Department of Electrical Engineering

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IIT Jodhpur

Wind energy (WE) is emerging as a green and clean energy source. The power quality (PQ) significantly deteriorates when WE sources are connected to the weak ac grid. This is due to the variable wind speed, the impedance of weak grids, and nonlinear loads. This article proposes a methodology to improve the PQ in the weak grid with WE penetration using additional distribution static compensator (DSTATCOM). Fuzzy logic (FL) controller is implemented in the conventional synchronous reference frame (SRF) scheme to minimize the oscillations in the voltage signals. Also, a feedforward block of the WE source is incorporated in the FLSRF control scheme for adapting changes associated with the wind speed. The proposed control scheme accommodates the changes related to the grid's strength, wind speed, load currents, and dc-link voltage dynamics to estimate the switching signals for the DSTATCOM. The MATLAB simulation and experimental studies established the effectiveness of the proposed method for enhancing the PQ performance of weak grid-connected WE sources in the presence of nonlinear loads. © 1982-2012 IEEE.

World University root node

IEEE Transactions on Industrial Electronics

Performance Improvement of Weak Grid-Connected Wind Energy System Using FLSRF-Controlled DSTATCOM

Multimedia Systems

Edge-preserving image denoising using noise-enhanced patch-based non-local means

In the world of ever-growing technology and multimedia devices, educators around the globe are innovating newer ways to engage students in a more immersive and enjoyable way. Games have had a proven effect on marketing, sales, healthcare, behavioral changes, K12 education, and have now increasingly gained momentum in higher education, especially engineering education, primarily to enhance learner engagement and motivation. This paper presents a work-in-progress towards developing serious games as supplemental material in teaching the course on Basic Electronics. Two story boards of game-based learning are presented in this paper along with the design strategy and target core motivational drives. The game development is under progress and student reception and feedback is yet to be incorporated.

Game-based Learning for Engineering Education: Supplementing Basic Electronics Instruction with Educational Games

The use of smartphone cameras for capturing photographs has seen an exponential growth in the last decade. The noise present in these photographs significantly deviates from the popular Independently Identically Distributed (i.i.d.) Additive White Gaussian Noise (AWGN) noise, and thus the conclusions drawn from simulated-AWGN cannot be directly applied to the smartphone’s true noise. This paper is the first reporting of the exhibition of Stochastic Resonance (SR) or noise-induced threshold-crossing in three genres of discontinuity detectors used in image processing — corner detector, line detector, and edge detector for real-world smartphone images. For the images under investigation, the performance of these detectors is quantified w.r.t. parameters representing intrinsic noise. Observations suggest that all these detectors inherently exhibit the phenomenon of SR due to the fundamental assistance offered by controlled amount of noise in crossing detector thresholds. The manifestations of SR — constant parameter value with varying noise and varying parameter value with constant noise — are demonstrated to exhibit SR in each of the three detectors.

Fluctuation and Noise Letters

Exhibition of Noise-aided Stochastic Resonance by Discontinuity Detectors in Smartphone Images

Automatic modulation classification finds its application in many military and civil areas. It is an integral part of cognitive radio and software defined radio technologies. In this paper, LabVIEW based Field Programmable Gate Array (FPGA) implementation of modulation classification algorithm is proposed. Any modulation scheme among BPSK, QPSK, 8PSK, 8QAM, 16QAM and 4ASK is classified by alteration of oversampling factor and further error minimization between extracted constellation and ideal constellation of considered modulation schemes. Study results reveal that the developed method detects the above mentioned modulation schemes reliably above 12 dB SNR in Additive White Gaussian Noise (AWGN) channel. Comparative analysis of the proposed method with existing methods based on higher order statistics, mel-frequency ceptral coefficients and naive based modulation classification shows an overall improvement in classification accuracy.

Wireless Personal Communications

Blind Signal Modulation Classification Using Constellation Pattern Analysis with Oversampling Factor Alteration

Edge-preserving denoising using gradient-based estimation and iterative noise-aided processing

Preserving edges in a noisy environment is a challenging task as even some of the latest endto-end deep learning (DL) algorithms continue to struggle in achieving high pixel-level accuracy. As the Canny Edge Detector (CED) continues to be one of the most popular edge detection operators, this paper presents an enhanced CED using Stochastic Resonance (SR) guided threshold maneuvering and window mapping, which takes the same input parameter set as that of the conventional Canny but produces the edge map with better-connected edges and reduced noise. The SR-based analysis informs the steps that should be followed to enhance the performance of the classical CED. We also propose a new measure for efficient edge detection; a unique, efficient way of edge content extraction and its combination for various channels; and a framework to handle repercussions of the randomness of the noise. Since the proposed solution comes in the form of a modular patch-based framework, it can be easily incorporated into other algorithm developments. Qualitative and quantitative results are presented along with the BSDS500 &amp; BIPED benchmarking to showcase the proposed algorithm’s effectiveness. On BIPED benchmarking, our algorithm gives the human-level performance (F1 score .79), which is appreciable considering that it is a non-DL–based algorithm.

Fulltext

IEEE Access

Enhanced edge detection using SR-guided threshold maneuvering and window mapping: Handling broken edges and noisy structures in Canny Edges

Effective interactive video assignments and rewatch analytics for online flipped classrooms

The dependency of synchrophasor technology on shared/dedicated communication networks for data transfer and the lack of security specifications in C37.118 standard makes phasor measurements susceptible to data manipulation attacks. More critically, a false data injection attack could influence both accuracy of state esti-mates and the evaluation of system dynamics. Typically, false data sequences are modeled as multi-constraint non-linear optimization with random, step, or ramp type distribution. However, a carefully designed attack that mimics the dynamic response of a natural disturbance can hugely impact trends-based applications of synchrophasor-based disturbance monitoring and mode metering. This work designs a multi-channel/multi- sample dynamic injection attack in &nbsp;phasor trends to &nbsp;closely mimic natural disturbances aiming at &nbsp;trends- based applications. Also, the &nbsp;work proposes an un-supervised wavelet probability mapping method for &nbsp;the detection and correction of dynamic false data sequences. The proposed method identifies the attack sequences from disturbances using relative wavelet energy measure and &nbsp;replaces the &nbsp;corrupted sub-sequences with coherent un-corrupted trends using a kernel density estimation-based mode mapping method. The efficacy of the proposed method is validated for simulated injection cases in IEEE-118 bus system using DigSILENT/Power-Factory and real phasor data for the Eastern region of the India grid. The results show that the proposed method exhibits high detection accuracy and low correction error for different categories of dynamic false data cases under real system conditions.

International Journal of Electrical Power & Energy Systems

Wavelet probability distribution mapping for detection and correction of dynamic data injection attacks in WAMS

The notion of corona of two graphs was introduced by Frucht and Harary in 1970. In this paper, we generalize their definition of corona product of two graphs and introduce corona product of two signed graphs by utilizing the framework of marked graphs, which was introduced by Beineke and Harary in 1978. We study structural and spectral properties of corona product of signed graphs. Further, we define signed corona graphs by considering corona product of a fixed small signed graph with itself iteratively, and we call the small graph as the seed graph for the corresponding corona product graphs. Signed corona graphs can be employed as a signed network generative model for large growing signed networks. We study structural properties of corona graphs that include statistics of signed links, all types of signed triangles and degree distribution. Besides we analyze algebraic conflict of signed corona graphs generated by specially structured seed graphs. Finally, we show that a suitable choice of a seed graph can produce corona graphs which preserve properties of real signed networks. © 2022 World Scientific Publishing Company.