-V characteristics of the heterojunction diodes. The bandgap and activation energies of n-Si and p-ZnTe were also determined and a theoretical band diagram of n-Si/p-ZnTe heterojunction was drawn based on Anderson's model. © 2012 Elsevier B.V. All rights reserved.
Influence of substrate temperature and post deposition annealing on the properties of vacuum deposited ZnSe thin films
(2013) Rao, K.; Bangera, K.V.; Shivakumar, G.K.
The effects of substrate temperature and post deposition annealing on the structural, optical and electrical properties of vacuum deposited ZnSe thin films are presented here. The chemical composition of the films varied drastically with substrate temperature which in turn caused changes in various properties of the films. The grain size of the films increased with substrate temperature and also after annealing. The electrical properties of the films were found to be varying as a function of chemical composition and grain size. © 2012 Elsevier Ltd.
Influence of welding process parameters on microstructure and mechanical properties of friction stir welded aluminium matrix composite
(2017) Prabhu, S.; Shettigar, A.K.; Rao, K.; Rao, S.; Herbert, M.
In this study, the effect of process parameters on microstructure and mechanical properties of friction stir welded aluminium matrix composites(AMC) have been explored. The results indicated that the recrystallized grain size at the bottom of the weld region is smaller than that at the top region due to difference in the heat transfer at the weld region. The joint strength of AMCs depends on proper selection of process parameters like tool rotational speed and welding speed. If process parameter values are beyond the optimal value, the joint strength decreases due to formation of defects. Maximum tensile strength is obtained for rotational speed of 1000 rpm and welding speed of 80mm/min. � 2017 Trans Tech Publications, Switzerland.
Machining Parameters Optimization of AA6061 Using Response Surface Methodology and Particle Swarm Optimization
(2018) Lmalghan, R.; Rao, K.; ArunKumar, S.; Rao, S.S.; Herbert, M.A.
The influence of cutting parameters on the responses in face milling has been examined. Spindle speed, feed rate and depth of cut have been considered as the influential factors. In accordance with the design of experiments (DOE) a series of experiments have been carried out. The paper exemplifies on the optimizing the process parameters in milling through the application of Response surface methodology (RSM), RSM-based Particle Swarm Optimization (PSO) technique and Desirability approach. These aforesaid techniques have been applied to experimentally establish data of AA6061 aluminium material to study the effect of process parameters on the responses such as cutting force, surface roughness and power consumption. By adopting the multiple regression techniques, the interaction between the process parameters are acquired. The optimal parameters have been found by adopting the multi-response optimization techniques, i.e. desirability approach and PSO. The performance capability of PSO and desirability approach is investigated and found that the values obtained from PSO are comparable with the values of desirability approach. 2018, Korean Society for Precision Engineering and Springer-Verlag GmbH Germany, part of Springer Nature.
MAPE-An Alternative Fitness Metric for Prony Analysis of Power System Signals
(2018) Rao, K.; Shubhanga, K.N.
Phasor Measurement Units have facilitated tracking of oscillations in power system response signals. This has provided an impetus for identifying unstable component modes directly from oscillatory signals. Prony analysis, the earliest method proposed for this purpose, throws up some trivial modes. These not only distract the analyzer but also prolong processing time thereby delaying corrective action. Hence the fitness metric chosen should serve to minimize the number of trivial modes. The conventional fitness metric is Signal-To-Noise Ratio (SNR), which is actually Signal-To-Estimation error Ratio (SER). This paper proposes that Mean Absolute Percentage Error (MAPE) can also serve well as a fitness metric. It is shown through case studies carried out on well-known four-machine power system that there are a few cases where MAPE performs better than SER while in some instances SER works better. This inference is verified even in the presence of measurement noise. Hence a novel fitness metric is proposed combining MAPE with SER. Case studies on simulated signals obtained from New England-power system prove that this novel metric can achieve considerable reduction in processing time. Besides, an exponential binary search has been suggested for determining the optimal model order in minimum number of iterations. 2018 Walter de Gruyter GmbH, Berlin/Boston 2018.
MAPE-An Alternative Fitness Metric for Prony Analysis of Power System Signals
(De Gruyter peter.golla@degruyter.com, 2018) Rao, K.; Shubhanga, K.N.
Phasor Measurement Units have facilitated tracking of oscillations in power system response signals. This has provided an impetus for identifying unstable component modes directly from oscillatory signals. Prony analysis, the earliest method proposed for this purpose, throws up some trivial modes. These not only distract the analyzer but also prolong processing time thereby delaying corrective action. Hence the fitness metric chosen should serve to minimize the number of trivial modes. The conventional fitness metric is Signal-To-Noise Ratio (SNR), which is actually Signal-To-Estimation error Ratio (SER). This paper proposes that Mean Absolute Percentage Error (MAPE) can also serve well as a fitness metric. It is shown through case studies carried out on well-known four-machine power system that there are a few cases where MAPE performs better than SER while in some instances SER works better. This inference is verified even in the presence of measurement noise. Hence a novel fitness metric is proposed combining MAPE with SER. Case studies on simulated signals obtained from New England-power system prove that this novel metric can achieve considerable reduction in processing time. Besides, an exponential binary search has been suggested for determining the optimal model order in minimum number of iterations. © 2018 Walter de Gruyter GmbH, Berlin/Boston 2018.
Modal Analysis of Multi-machine Power System for Load Perturbation
(Institute of Electrical and Electronics Engineers Inc., 2019) Zala, D.; Kn, S.; Rao, K.
Load modeling has always been one of the important aspects of power system stability analysis. In this paper, efforts are made to study the modal behavior of multi-machine power systems for load perturbations. Provisions are made in the time-domain simulation environment to perturb different kind of load components by modeling them as ZIP loads. Resulting slip signals are subjected to Prony analysis to characterize the frequencies and damping of oscillations. Effects of continuous load variation on the power system stability is realized by performing random load perturbation in addition to sudden load changes. Further, an attempt is made to quantify the possible relation between the randomness of the continuous load change to the level of noise contamination in the slip signal of generators. Case studies are presented for 4-machine and 16-machine power systems. Â© 2019 IEEE.
Modified matrix of ZnO prismoid structures for improved photocatalytic activity: A theoretical and experimental insight
(Elsevier B.V., 2024) Manohar, A.; Kompa, A.; Christopher, B.; Shil, S.; Rao, K.; Udayshankar, N.K.; Mahesha, M.G.; Singh, V.; U, U.
Currently, the world needs low-cost and high-performance photocatalysts to degrade the carcinogenic pollutant from water. In the present work, a modified ZnO matrix using Mg as a dopant has been reported with theoretical and experimental results to highlight its structure and functions on photocatalytic activity. A versatile chemical co-precipitation technique was employed to get the Mg-ZnO nanostructures. Structural characterization by high-resolution transmission electron microscopy (HRTEM) and X-ray diffraction (XRD) studies show the formation of hexagonal wurtzite structures with no impurity phases. Optical studies confirm the formation of ZnO with intrinsic defects after modifying the matrix, which agrees with the band structure calculations computed using density functional theory (DFT). Mg-modified ZnO introduced intrinsic defects like vacancies and interstitials that have a great impact on applications like photocatalysis. Based on these supporting results we employed prepared samples for dye degradation, which performed well (80% degradation efficiency) in a short period of UV irradiation. This could be a promising technology for environmental remediation. © 2023 Elsevier B.V.
On the Ability of Eigensystem Realization Algorithm to Identify the Dominant System Modes
(Institute of Electrical and Electronics Engineers Inc., 2025) Rao, K.; Shubhanga, K.N.
Eigensystem realization algorithm (ERA) is a popular ring-down mode identification algorithm used for power system identification from wide area measurement systems. This essentially involves construction of a state matrix from the measured ring-down response signal through some matrix manipulation. The eigenvalues of the state matrix thus obtained are known to match with the dominant system modes excited upon the occurrence of a disturbance. However, a mathematical proof for the similarity of the state matrix thus constructed from the response signal to the reduced-rank state matrix obtained through detailed modelling of the system is not available. This paper ventures successfully in this direction by relating the Vandermonde- and singular value-decompositions of the data matrix pertaining to pulse response. Â© 2025 IEEE.
Ubiquitous greenhouse monitoring system
(2016) Rao, K.; Srijana, K.; Prasad, D.; Chandrasekaran, K.
A greenhouse is a structure generally made of glass, designed to provide protection and controlled environment to raise plants indoors. In order to achieve high quality and quantity of produce, proper management and data collection of the greenhouse environment is required. Manual practice of plant monitoring is laborious and time consuming. The proposed greenhouse system is an application which demonstrates the concept of Internet of Things and involves ubiquitous monitoring and controlling of environmental parameters within the greenhouse, which directly or indirectly control the plant growth and so their production. The system thus designed, mainly aims to remotely monitor and control the greenhouse using temperature sensor, light sensor, soil moisture, water level sensor and actuators through a customized webpage. Moreover, real-time representation of the sensed data is graphically plotted as well as stored for improved monitoring and further analysis, illustrating the concept of cloud instrumentation. � 2015 IEEE.
Ubiquitous greenhouse monitoring system
(Institute of Electrical and Electronics Engineers Inc., 2016) Rao, K.; Srijana, K.; Prasad, D.; Chandrasekaran, K.
A greenhouse is a structure generally made of glass, designed to provide protection and controlled environment to raise plants indoors. In order to achieve high quality and quantity of produce, proper management and data collection of the greenhouse environment is required. Manual practice of plant monitoring is laborious and time consuming. The proposed greenhouse system is an application which demonstrates the concept of Internet of Things and involves ubiquitous monitoring and controlling of environmental parameters within the greenhouse, which directly or indirectly control the plant growth and so their production. The system thus designed, mainly aims to remotely monitor and control the greenhouse using temperature sensor, light sensor, soil moisture, water level sensor and actuators through a customized webpage. Moreover, real-time representation of the sensed data is graphically plotted as well as stored for improved monitoring and further analysis, illustrating the concept of cloud instrumentation. Â© 2015 IEEE.