Department of Electrical Engineering

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Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

The present report investigates hydrogen gas sensing properties on PAN/(PAN-b-PMMA) derived electrospun nanoporous carbon nanofibers loaded on ZnO nanostructures. Polymer blend of PAN and PAN-b-PMMA is used to obtain the high surface area porous CNF which improve further sensing performance. Moreover, a facile technique such as drop cast method is used to load the CNF (0.1–0.5 wt%) on Au pattern interdigitated electrodes over ZnO nanostructures. Loading of CNF was optimized to ensure proper connection between the electrodes over ZnO surface, which was measured using I–V characteristics. Initially, current decreased for less amount of CNF (0.1–0.2 wt%), which later increased for high concentration of CNF (0.3–0.5 wt%). It was further observed that 0.2 wt% CNF/ZnO nanostructures based sensor exhibited maximum sensing response (73.54%) as compared to CNF (3.29%) and ZnO (44.51%) for 100 ppm hydrogen at 150 °C. This enhanced sensing response may be attributed to diffusion of hydrogen molecules through the nanoporous CNF, thus enabling the formation of p - n heterojunction at the interface of CNF and ZnO. The presence of oxygen functional groups on CNF surface also contributes to the enhancement of the sensing performance. © 2019 Elsevier B.V.

World University root node

Sensors and Actuators, B: Chemical

PAN/(PAN-b-PMMA) derived nanoporous carbon nanofibers loaded on ZnO nanostructures for hydrogen detection

Real-time multiple event analysis is important for reliable situational awareness and secure operation of the power system. Multiple sequential events can induce complex superimposed pattern in the data and are challenging to analyze in real time. This paper proposes a method for accurate detection, temporal localization, and classification of multiple events in real time using synchrophasor data. For detection and temporal localization, a Teager-Kaiser energy operator (TKEO) based method is proposed. For event classification, a time series classification based method using energy similarity measure (ESM) is proposed. The proposed method is tested for simulated multiple event cases in the IEEE-118 bus system using DigSilent/PowerFactory and real PMU data for the Indian grid. © 2005-2012 IEEE.

IEEE Transactions on Industrial Informatics

Real-Time Multiple Event Detection and Classification in Power System Using Signal Energy Transformations

A superpixel based on-chip compression is proposed in this paper. Pixels are compared in spatial domain and the pixels with similar characteristics are grouped to form the superpixels. Only one pixel corresponding to each superpixel is read to achieve the compression. The on-chip compression circuit is designed and simulated in UMC 180 nm CMOS technology. For 70% compression, the proposed design results in about 33% power saving. The reconstruction of the compressed image is performed off-chip using bilinear interpolation. Further, two enhancement approaches are developed to improve the output image quality. The first approach is based on wavelet decomposition whereas the second approach uses a deep convolutional neural network. The proposed reconstruction technique takes two orders of magnitude lesser time as compared to the state-of-the-art technique. On an average, it results in peak signal to noise ratio (PSNR) and structural similarity index measure values of 30.999 and 0.9088 dB, respectively, for 70% compression in natural images. On the other hand, the best values observed from the existing approaches for the two metrics are 28.634 and 0.8115 dB, respectively. Further, the proposed technique is found useful for thermal image compression and reconstruction. The experiment shows that the compression of 86.2% can be achieved using the threshold of two intensity levels and the compressed image can be reconstructed with the PSNR of 45.87 dB. © 2018 IEEE.

IEEE Sensors Journal

Content Driven On-Chip Compression and Time Efficient Reconstruction for Image Sensor Applications

The presence of harmonic components in a power delivery network affects the performance of the high-speed systems. In this paper, harmonic distortion associated with a 12 V to 1.2 V open-loop buck converter (designed in the BCD 180 nm technology of STMicroelectronics) has been analyzed. The nonlinear behavior of a buck converter has been modeled using Volterra series for expected power supply ripples of 50 Hz. The analysis has been compared with simulation results and shows 5 %, 1 % and 7 % of mean relative error. The difference between the analytical and the simulation results for IP2h and IP3h are 2.7 dB and 3 dB, respectively. © 2017 IEEE.

ICECS 2017 - 24th IEEE International Conference on Electronics, Circuits and Systems

Nonlinear modeling and analysis of buck converter using volterra series

This paper presents a flexible and reliable chemiresistor-type NO2 gas sensor based on single-walled carbon nanotubes (SWNTs) on polytetrafluoroethylene (PTFE) membrane filter substrates. The sensor is realized by using a cost-effective spray coating in the preparation of SWNTs thin film, followed by the fabrication of metal contacts using a shadow mask and polyethyleneimine (PEI) noncovalent functionalization of the SWNTs. This showed a high sensitivity to NO2 gas at room temperature in dry air; 21.58% to 167.7% for concentrations of 0.75 ppm to 5 ppm, and was almost nonsensitive to ammonia. Gas sensing characterization results, obtained for various substrate bending/wrapping over different cylinders with diameters of 75 mm, 12.5 mm, and 6 mm showed that bending does not significantly affect sensitivity for NO2 concentrations of 0.75 ppm to 2 ppm, while in the case of 3 ppm to 5 ppm NO2, the bent samples indicate enhanced sensitivity. This is probably because of the porous nature of PTFE substrates; these sensors were 1.5 to 2.7 times more sensitive than those fabricated over silicon substrate for 1 ppm and 5 ppm, respectively. Moreover, the relative humidity of 10% and 30% significantly reduced the sensitivity of the sensors. The presented results could be useful for the future development of flexible electronics/sensors for monitoring outdoor air quality and for the detection of volatile organic compounds. © 2018 IOP Publishing Ltd.

Flexible and Printed Electronics

Flexible NO2 gas sensor based on single-walled carbon nanotubes on polytetrafluoroethylene substrates

This paper presents design and fabrication of MEMS 1-D micro mirror using thermally actuated bimorph actuator, for out of plane actuation application. Bimorph actuator was made of aluminum and silicon dioxide materials. Micro mirror performance was simulated using COMSOL multiphysics tool. Maximum displacement and temperature profile with voltage along micro mirror were presented. Aluminum was used as heater element as well as top layer of bimorph layer. Micro mirror was successfully released using surface micromachining with copper as sacrificial layer. © 2018 IEEE.

Proceedings of International Conference on 2018 IEEE Electron Device Kolkata Conference, EDKCON 2018

Design and Fabrication of Electro-Thermal 1-D Micro-Mirror

This work presents a protection algorithmto diagnose the fault and its type, using alienation coefficients of current signals, on a parallel transmission system. Alienation Coefficients are computed by comparing samples of post-fault current signals for successive cycles, obtained for a quarter cycle period. This Alienation Coefficient is compared with the threshold to detect the faulty phase and consequent classification of type of fault. Thus.the fault detection time for this algorithm is only a quarter cycle period. The performance of the proposed scheme has been established by various case studies in which fault locations, incipient angles and fault impedances are varied. © 2018 IEEE.

2018 3rd International Conference for Convergence in Technology, I2CT 2018

Transmission Line Fault Detection and Classification Using Alienation Coefficient Technique for Current Signals

Iris serves as one of the best biometric modality owing to its complex, unique and stable structure. However, it can still be spoofed using fabricated eyeballs and contact lens. Accurate identification of contact lens is must for reliable performance of any biometric authentication system based on this modality. In this paper, we present a novel approach for detecting contact lens using a Generalized Hierarchically tuned Contact Lens detection Network (GHCLNet). We have proposed hierarchical architecture for three class oculus classification namely: no lens, soft lens and cosmetic lens. Our network architecture is inspired by ResNet-50 model. This network works on raw input iris images without any pre-processing and segmentation requirement and this is one of its prodigious strength. We have performed extensive experimentation on two publicly available data-sets namely: 1) IIIT-D 2) ND and on IIT-K data-set (not publicly available) to ensure the generalizability of our network. The proposed architecture results are quite promising and outperforms the available state-of-the-art lens detection algorithms.

GHCLNet: A Generalized Hierarchically tuned Contact Lens detection Network

Renewable energy (RE) sources when integrated to utility network to form hybrid power system pose challenges in terms of stability and power quality. A method based on Stockwell's transform (S-transform) is presented in this paper for power quality (PQ) assessment and detection of islanding, outage and grid synchronization of renewable energy sources. Voltage signals are decomposed using multi-resolution analysis (MRA) of S-transform and features extracted are realized to assess the power quality disturbances associated with various events. Operational events are detected with the help of features extracted from the S-transform based decomposition of negative sequence component of voltage. A power quality index is proposed to rank the various operational events based on power quality. Proposed algorithm has been tested successfully on IEEE-13 bus test system with necessary modifications to integrate wind and solar PV generators to form the hybrid power system. Simulation results are validated in real time environment with the help of real time digital simulation (RTDS) system. © 2018 Elsevier B.V.

Electric Power Systems Research

Power quality assessment and event detection in hybrid power system

This paper considers collective circular motion of multi-agent systems in which all the agents are required to traverse different circles or a common circle at a prescribed angular velocity. It is required to achieve these collective motions with the heading angles of the agents synchronized or balanced. In synchronization, the agents and their centroid have a common velocity direction, while in balancing, the movement of agents causes the location of the centroid to become stationary. The agents are initially considered to move at unit speed around individual circles at different angular velocities. It is assumed that the agents are subjected to limited communication constraints, and exchange relative information according to a time-invariant undirected graph. We present suitable feedback control laws for each of these motion coordination tasks by considering a second-order rotational dynamics of the agent. Simulations are given to illustrate the theoretical findings. © 2017 Elsevier B.V.